Evidence Report/Technology Assessment 

Number 151 

Nurse Staffing and Quality of Patient Care 

Prepared for: 

Agency for Healthcare Research and Quality 

U.S. Department of Health and Human Services 

540 Gaither Road 

Rockville, MD 20850 

www.ahrq.gov 

Contract No. 290-02-0009 

Prepared by: 

Minnesota Evidence-based Practice Center, Minneapolis, Minnesota 

Investigators

Robert L. Kane, M.D. 

Tatyana Shamliyan, M.D., M.S. 

Christine Mueller, Ph.D., R.N. 

Sue Duval, Ph.D. 

Timothy J. Wilt, M.D., M.P.H. 

AHRQ Publication No. 07-E005 

March 2007
This report is based on research conducted by the Minnesota Evidence-based Practice Center 

(EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ), Rockville, 

MD (Contract No. 290-02-0009). The findings and conclusions in this document are those of the 

author(s), who are responsible for its content, and do not necessarily represent the views of 

AHRQ. No statement in this report should be construed as an official position of AHRQ or of the 

U.S. Department of Health and Human Services. 

The information in this report is intended to help clinicians, employers, policymakers, and others 

make informed decisions about the provision of health care services. This report is intended as a 

reference and not as a substitute for clinical judgment. 

This report may be used, in whole or in part, as the basis for the development of clinical practice 

guidelines and other quality enhancement tools, or as a basis for reimbursement and coverage 

policies. AHRQ or U.S. Department of Health and Human Services endorsement of such 

derivative products may not be stated or implied. 
ii 

This document is in the public domain and may be used and reprinted without permission except 

those copyrighted materials noted for which further reproduction is prohibited without the 

specific permission of copyright holders. 

Suggested Citation: 

Kane RL, Shamliyan T, Mueller C, Duval S, Wilt T. Nursing Staffing and Quality of Patient 

Care. Evidence Report/Technology Assessment No. 151 (Prepared by the Minnesota Evidencebased Practice Center under Contract No. 290-02-0009.) AHRQ Publication No. 07-E005. 

Rockville, MD: Agency for Healthcare Research and Quality. March 2007. 

No investigators have any affilications or financial involvement (e.g., employment, 

consultancies, honoraria, stock options, expert testimony, grants or patents received or pending, 

or royalties) that conflict with material presented in this report. 
iii 

Preface 

 The Agency for Healthcare Research and Quality (AHRQ), through its Evidence-Based 

Practice Centers (EPCs), sponsors the development of evidence reports and technology 

assessments to assist public- and private-sector organizations in their efforts to improve the 

quality of health care in the United States. The reports and assessments provide organizations 

with comprehensive, science-based information on common, costly medical conditions, and new 

health care technologies. The EPCs systematically review the relevant scientific literature on 

topics assigned to them by AHRQ and conduct additional analyses when appropriate prior to 

developing their reports and assessments. 

 To bring the broadest range of experts into the development of evidence reports and health 

technology assessments, AHRQ encourages the EPCs to form partnerships and enter into 

collaborations with other medical and research organizations. The EPCs work with these partner 

organizations to ensure that the evidence reports and technology assessments they produce will 

become building blocks for health care quality improvement projects throughout the Nation. The 

reports undergo peer review prior to their release. 

 AHRQ expects that the EPC evidence reports and technology assessments will inform 

individual health plans, providers, and purchasers as well as the health care system as a whole by 

providing important information to help improve health care quality. 

 We welcome written comments on this evidence report. They may be sent to the Task Order 

Officer named below at: Agency for Healthcare Research and Quality, 540 Gaither Road, 

Rockville, MD 20850, or by email to epc@ahrq.gov.

Carolyn M. Clancy, M.D. Jean Slutsky, P.A., M.S.P.H. 

Director Director, Center for Outcomes and Evidence 

Agency for Healthcare Research and Quality Agency for Healthcare Research and Quality 

Beth A. Collins Sharp, Ph.D.,R.N. Ernestine Murray, M.A.S., R.N. 

Director, EPC Program EPC Program Task Order Officer 

Agency for Healthcare Research and Quality Agency for Healthcare Research and Quality 

 
iv 

Acknowledgments 

 We would like to thank David Jacobs, Ph.D., for his contribution to conceptualization and 

methodology of meta-analysis; the librarians Jim Beattie, MLIS, Lisa McGuire, MLIS, Judy 

Stanke, M.A., and Delbert Reed, Ph.D., for their contributions to the literature search; Kim 

Belzberg, R.N., B.S.N., and John Nelson, M.S., R.N., for assistance with the literature search and 

data abstraction; and Marilyn Eells for editing and formatting this report. We would also like to 

thank Mary Blegen, Ph.D., R.N., F.A.A.N., and Barbara Mark, Ph.D., R.N., F.A.A.N., for their 

cooperation in sharing their raw data. 

 We also want to thank Mary Blegen, Ph.D., M.A., B.S.N., R.N.; Peter Buerhaus, Ph.D., R.N., 

M.S., F.A.A.N.; Sean Clarke, Ph.D., M.S., B.A., B.S., C.R.N..P, R.N.; Linda McGillis-Hall, 

Ph.D., M.Sc., B.A.S., R.N.; and Linda O’Brien-Pallas, Ph.D., M.Sc.N., B.Sc.N., R.N., for 

reviewing the draft of this report and providing us with helpful recommendations for revisions 

and clarifications. 
v 

Structured Abstract 

Objectives: To assess how nurse to patient ratios and nurse work hours were associated with 

patient outcomes in acute care hospitals, factors that influence nurse staffing policies, and nurse 

staffing strategies that improved patient outcomes. 

Data Sources: MEDLINE® (PubMed®), CINAHL, Cochrane Databases, EBSCO research 

database, BioMed Central, Federal reports, National Database of Nursing Quality Indicators, 

National Center for Workforce Analysis, American Nurses Association, American Academy of 

Nurse Practitioners, and Digital Dissertations. 

Review Methods: In the absence of randomized controlled trials, observational studies were 

reviewed to examine the relationship between nurse staffing and outcomes. Meta-analysis tested 

the consistency of the association between nurse staffing and patient outcomes; classes of patient 

and hospital characteristics were analyzed separately. 

Results: Higher registered nurse staffing was associated with less hospital-related mortality, 

failure to rescue, cardiac arrest, hospital acquired pneumonia, and other adverse events. The 

effect of increased registered nurse staffing on patients safety was strong and consistent in 

intensive care units and in surgical patients. Greater registered nurse hours spent on direct patient 

care were associated with decreased risk of hospital-related death and shorter lengths of stay. 

Limited evidence suggests that the higher proportion of registered nurses with BSN degrees was 

associated with lower mortality and failure to rescue. More overtime hours were associated with 

an increase in hospital related mortality, nosocomial infections, shock, and bloodstream 

infections. No studies directly examined the factors that influence nurse staffing policy. Few 

studies addressed the role of agency staff. No studies evaluated the role of internationally 

educated nurse staffing policies. 

Conclusions: Increased nursing staffing in hospitals was associated with lower hospital-related 

mortality, failure to rescue, and other patient outcomes, but the association is not necessarily 

causal. The effect size varied with the nurse staffing measure, the reduction in relative risk was 

greater and more consistent across the studies, corresponding to an increased registered nurse to 

patient ratio but not hours and skill mix. Estimates of the size of the nursing effect must be 

tempered by provider characteristics including hospital commitment to high quality care not 

considered in most of the studies. Greater nurse staffing was associated with better outcomes in 

intensive care units and in surgical patients.

vii 

Contents 

Executive Summary........................................................................................................................ 1 

Evidence Report............................................................................................................................ 7 

Chapter 1. Introduction ................................................................................................................... 9 

 Overview .................................................................................................................................. 9 

Chapter 2. Methods....................................................................................................................... 21 

 Literature Search Strategy and Eligibility Criteria ................................................................. 21 

 Search Strategy................................................................................................................. 21 

 Eligibility.......................................................................................................................... 21 

 Data Synthesis .................................................................................................................. 23 

Chapter 3. Results ......................................................................................................................... 25 

 Association Between Nursing Hours and Ratios and Patient Outcomes................................ 26 

 Distribution of Nurse Staffing Hours and Ratios ................................................................... 26 

Question 1. Association Between Nurse to Patient Ratios and Hospital-Related 

Mortality........................................................................................................................... 26 

 Nurse Ratios and Mortality .............................................................................................. 26 

 Association Between Nurse to Patient Ratios and Nurse Sensitive Patient 

Outcomes.................................................................................................................... 28 

Question 2. Association Between Nurse Hours per Patient Day and Patient 

Outcomes.......................................................................................................................... 31 

 Total Nurse Hours per Patient Day and Hospital Related Mortality................................ 31 

Question 3. What Factors Influence Nurse Staffing Policies? ............................................... 36 

 Staffing Ratios/Mix/Hours ............................................................................................... 37 

Question 4. Association Between Nurse Staffing Strategies and Patient Outcomes.............. 42 

 Patient Outcomes Corresponding to an Increase by 1 Percent in the Proportion 

of RNs ........................................................................................................................ 42 

 Patient Outcomes Corresponding to an Increase by 1 Percent in the Proportion 

of Licensed Nurses..................................................................................................... 43 

 Patient Outcomes Corresponding to an Increase by 1 Percent in Overtime 

Hours .......................................................................................................................... 44 

 Patient Outcomes Corresponding to an Increase by 1 Percent in Contract Hours ........... 44 

Chapter 4. Discussion ................................................................................................................... 91 

 Association or Cause ........................................................................................................ 91 

 Marginal Effects ............................................................................................................... 92 

 Nurse Staffing and Patient Outcomes in Hospitals .......................................................... 93 

 Staffing Measures............................................................................................................. 93 

 Care Setting ...................................................................................................................... 94 

 Other Factors .................................................................................................................... 95 

 Policy Implications........................................................................................................... 96 

 Strength of the Evidence .................................................................................................. 97 
viii 

 Recommendations for Future Research............................................................................ 97 

References and Included Studies ................................................................................................ 105 

List of Acronyms/Abbreviations................................................................................................. 115 

Tables

Table 1. Operational Definitions.............................................................................................. 14 

Table 2. Distribution of the Studies’ Quality (94 Studies)....................................................... 47 

Table 3. Distribution of Nurse Hours and Ratios (94 Studies) ................................................ 48 

Table 4. Hospital Related Mortality Rates Corresponding to Changes in Patients/RN 

Ratio (Pooled Weighted Estimates from Published Studies)..................................... 49 

Table 5. RN to Patient Ratios and Relative Risk of Hospital Related Mortality 

(Pooled Adjusted Estimates from Published Studies)................................................ 50 

Table 6. Number of Avoided Deaths/1,000 Hospitalized Patients Attributable to 

RN/Patient Day Ratio (Pooled Adjusted Estimates from Published Studies)............ 53 

Table 7. Calculated Relative Risk of Hospital-Related Mortality Corresponding to 

Increased RN Staffing (Results from Individual Studies).......................................... 54 

Table 8. Association Between RN Staffing Ratio and Mortality and Proportion of 

Mortality Attributable to Nurse Staffing (Results from Individual Studies) ............. 55 

Table 9. Correlation Between Nurse Staffing and Age Adjusted Fatal Adverse 

Events Related to Medical Care at the State Level .................................................... 56 

Table 10. Association Between Nurse Education, Experience, and Mortality .......................... 57 

Table 11. Patient Outcomes Rates (%) Corresponding to an Increase in RN Staffing 

Ratios (Pooled Estimation from the Published Studies) ............................................ 58 

Table 12. Relative Risk of Patient Outcomes Corresponding to an Increase in RN 

Staffing Ratios (Pooled Estimation from the Studies) ............................................... 59 

Table 13. Length of Stay Corresponding to an Increase in RN Staffing Ratios (Pooled 

Analysis) .................................................................................................................... 62

Table 14. Patient Outcomes Rates (%) Corresponding to an Increase by 1 Hour in 

Total Nursing Hours/Patient Day (Pooled Analysis) ................................................. 67 

Table 15. Patient Outcomes Rates (%) Corresponding to an Increase by 1 Hour in RN 

Hours/Patient Day (Pooled Analysis Reported by the Authors and 

Estimated RN Hours/Patient Day) ............................................................................. 69 

Table 16. Patient Outcomes Rates (%) Corresponding to an Increase by 1 Hour in 

LPN/LVN Hours/Patient Day (Pooled Analysis)....................................................... 72 

Table 17. Differences in Outcomes Rates (%) in Quartiles of Total Nursing 

Hours/Patient Day Distribution (Pooled Analysis) .................................................... 75 

Table 18. The Distribution of Nurse Skill and Experience Mix, Nurse Education, and 

Proportion of Temporary and Full-Time Nurse Hours .............................................. 78 

Table 19. Calculated Changes in Rates of Patient Outcomes Corresponding to an 

Increase by 1% in the Proportion of RNs................................................................... 79 

Table 20. Relative Risk of Patient Outcomes Corresponding to an Increase by 1% in 

Licensed Nurse Hours ................................................................................................ 86 
ix 

Table 21. The Number of Patient Adverse Events that Could be Avoided by 

Additional 8 RN Hours a Patient Receives During 24 Hours in a Hospital............... 99 

Table 22. The Proportion of Patient Adverse Events (%) that Could be Avoided by 

Reducing the Number of Patients Assigned to an RN During an 8-Hour 

Shift .......................................................................................................................... 100 

Table 23. Relative Risk of Mortality and Nurse Sensitive Patient Outcomes 

Corresponding to One Unit Increase in Nurse Staffing Ratios and Hours 

(Pooled Estimates) ................................................................................................... 101 

Table 24. Consistent Across the Studies, Significant Association Between Nurse 

Staffing and Patient Outcomes (Results from Pooled Analysis), 

Attributable to Nurse Staffing Proportion of Events, and Number of 

Avoided Events Per 1,000 Hospitalized Patients..................................................... 103 

Figures 

Figure 1. Conceptual Framework of Nurse Staffing and Patient Outcomes ............................. 13 

Figure 2. Factors Affecting Nurse Staffing Policies.................................................................. 18 

Figure 3. Nurse Staffing Strategies and Patient Outcomes ....................................................... 19 

Figure 4. Flow of Study Selection for Questions 1, 2, and 4..................................................... 46 

Figure 5. Relative Risk of Patient Hospital-Related Mortality Corresponding to 

Change in Registered Nurse to Patient Ratio (Pooled Estimation from the 

Studies)....................................................................................................................... 51 

Figure 6. Relative Risk of Death Among Different Categories of Patients/RN/Shift 

(Pooled Analysis) ....................................................................................................... 52 

Figure 7. Patient Outcomes Rates (%) Corresponding to an Increase by Patient per 

LPN/LVN per Shift (Calculated from One Study) .................................................... 60 

Figure 8. Patient Outcomes Rates (%) Corresponding to an Increase by 

Patient/UAP/Shift (Estimates from Individual Studies and Pooled Analysis)........... 61 

Figure 9. Relative Changes in LOS Corresponding to an Increase in RN Staffing 

Ratios (Pooled Estimation from the Studies) ............................................................. 63 

Figure 10. Relative Risk of Hospital Acquired Infections in Quartiles of 

Patients/RN/Shift Distribution (Pooled Analysis) ..................................................... 64 

Figure 11. Relative Risk of Patient Outcomes in Quartiles of Patients/RN/Shift 

Distribution (Pooled Analysis)................................................................................... 65 

Figure 12. Relative Risk of Patient Outcomes in Quartiles of Patients/RN/Shift 

Distribution (Pooled Analysis)................................................................................... 66 

Figure 13. Relative Risk of Patient Outcomes Corresponding to an Increase by 1 Hour 

in Total Nursing Hours/Patient Day........................................................................... 68 

Figure 14. Relative Risk of Patient Outcomes Corresponding to an Increase by 1 Hour 

in RN Hours/Patient Day (Pooled Analysis).............................................................. 70 

Figure 15. Relative Risk of Outcomes Corresponding to an Increase by 1 Hour in RN 

Hours/Patient Day (Pooled Analysis Combined from Reported and 

Estimated Hours)........................................................................................................ 71 

Figure 16. Patient Outcomes Rates (%) Corresponding to an Increase by 1 Hour in 

UAP Hours/Patient Day (Pooled Analysis) ............................................................... 73 
x 

Figure 17. Changes in LOS Corresponding to an Increase by 1 Nursing Hour/Patient 

Day (Pooled Analysis) ............................................................................................... 74 

Figure 18. Relative Risk of Patient Outcomes in Quartiles of RN Hours/Patient Day 

(Pooled Analysis of RN Hours Reported by the Authors and Estimated 

from RN Ratios .......................................................................................................... 76 

Figure 19. Patient Outcome Rates Corresponding to an Increase in Nurses’ Education 

and Experience (Results from Individual Studies)..................................................... 77 

Figure 20. Calculated Changes in Rates of Patient Outcomes Corresponding to an 

Increase by 1% in the Proportion of RNs................................................................... 81 

Figure 21. Relative Risk of Patient Outcomes Corresponding to an Increase by 1% in 

the Proportion of RNs (Pooled Analysis)................................................................... 82 

Figure 22. Relative Risk of Hospital Related Mortality and Failure to Rescue 

Corresponding to an Increase by 1% in the Proportion of RNs (Results 

from Individual Studies and Pooled Estimates) ......................................................... 83 

Figure 23. Relative Risk of Patient Outcomes Corresponding to an Increase by 1% in 

the Proportion of RNs (Results from Individual Studies and Pooled 

Estimates)................................................................................................................... 84

Figure 24. Relative Risk of Treatment Complications Corresponding to an Increase by 

1% in the Proportion of RNs (Results from Individual Studies and Pooled 

Estimates)................................................................................................................... 85

Figure 25. Relative Risk of Hospital Related Mortality and Failure to Rescue 

Corresponding to an Increase by 1% in the Proportion of Licensed Nurses ............. 89 

Figure 26. Relative Risk of Patient Outcomes Corresponding to an Increase by 1% in 

the Proportion of Licensed Nurses............................................................................. 90 

Figure 27. Relative Risk of Outcomes Corresponding to an Increase by RN 

FTE/Patient Day Consistent Across the Studies ........................................................ 98 

Appendixes 

Appendix A: Exact Search Strings 

Appendix B: List of Excluded Studies 

Appendix C: Technical Expert Panel Members and Affiliation 

Appendix D: Sample Abstraction Forms 

Appendix E: Quality of the Studies 

Appendix F: Analytic Framework 

Appendix G: Evidence Tables 

Appendix and Evidence Tables for this report are provided electronically at 

http://www.ahrq.gov/downloads/pub/evidence/pdf/nursestaff/nursestaff.pdf . 
1 

Executive Summary 

Introduction 

 A shortage of registered nurses, in combination with increased workload, has the potential to 

threaten quality of care.1-3 Increasing the nurse to patient ratios has been recommended as a 

means to improve patient safety.4,5 However, the cost effectiveness of increasing registered nurse 

(RN) staffing is controversial.6,7

 This systematic review analyzes associations between hospital nurse staffing and patient 

outcomes with consideration of variables that could influence the primary association. The basic 

research questions were: 

1. How is a specific nurse to patient ratio associated with patient outcomes (i.e., mortality; 

adverse drug events, nurse quality outcomes, length of stay; patient satisfaction with 

nurse care)? How does this association vary by patient characteristics, nurse 

characteristics, organizational characteristics, and nursing outcomes? 

2. How is a measure of nurse work hours (hours per patient or patient day) associated with 

the same patient outcomes? 

3. What factors influence nurse staffing policies? 

4. What nurse staffing strategies are effective for improving the patient outcomes listed in 

question 1? 

5. What gaps in research on nurse staffing and patient outcomes can be identified to address 

in future studies? 

 Questions 1, 2, and 4 are addressed in the systematic review using meta-analytic approaches. 

The literature associated with question 3 does not lend itself to meta-analysis. 

 Questions 1 and 2 address the same basic association but employ two different measures of 

nurse staffing. The nurse to patient ratio relies on a general ratio, which may include all nurses 

assigned to a unit, including non-clinical time, whereas nurse work hours look specifically at 

nurses involved in patient care. Even beyond this distinction, the varied ways staffing rates are 

calculated complicates pooling data. 

Methods 

 Observational studies from from 1990 to 2006 from the United States and Canada were 

reviewed for questions 1, 2, and 4. Studies for question 3 addressed implications for nurse 

staffing policies. No studies primarily empirically examined a specific nurse staffing policy. 

Sources included journal articles, administrative reports, and dissertations. 

 For questions 1, 2, and 4, we present the relative risks of nurse staffing levels on various 

patient outcomes adjusted for measured confounding factors. Meta-analysis was used to test the 

consistency of the association between nurse staffing and both patient outcomes and economic 

outcomes (e.g., length of stay); the analyses were conducted separately for classes of patients and 

hospital characteristics. 
2 

Results 

 Of the 94 eligible studies from 96 reports, 7 percent were case-control studies; 3 percent 

were case-series; 44 percent were cross-sectional studies; 46 percent assessed temporality in the 

association between nurse staffing and patient outcomes. The overall quality of the studies 

averaged 38 (of a possible 50). 

Patient Outcomes and Nurse Staffing Ratios 

 Consistent evidence from observational studies suggests that an increase in Registered 

Nurse (RN) to patient ratios was associated with a reduction in hospital-related mortality, failure 

to rescue,1

 and other nurse sensitive outcomes, as well as reduced length of stay (LOS), after 

adjustment for patient and provider characteristics but does not establish a causal relationship. 

The effect size is greater in surgical patients; ratios less than 2.5 patients per RN per shift in 

intensive care units (ICUs) and less than 3.5 patients per RN in surgical units were associated 

with the largest risk reduction based on quartiles of nurse staffing ratios. 

 Pooled results showed that every additional RN full time equivalent (FTE) per patient 

day was associated with a relative risk reduction in hospital-related mortality by 9 percent in 

intensive care units and 16 percent in surgical patients.8-21 If the relationship were indeed causal, 

we estimate that an increase by one RN FTE per patient day would save five lives per 1,000 

medical patients, and six per 1,000 surgical patients. Reducing the workload from more than six 

to two or less patients per RN per shift would save 25 lives per 1,000 hospitalized patients and 

15 lives per 1,000 surgical patients. A further reduction from two to four patients to less than 1.5 

patients per RN would save four lives per 1,000 hospitalized patients and nine lives per 1,000 

surgical patients. However, staffing rates of this magnitude may not be realistic. 

 Every additional patient per RN per shift was associated with a 7 percent increase in 

relative risk of hospital acquired pneumonia,13,14,22 a 53 percent increase in pulmonary 

failure,13,14,23,24 a 45 percent increase in unplanned extubation,13,14,23-25 and a 17 percent increase 

in medical complications.13,23,24 The increase in relative risk of unplanned extubation and 

pulmonary failure was higher and in hospital acquired pneumonia was lower, corresponding to 

an increase in patients per nurse ratios. We estimated that if the relationship were causal, one 

additional patient per RN per shift would result in 12 additional cases of failure to rescue, six 

cases of pulmonary failure, and five accidental extubations per 1,000 hospitalized patients. 

 The associations vary by clinical settings and patient population. In ICUs, an increase by 

one RN FTE per patient day was associated with a consistent decrease across studies in relative 

risk of these patient outcomes: a 28 percent decrease of cardiopulmonary resuscitation,13,23,24 a 

51 percent decrease of unplanned extubation,13,14,23-25 a 60 percent decrease of pulmonary 

failure,13,14,23,24 and a 30 percent decrease of hospital acquired pneumonia.13,14,22 In surgical 

patients, an increase of one RN FTE per patient day was associated with a consistent reduction in 

the relative risk of failure to rescue by 16 percent,12,15,16,20,21 and in nosocomial bloodstream 

infections of 31 percent. 

 

1

 The number of deaths in patients who developed an adverse occurrence among the number of patients who 

developed an adverse occurrence. 
3 

 The data on other nursing personnel is limited and not replicable in the studies. LOS was 

shorter by 24 percent in ICUs and by 31 percent in surgical patients, corresponding to an 

additional RN FTE per patient day.8,9,13,14 

Patient Outcomes and Nurse Staffing Hours

 An increase in total nurse hours per patient day was associated with reduced hospital 

mortality, failure to rescue, and other adverse events. The death rate decreased by 1.98 percent 

for every additional total nurse hours per patient day (95 percent confidence interval [CI] 0.96-3 

percent).26-29 The association with RN hours per patient day did not show significant changes in 

mortality rates.26-29 The relative risk of death was lower by 1 percent per 1 additional RN hour 

per patient day in ICUs8,9,13,14,16 and in medical8,10,11,17-19,26,27,30-32 and surgical patients.9,12-

16,20,26,27 The association between LPN/LVN hours per patient day and death rate was not 

consistent across studies.17,20,26,27,33,34

 The association between patient outcomes and RN and LPN/LVN hours was inconsistent 

across the studies. Pooled analysis showed that 1 additional RN hour per patient day was 

associated with a reduction in relative risk of hospital acquired pneumonia by four percent,13,14,22

pulmonary failure by 11 percent,13,14,23,24 unplanned extubation by 9 percent in ICUs,13,14,23-25

failure to rescue by 1 percent in surgical12,15,16,20,26,27,30 and medical patients,26,27,35 and deep 

venous thrombosis by 2 percent in medical patients.27,35

 The LOS in hospitals was lower for additional total nursing, but not for licensed 

LPN/LVN and unlicensed assistive personnel (UAP) hours. The association between RN hours 

and LOS was not consistent across studies. 

Other Attributes of Nursing 

 There was a significant negative correlation between the percentage of nurses with 

Bachelor of Science in Nursing (BSN) degrees and the incidence of deaths related to health care 

(r = -0.46, p = 0.02). Nurse job satisfaction and autonomy was associated with a significant 

reduction in the risk of death. An increase in nurse turnover increased the rate of patient falls by 

0.2 percent.36

 Staffing policies examined for this review related to the shift length, scheduling nurses to 

rotate to different shifts, mandatory overtime, weekend staffing, use of agency or temporary 

nurses, assigning nurses to nursing units other than those they are regularly assigned to work 

(floating), use of full-time, part-time, and internationally educated nurses (IENs), the nurse-topatient ratio or nursing hours per patient day for nursing units, and the skill mix (licensed vs. 

unlicensed staff) of nursing units. Overall, few studies for any of these staffing policy variables 

limited drawing any conclusions. Trends in the literature suggested that rotating shifts may have 

negative effects on nurses’ stress levels and job performance perceptions. Further, several studies 

indicated that nurses working longer hours may have a negative impact on patient outcomes and 

safety. No research provides guidance on the impact or effective use of agency/temporary staff. 

Research on the use and effectiveness of IENs in U.S. hospitals37 includes qualitative exploratory 

studies38,39 and descriptive studies40-42 that examined IEN use in healthcare. No studies 

empirically evaluated the interaction of IEN staffing policies with organizational, nurse, or 

patient care unit factors. 
4 

 Within the limits of scant literature, RN overtime is not associated with the location of 

the hospital, teaching status of the hospital, average hours in a nurses’ work week, acute bed 

occupancy, acute average daily census, or financial margin of the hospital.37,42-44 More overtime 

hours were associated with an increase in hospital-related mortality, nosocomial infections, 

shock, and bloodstream infections. The proportion of float nurses was positively associated with 

the risk of nosocomial bloodstream infections.45-47 More contract hours was associated with an 

increase in LOS.28,45,48,50

Discussion 

 This review confirms previous contentions that increased nurse staffing in hospitals is 

associated with better care outcomes,51 but this association has not been shown to reflect a causal 

relationship. Hospitals that invest in more nurses may also invest in other actions that improve 

quality. Magnet hospitals that are said to provide high quality care have better nurse staffing 

strategies.10,52 Overall hospital commitment to a high quality of care in combination with 

effective nurse retention strategies leads to better patient outcomes, patient satisfaction with 

overall and nursing care, and nurse satisfaction with job and provided care.10,52-59

 Two general measures of nurse staffing were studied.60 One addressed hours of care provided 

by nursing staff averaging FTEs of different nurse categories at the hospital level,11,18,19

sometimes including only productive hours worked in direct care.28,61,62 The other relies on less 

precise data of total nurse staffing to patient volume derived from administrative databases61,63-65

averaging annual nurse to patient ratios20 at the hospital or unit level.20 The ratio of patients per 

RN per shift ratio was more frequently used and provided greater evidence of the effect, but both 

showed generally the same trends. 

 The effect size varied with the nurse staffing measure. The reduction in relative risk of 

hospital related mortality was 16 percent for one RN FTE per patient day, and 1 percent for an 

additional RN hour per patient day in surgical patients. Assuming that every additional RN FTE 

per patient day would provide approximately 8 additional RN hours per patient day, the expected 

reduction should be more than observed in the studies that examined the risk of mortality in 

relation to nurse hours. The comparison of the effect size on patient outcomes among quartiles of 

patients per RN per shift ratio and nurse hours per patient day detected the same pattern; the 

maximum reduction in relative risk of hospital-related mortality and adverse events occurred 

when no more than two patients were assigned to an RN and more than 11 nurse hours were 

spent per 1 patient day. We did not find consistent evidence that a further increase in RN FTE 

per patient day ratio can provide better patient safety. The evidence of the effects of LPN/LVNs 

and UAP were limited and inconsistent. 

 It is difficult to transition between nurse hours and nurse-to-patient ratios. Nurse hours per 

patient day reflect average staffing across a 24-hour period and do not reflect fluctuations in 

patient census, scheduling patterns during different shifts (even the length of shifts varies),9,13 

and periods of the year.66,67 They do not account for the time nurses spend in meetings, 

educational activities, and administrative work. 

 Nurse staffing could have a different effect in different hospital settings. The addition of one 

unit of nursing care may depend on the baseline rate. The effect of an additional nurse hour 

might be quite dissimilar in ICUs and typical hospital units. As shown in previous studies,26,27

the present meta-analysis found consistent evidence that surgical patients are sensitive to nurse 

staffing. 
5 

 The size of the nursing effect must be tempered by all the other factors not considered in 

most of these studies. No direct measure of other influences on outcomes is typically made. The 

traditional concerns about factors that affect quality of care, such as the nature of the primary 

medical and surgical treatment and the skill of the physician staff, are not addressed and are 

assumed to be evenly distributed to yield noise, but not bias. Many of the studies are performed 

on data collected at the hospital level over a long period of time. Adjustments for comorbidity 

depend on simple averages. 

 Skill, organization, and leadership undoubtedly play a role but are much more difficult to 

assess. Skill mix did not demonstrate consistent associations with tested patient outcomes in the 

present review. Nurse competence requirements include education, expertise, and experience68,69

Nurse education was associated with lower mortality. The importance of nurses’ professional 

competence and performance have been discussed with regard to developing standards of nurse 

performance to encourage high quality of care.70-73

Conclusions 

 Increased nurse staffing in hospitals is associated with better care outcomes, but this 

association is not necessarily causal. The effect size varied with the nurse staffing measure and 

sites of patient care (i.e., ICU, medical vs. surgical units). The size of the nursing effect must be 

tempered by all the other factors not considered in most of these studies. 

Future Research 

 Future observational studies will need to take cognizance of the many other factors that 

can affect the outcomes of interest, especially medical care, patient characteristics, and 

organization of nursing units and staffs. Larger multi-center studies will be needed. More studies 

should be conducted at the patient level to allow for better control of issues like comorbidity. 

Hierarchical models that control for both institutional and nursing effects could be employed. 

Nonetheless, it is unlikely that all the salient variables can be addressed in any one study. Future 

work will need to target specific questions and collect and analyze enough information to isolate 

the effects of nurse staffing levels. 

Evidence Report

9 

Chapter 1. Introduction 

Overview 

 Reports from the Institute of Medicine addressing quality of health care provided in the 

United States call for significant improvements at a system level to guarantee effective, efficient, 

evidence-based, patient-oriented, and equitable care.74,84,85 Patient safety from injuries caused by 

the health care system is critical to improving quality of care and reducing health care costs.84

Estimates suggest that 1 percent of health expenditures, or $8.8 billion, is attributable to 

preventable adverse events.84 Patient safety is included in certification process of health care 

organizations by the Joint Commission on Accreditation of Healthcare Organizations (JCAHO)4

and monitored by the voluntary National Quality Forum (NQF).5,87 The health care workforce is 

crucial to providing patients with high-quality care.74 Nurses constitute 54 percent of all health 

care workers in the United States.74 Because of the key role nurses play in patient safety and 

quality of care, the U.S. Department of Health and Human Services (DHHS) and the Agency for 

Healthcare Research and Quality (AHRQ) conducted several studies51,65,89,90 to examine the 

association between nurse staffing and patient outcomes which showed that the work 

environment was a major threat to safe nursing practice in hospitals.27 Hospital restructuring in 

the last two decades, in response to the advent of managed care, resulted in shorter 

hospitalizations of acutely ill patients to increase hospitals’ efficiency and financial 

performance.19 Increased patient turnover placed new stresses on nurses to provide safe patient 

care.3,74 The increased workload, when 23 percent of hospitals reported 7-12 patients per nurse in 

most medical-surgical units, reduced nurses’ trust in hospital and nursing administration as well 

as reducing nurse autonomy.74 At least part of the growing nurse shortage from 6 percent in 2000 

to a projected 20 percent in 2020 can be traced to nurse job dissatisfaction.1,91

 A nurse shortage, in combination with increased workload, has the potential to threaten 

quality of care.74,51 Hospitals with inadequate nurse staffing have higher rates of adverse events 

such as hospital acquired infection, shock, and failure to rescue.26,27,51 Systematic reviews of the 

published literature show that better nurse staffing is associated with less hospital mortality and 

failure to rescue, and shorter lengths of stay.51,92,93 A simulation model based on extensive 

research on nurse staffing estimates the need for additional nurses to achieve the quality goals set 

for hospital care.6,26,27

 The design of nurse staffing studies varies. Some look specifically at individual units or 

nurses, while others use administrative data bases that address data at the hospital level and do 

not permit statistical adjustment for many potentially relevant factors. The latter designs allow 

for only crude associations. 

 Quality indicators directly related to nurse staffing have been developed.89,95 AHRQ, the 

American Nurses Association (ANA), and the NQF considered failure to rescue and pressure 

ulcers as patient outcomes that are sensitive to nursing care, but there is less consensus on other 

quality measures such as hospital acquired pneumonia (AHRQ, NQF), urinary tract infection 

(NQF, ANA), patient falls (NQF, ANA), patient satisfaction with nursing care (ANA), ventilator 

associated pneumonia, and catheter associated bloodstream infections (NQF).5,89,95

 Few studies have evaluated optimal nurse staffing ratios and hours in different clinical 

settings; instead, they reported the overall correlation with selected patient outcomes.35,92,94,96-99

The effect size varied widely using different definitions of RN to patient ratio. An additional 
10 

patient per RN per shift was associated with increased relative risk of mortality by 6-7 percent in 

surgical patients.15,16 An increased patient/RN ratio in the evening was associated with a 90 

percent increase in relative risk of death in ICUs.9 An increase from 1.06 to 2.66 RN FTE per 

patient day was associated with a relative reduction in hospital-related mortality by 9 percent.17

Failure to rescue was reduced by 4-6 percent in surgical patients26 when the proportion of RNs 

increased by 13 percent.27 Each additional patient per RN was associated with a 5 percent 

increase in failure to rescue.16 Few studies examined the effect on patient outcomes of nurse 

staffing strategies, such as overtime hours100 and contract or agency nurses.28,30,64,101

 Increasing the nurse-to-patient ratios and hours has been recommended as a means to 

improve patient safety.74 Mandatory nurse-to-patient ratios and staffing plans have been 

established in several states102 and proposed for all Medicare participating hospitals.103 However, 

most legislative efforts related to mandatory staffing regulations cannot be supported by research 

that has yielded evidence-based optimal nurse-to-patient ratios or hours.104 Moreover, the cost 

effectiveness of increasing the number of RN hours or RN patient ratios is controversial.105-107 A 

national estimation of the cost of increasing RN staffing and the concomitant benefits from 

avoided deaths, reduced length of stay, and patient adverse events (urinary tract infections, 

hospital acquired pneumonia, shock, upper gastrointestinal bleeding, and failure to rescue) 

concluded that increased RN hours per patient day without increased total nursing hours could 

yield a net reduction in cost of care.6

 Comparing the results of different studies is complicated by 

the way both staffing and outcomes are measured. 

 The aim of this systematic review is to analyze associations between hospital nurse staffing 

and patient outcomes with consideration of variables that could influence the primary 

association. The idea for this systematic review was supported by the American Organization of 

Nurse Executives (AONE). AONE had representation on the Technical Expert Panel. A series of 

research questions was developed by AONE in conjunction with AHRQ staff as follows: 

1. How is a specific nurse-to-patient ratio associated with patient outcomes? 

a. Patient outcomes: mortality; adverse drug events, nurse quality outcomes, length of 

stay; patient satisfaction with nurse care 

b. How does this association vary by: 

i. patient characteristics such as acuity/severity of illness, stage of treatment 

process; functional capacity 

ii. nurse characteristics such as nurse level of education, nursing years in practice, 

contract nurses, foreign-trained nurses 

iii. organizational characteristics such as type of clinical unit, duration of shift, shift 

rotation 

iv. nursing outcomes such as nurse satisfaction, nurse vacancy rate, nurse turnover 

rate, nurse retention rate 

2. How is a measure of nurse work hours (hours per patient or patient day) associated with 

patient outcomes? 

a. Patient outcomes: mortality; adverse drug events, nurse quality outcomes, length of 

stay; patient satisfaction with nurse care 

b. How does this association vary by: 

i. patient characteristics such as acuity/severity of illness, stage of treatment 

process; functional capacity 

ii. nurse characteristics such as nurse level of education, nursing years in practice, 

contract nurses, foreign-trained nurses 
11 

iii. organizational characteristics such as type of clinical unit, duration of shift; shift 

rotation 

iv. nursing outcomes such as nurse satisfaction, nurse vacancy rate, nurse turnover 

rate, nurse retention rate 

3. What factors influence nurse staffing policies (staffing ratios, hours per patient day, skill 

mix, shift rotations, shift durations, overtime (mandatory and voluntary), weekend 

staffing, temporary nurses, full-time/part-time mix, floating to nursing units, foreign 

graduate nurses)? 

4. What nurse staffing strategies (use of temporary nursing agencies, part-time nurses, 

proportion of RNs, experience mix of nursing staff, continuing nurse education, use of 

ancillary personnel) are effective for improving the patient outcomes listed in question 1? 

5. What gaps in the body of research of nurse staffing and patient outcomes can be 

identified to address in future studies? 

 Questions 1, 2, and 4 are addressed in the systematic review using meta-analytic approaches. 

The literature associated with question 3 does not lend itself to meta-analysis. Rather, the third 

question is approached by a review of the literature. The fifth question is addressed from the 

results of the overall review and analysis of the studies on nurse staffing and quality. 

 Questions about nurse ratios and hours are basically similar and examine the same 

conceptual association between nurse staffing and patient outcomes but employ two different 

measures of nurse staffing.108 The nurse to patient ratio relies on a general ratio, which may 

include all nurses assigned to a unit, including nonclinical time, whereas nurse work hours look 

specifically at nurses involved in patient care. Ideally, worked hours should not include other 

time (e.g., vacation, sick leave, conferences) that is included in the ratio. It is important to 

distinguish wherever possible paid hours from those actually worked. 

 Even within this distinction, a number of important differences exist in the way staffing 

ratios are calculated. Various authors used different operational definitions for the nurse to 

patient ratio, including: 

• Number of patients cared for by one nurse per shift. 

• FTE per 1,000 patient days. 

• Nurse per patient day or FTE per occupied bed. 

 These differences provide challenges to pool data across studies. 

 Hours per patient day (HPD) cannot readily be used to accurately determine nurse-to-patient 

ratios. HPD reflect average staffing across a 24-hour period and do not reflect fluctuations in 

census, scheduling patterns, or absenteeism. Not all productive nursing hours are spent at the 

bedside. Nurses may be engaged in activities such as education, administration, and quality 

assurance. Thus, HPD are likely to overestimate the actual amount of bedside care, and the 

magnitude of the discrepancy may vary from hospital to hospital.60,109

 Other challenges are associated with the type of nursing staff included in the nursing hours or 

nurse ratios. Some studies include only RNs and other studies include both RNs and 

LPNs/LVNs. 

 Outcomes research attempts to isolate the relationship between any type of treatment and 

outcomes by adjusting for the effects of other salient variables, such as the nature of the disease 

and patient characteristics. In the case of nurse staffing, the situation is somewhat different. 

Nurse staffing is only one component of treatment. The ideal study design would simultaneously 

adjust for the effects of other treatment elements, such as the specific medications and 

procedures given and the skills of the medical staff. Instead, most nursing studies emphasize the 
12 

effect of nursing resources, assuming that all other variables are constant and use average 

comorbidity scores across hospitals instead of more patient-specific measures. Indeed, individual 

level patient characteristics are not usually directly addressed, at least not in any detail. Some 

studies may be conducted on specific units that treat certain types of patients, but the disease mix 

and severity are generally not addressed specifically.86 Whereas a typical medical outcomes 

study would include variables on patients’ disease severity and comorbidities, these can best be 

addressed in the nurse staffing analyses conducted at patient levels, but most studies were 

conducted at the unit and hospital level where average values may result from various mixes of 

patient types.110,111

 Given this reality, the conceptual model for the relationship between nurse staffing and 

outcomes (questions 1 and 2) (shown in Figure 1) focuses on those aspects of care that are 

generally addressed in such studies.112-115 Two types of outcomes are proposed to be related to 

nurse staffing: nurse outcomes and patient outcomes. While patient outcomes are the ultimate 

concern, nurse outcomes can interact with nurse staffing to affect patient outcomes. Nurse 

characteristics can influence nurse staffing. The model includes patient factors and hospital 

organizational factors that may influence the effect of nurse staffing on patient outcomes. Patient 

outcomes will, in turn, affect LOS; greater complication rates will increase LOS. Table 1 

provides definitions for the variables included in Figure 1. 

 The conceptual model for question 3 (Figure 2) focuses on nurse staffing policies and 

illustrates factors that might affect such policies, including patient care unit factors. The 

composition of the nursing staff, such as the extent of experience or extent of contract nursing 

staff, may also play a role in determining nurse staffing policies and vice versa. Hospital factors 

will influence nurse staffing policies; however, it is proposed that nursing organizational factors 

are an intervening factor. The definitions for the variables are provided in Table 1. 

 The conceptual model for question 4 (Figure 3) emphasizes the relationship between nurse 

staffing strategies and patient outcomes. Although these strategies may be influenced by nurse 

staffing models, this variable is not overtly considered in this analysis, and hence is shown in a 

dotted box. Hospital factors and patient factors can directly affect patient outcomes, as can 

medical care and nurse staffing levels (not shown in the model). 
13 

Figure 1. Conceptual framework of nurse staffing and patient outcomes 

Nurse Staffing

• Hours/patient day: 

 Delivered care hours 

 Total paid hours 

• Skill mix 

• Nurse staffing ratio 

Patient Outcomes

• Mortality 

• Adverse drug events 

• Patient satisfaction 

• Nurse quality outcomes 

Length of stay 

Hospital Factors

• Size 

• Volume 

• Teaching 

• Technology 

Patient Factors

• Age 

• Primary diagnosis 

• Acuity and severity 

• Comorbidity 

• Treatment stage 

Organization Factors

• Clinical units 

• Duration of shift 

• Shift rotation 

Nurse Outcomes

• Satisfaction 

• Retention rate 

• Burnout rate 

Medical care 

Nurse Characteristics

• Education 

• Experience 

• Age 

• Contract nurses 

• Internationally educated 

nurses 
14 

Table 1. Operational definitions 

Questions 1 and 2: How is a specific nurse to patient ratio or a measure of nurse work hours associated with patient 

outcomes and how does this association vary by patient, nurse, and organizational characteristics? 

Variable Definition 

Nurse Workforce116

Registered Nurse (RN) An individual who holds a current license to practice within the scope of 

professional nursing in at least one jurisdiction of the United States.

Licensed Practical/Vocational 

Nurse (LPN/LVN)

An individual who holds a current license to practice as a practical or vocational 

nurse in at least one jurisdiction of the United States.

UAP Assistive Nursing 

Personnel

Unlicensed individuals who assist nursing staff in the provision of basic care to 

clients and who work under the supervision of licensed nursing personnel. 

Included in, but not limited to, this category are nurses aides, nursing 

assistants, orderlies, attendants, personal care aides, medication technicians, 

and home health aides.

Nursing personnel This term refers to the full range of nursing personnel including RNs, 

LPNs/LVNs and UAPs. 

Nurse Staffing Measures 

Patient to nurse ratios Number of patients cared for by one nurse, specified by job category 

RN to patient ratio Number of patients cared for by one RN 

LPN to patient ratio Number of patients cared for by one LPN 

UAP to patient ratio Number of patients cared for by one UAP 

Nurse hours per patient day Total number of productive hours worked by all nursing staff with direct care 

responsibilities per patient day (a patient day is the number of days any one 

patient stays in the hospital) 

RN hours per patient day Number of productive hours worked by RN with direct care responsibilities per 

patient day (a patient day is the number of days any one patient stays in the 

hospital) 

LPN/LVN hours per patient day Number of productive hours worked by LPN/LVN with direct care 

responsibilities per patient day (a patient day is the number of days any one 

patient stays in the hospital) 

UAP hours per patient day Number of productive hours worked by UAP with direct care responsibilities per 

patient day (a patient day is the number of days any one patient stays in the 

hospital) 

RN/LPN/UAP FTEs per patient 

day 

Number of RN/LPN/UAP FTEs per patient day (FTEs can be composed of 

multiple part-time or one full-time individual) This ratio has been calculated in 

several different ways: number of patients cared for by one nurse per shift; 

FTE/1,000 patient-days; nurse/patient day or FTE/occupied bed. For analytic 

purposes we operationalized the nurse to patient ratio as the number of patients 

cared by one nurse per shift and FTE/patient day (see Appendix F for 

calculations) 

FTE A full-time employee, or a combination of part-time employees whose combined 

hours are the equivalent of a full-time position, as defined by the employer 

Skill mix Proportion of productive (i.e., direct patient care related) hours worked by each 

skill mix category (RN, LP/VN, UAP) 

Licensed nurse RN and LP/VN 

Patient Outcomes

Mortality 

Mortality Death from all causes (intra hospital, 30 days after discharge) 

Death in low mortality Diagnosis 

Related Groups (DRGs) 

In-hospital deaths in DRGs with less than 0.5% mortality 

Adverse Drug Event 

Adverse Drug Events An injury related to drugs caused by medical management rather than by the 

underlying disease or condition of the patient 

Length of Stay 

Length of stay Average length of stay: the number of patient days divided by the number of 

discharges for a time period 

Patient Satisfaction 

Patient satisfaction with nursing 

care 

Measure of patient perception of the hospital experience related to satisfaction 

with nursing care 
Table 1. Operational definitions (continued) 

15 

Variable Definition 

Patient satisfaction with pain 

management 

Patient opinion of how well nursing staff managed their pain as determined by 

scaled responses to a uniform series of questions designed to elicit patient 

views regarding specific aspects of pain management 

Patient satisfaction with 

educational information 

Patient opinion of nursing staff efforts to educate them regarding their 

conditions and care requirements as determined by scaled responses to a 

uniform series of questions designed to elicit patient views regarding specific 

aspects of patient education activities 

Patient satisfaction with overall 

care 

Patient opinion of care received during the hospital stay as determined by 

scaled responses to a uniform series of questions designed to elicit patient 

views regarding global aspects of care 

Nurse Quality Outcomes 

Patient falls, injuries Unplanned descent to the floor during the course of a hospital stay 

Maintenance of skin 

integrity/pressure ulcers 

Stage I-IV ulcers 

Nosocomial infection rate An infection occurring in a patient in a hospital or other healthcare facility in 

whom it was not present or incubating at the time of admission 

Failure to rescue The number of deaths in patients who developed an adverse occurrence; the 

number of patients who developed an adverse occurrence 117 

Urinary tract infection rate Disorder involving repeated or prolonged bacterial infection of the bladder or 

lower urinary tract (urethra) 

Surgical bleeding Post-surgical hematoma or hemorrhage 

Upper gastrointestinal bleeding Gastrointestinal hemorrhage 

Post surgical thrombosis Deep vein thrombosis or pulmonary embolism among surgical patients 

Atelectasis and pulmonary 

failure 

Iatrogenic atelectasis and acute respiratory failure in hospitalized patients 

Accidental extubation Iatrogenic accidental extubation 

Hospital-acquired pneumonia An infection of the lungs contracted during a hospital stay 

Postoperative infection Any infection of post-surgical wounds 

Cardiac arrest/shock Cessation of cardiac mechanical activity as confirmed by the absence of signs 

of circulation 

*Restraint prevalence (vest and 

limb only) 

Restricting free movement of another person 

Urinary catheter associated 

infections 

Iatrogenic infection of urinary tract associated with a catheterization 

Nurse Outcomes

Staff vacancy rate Open positions divided by total positions 

Nurse satisfaction Opinion of nurses about their job in terms of pay, reward, administration style, 

professional status, and interaction with colleagues 

Staff turnover rate Departures from the staff (or hires) divided by total positions 

Retention rate Proportion of nurses employed at the beginning of the year who are still 

employed there at the end in each participating unit 

Burnout rate Proportion of nurses who reported an excessive stress reaction to professional 

environment manifested by feelings of emotional and physical exhaustion 

coupled with a sense of frustration and failure 

Patient Characteristics

Age Mean age in years 

Primary diagnosis Diagnosis which was a cause for hospitalization (ICD-9 codes) 

Comorbidity Coexistence of two or more disease-processes measured with weighted scales. 

This data can be collected on the individual patient level or an average figure 

can be calculated for an entire hospital. 

Severity Severity of illness classified as none or minor, moderate, or major, based on 

expected impact on length of stay. For surgical patients, a fourth class is added 

for patients having catastrophic comorbidities or complications; including 

chronically, critically, or terminally ill. 

Stage of treatment This applies largely to surgical patients and would be pre-op/post-op; could 

apply to persons undergoing some other defined intervention; could also be 

used to distinguish rehabilitative phase from acute treatment. 

Functional capacity Individual’s maximum capacity to perform daily activities in the physical, 

psychological, social, and spiritual domains of life 
Table 1. Operational definitions (continued) 

16 

Variable Definition 

Nurse Characteristics

Demographics Age and gender 

Level of education Proportion of nurses with nursing degree: Associate degree; Diploma; BSN; 

Master of Science (MS); Doctor of Philosophy (PhD) 

Nursing experience Experience in nursing practice in years 

UAP Unlicensed assistive personnel (not RNs or LPNs) 

International Educated Nurse 

(IEN) 

Nurses who graduated from schools of nursing in foreign countries 

Contract/temporary/agency 

nurses 

Any licensed nurse who is providing service at the facility as an employee of 

another entity 

Organizational Characteristics

Type of clinical units Types of patients and services provided on a nursing unit (e.g., telemetry, 

medical, surgical, critical care) 

Duration of shift Length of working shift (8, 10, or 12 hour shift) 

Nursing unions Organizations that represent nurses for the purposes of collective bargaining 

Hospital Factors 

Teaching status Affiliation with a medical school 

Size Number of beds 

Volume Annual number of procedures performed in a hospital 

Technology index Weighted sum of the number of technologies for direct patient care and 

services available in a hospital. Availability and saturation in use of 

computerized physician orders entry systems, computerized nursing, and 

patient medical records 

* Nurse process measures 

Question 3: What factors influence nurse staffing policies? 

Variable Definition 

Nurse Staffing Policies 

Staffing ratios Policies regarding the number of patients cared for by one nurse specified by 

job category (RN, LPN/LVN, UAP) 

Staffing hours per patient day Policies regarding the total number of productive hours worked by nursing staff 

with direct care responsibilities on acute care units per patient day (total nursing 

hours, RN hours, LPN/LVN hours, UAP hours) 

Staff mix Policies regarding the proportion of productive hours worked by each skill mix 

category (RN, LPN/LVN, UAP) 

Shift rotations Policies regarding scheduling nursing staff to work different work shifts (days, 

evenings, nights) during a defined period of time (e.g., pay period; schedule 

period) 

Shift durations Policies regarding the length of shifts (e.g., 8 hours; 10 hours; 12 hours) 

Overtime (mandatory and 

voluntary) 

Policies requiring or permitting additional worked hours over 40 hours/week or 

more than 8 hours in a day or more than 80 hours in a pay period 

Weekend staffing Policies regarding the frequency of weekends worked 

Temporary nurses Policies regarding the use of temporary/agency nurses 

Full-time/part-time mix Policies regarding the number and type of nursing staff that are full time and 

part time 

Floating to nursing units Policies regarding when nurses can be assigned to work on nursing units other 

than their regularly assigned nursing unit 

International Educated Nurses 

(IEN) 

Policies regarding the hiring and use of nurses that have graduated from 

schools of nursing in foreign countries 

Patient Care Unit Factors 

Patient classification system Systems that classify patients according to the intensity of nursing care required 

Patient flow/census fluctuations Frequency of admissions, discharges, transfers of patients in a nursing unit or a 

hospital 
Table 1. Operational definitions (continued) 

17 

Type of nursing unit Types of patients and services provided in a nursing unit (e.g., telemetry, 

medical, surgical, pediatric, critical care) 

Nursing Organization Factors 

Governance Organizational models through which nurses control their practice as well as 

influence administrative areas 

Management/leadership style Degree to which nurses in management and leadership positions make 

themselves visible and accessible to nursing staff, seek, value, and incorporate 

feedback from nursing staff, and communicate with nursing staff 

Hospital Factors 

Type Teaching, non teaching, rural, urban 

Ownership Proprietary, government/public, and not-for-profit 

Technology use Electronic medical record 

Risk management Degree to which the organization addresses the prevention of adverse events 

Unionization Percent or proportion of nurses who are members of a collective bargaining unit 

Nurse Factors 

Experience in nursing Years working as a licensed nurse or UAP 

Age Age in years 

Education Proportion of nurses by highest level of education in nursing: practical nursing, 

associate degree, diploma, baccalaureate, masters, doctorate 

Question 4: What nurse staffing strategies are effective for improving outcomes? 

Variable Definition 

Nurse Staffing Models 

Patient focused care RNs serve as care managers managing unlicensed assistive personnel in 

expanded roles (drawing blood, performing EKGs, and performing certain 

assessment activities) 

Primary nursing RN accountable for care of patient from admission to discharge; coordinates all 

care; provides direct care for patient 

Total patient care RN assumes total responsibility for care of the patient during the time the nurse 

is on duty 

Team nursing RN is a team leader and LPNs and UAPs provide patient care as directed by 

the RN team leader 

Functional nursing Nursing staff are assigned specific tasks (e.g., treatments, medications, patient 

hygiene care) according to their skill and education 

Staffing Strategies 

Use of temporary nursing 

agencies 

Use of nursing personnel that are employed by an organization that supplies 

nursing staff 

Use of part-time nurses Proportion of nurses (RN and LPN) working part time (less than 8 hours per 

shift or less than 40 hours per week) 

Proportion of RNs Proportion of RNs among total hospital and total nursing personnel 

Experience mix of nursing staff Proportion of nursing staff (by type) according to their years of experience 

Continuing nurse education Professional development process after the completion of the pre-registration 

nurse education program. It consists of planned learning experiences which are 

designed to augment the knowledge, skills, and attitudes of registered nurses to 

improve quality of care and patient outcomes. 

Use of ancillary personnel Aides, clerical staff, phlebotomists 

Patient outcome measures used for questions 1 and 2 will be used for question 4 as well. 
18 

Figure 2. Factors affecting nurse staffing policies 

Hospital Related

• Type 

• Ownership 

• Mission 

• Technology level 

• Risk management 

• Unionization 

Nurse Factors

• Experience 

• Age 

• Education 

• Contract nurses 

Patient Care Unit Factors 

• Patient factors 

− Age 

− Primary diagnosis 

− Acuity and severity 

− Comorbidity 

− Treatment stage 

• Patient flow/census fluctuations 

• Unit function 

Nurse Staffing Policies

• Staffing ratio/mix/hours 

• Shift 

• Shift rotation 

• Shift duration 

• Overtime 

• Weekend staffing 

• Temporary nurses 

• Full time/part time mix 

• Internationally educated nurses 

• Floating to other units 

Nursing Organization Factors

• Governance 

• Management/leadership 
19 

Figure 3. Nurse staffing strategies and patient outcomes 

Nurse Staffing Models

• Patient focused care 

• Primary nursing 

• Total nursing care 

• Team nursing 

• Functional nursing 

Patient Outcomes

• Mortality 

• Adverse events 

• Satisfaction 

• Nurse quality outcomes 

Nurse Staffing Strategies

• Use of temporary nursing 

agencies 

• Use of part-time nurses 

• Proportion of RNs 

• Experience mix of the nursing 

staff 

• Continuing nurse education 

• Use of ancillary personnel 

Patient Factors

• Age 

• Primary diagnosis 

• Severity 

• Comorbidity 

• Treatment stage 

Hospital Factors

• Size 

• Volume 

• Teaching 

• Technology 

21 

Chapter 2. Methods 

Literature Search Strategy and Eligibility Criteria 

Search Strategy 

 Studies were sought from a wide variety of sources, including MEDLINE®, PubMed®, 

CINAHL, Cochrane databases, EBSCO research database, BioMed Central, federal reports, 

National Database of Nursing Quality Indicators, National Center for Health Workforce 

Analysis, American Nurses Association, American Academy of Nurse Practitioners, and Digital 

Dissertations. The search strategies for the four research questions are described in Appendix A∗. 

The same eligibility criteria, selection of studies, and analysis of studies were used to examine 

the association between nurse staffing and strategies and patient outcomes. The approach was 

different to identify studies that examined factors that influence nurse staffing policies. As noted 

earlier, the question about policies was not appropriate for meta-analysis. Excluded references 

are shown in Appendix B. All work was conducted under the guidance of a Technical Expert 

Panel (TEP). Members are identified in Appendix C. The data abstraction forms are shown in 

Appendix D. 

Eligibility 

 Two investigators independently decided on the eligibility of the studies.118 We reviewed 

abstracts to exclude studies with ineligible target populations conducted in countries other than 

the United States and Canada and in long-term nursing facilities. Then we confirmed the 

eligibility status of the study designs, excluding secondary data analysis, reviews, letters, 

comments, legal cases, and editorials. The full texts of the original epidemiologic studies were 

examined to define eligible independent variables (nurse staffing and strategies) and eligible 

outcomes. Then we excluded studies that did not test the associative hypotheses and did not 

provide adequate information on tested hypotheses (e.g., least square means, relative risk). 

 Inclusion criteria were applied to select articles for full review. Studies needed to meet one of 

the following criteria for questions 1, 2, and 4: 

• Retrospective observational cohort studies and retrospective cross sectional comparisons 

• Administrative cross-sectional survey and analyses; 

• Randomized controlled trials with random allocation of subjects to intervention and control 

groups 

• Controlled not randomized clinical trials2

• The studies must evaluate the associations between nurse staffing and patient 

outcomes/nurse quality measures among eligible target populations (patients hospitalized in 

acute care hospitals in the United States and Canada) and published after 1990 except 

conducted in 1982-1989 but frequently cited in recent publications 

• Ecologic studies on correlations between nurse staffing and patients outcomes 

• Cost-effectiveness analysis of nurse staffing 

 

1 The literature in this area contained no randomized controlled trials or even non-randomized trials. ∗ Appendixes and Evidence Tables for this report are provided electronically at http://www.ahrq.gov/clinic/tp/nursesttp.htm
22 

 Studies were selected for question 3 if the study provided implications for nurse staffing 

policies. No studies had as a primary purpose to empirically examine a specific nurse staffing 

policy. 

 The exclusion criteria included the following: 

• Studies published before 1990 

• Studies conducted in countries other than United States and Canada and not published in 

the English language 

• Studies with target population as outpatients and patients in long-term care facilities 

• Studies with no information relevant to nurse staffing policies and strategies 

• Studies that examined the contributions of advance practice nurses (nurse practitioners, 

nurse clinicians, certified nurse midwives, nurse anesthetists) 

• Studies that evaluated the association between nurse staffing and ineligible outcomes 

(questions 1, 2, and 4) 

• Administrative reports and single hospital studies with no control comparisons that do not 

test an associative hypothesis (questions 1, 2, and 4) 

 The assessment of the studies’ quality was based on “Systems to Rate the Strength of 

Scientific Evidence.”119 For questions 1, 2, and 4 we grouped all criteria into ten dimensions 

with scores for each aspect assigned a value from 0 to 5 (highest) for a total possible score of 50 

for the statistical analysis of the studies’ quality (Appendix E). 

 Given the absence of RCTs, the level of evidence for all studies was estimated using a subset 

of the U.S. Preventive Services Task Force120 criteria noted below: 

II-2A: Well-designed cohort (prospective) study with concurrent controls 

II-2B: Well-designed cohort (prospective) study with historical controls 

II-2C: Well-designed cohort (retrospective) study with concurrent controls 

II-3: Well-designed case controlled (retrospective) study 

III: Large differences from comparisons between times and/or places with or without 

interventions (cross-sectional comparisons). 

 For question 3, an evidence table was developed for each of the nurse staffing variables 

identifying the purpose of the study, sample, design, independent and dependent variables, and 

findings. 

 For questions 1, 2, and 4, descriptive statistics, correlation and regression coefficients, and F 

and T tests for treatment differences were used to assess reported outliers, variances, and 

skewness in the data.121,122 Baseline data were compared in different studies to test the 

differences in the target population and unusual patterns in the data.123,124 Standard errors, 

regression coefficients, and 95 percent CI were calculated from reported means, standard 

deviations, and sample size.121,122 The protocol for the meta-analyses was created according to 

the recommendations for Meta-analysis Of Observational Studies in Epidemiology (MOOSE).125 

 We used the Trim and Fill method126 to detect publication bias defined as the tendency to 

publish positive results and to predict the association when all conducted (published and 

unpublished) studies are analyzed. Time trends in positive results were assessed with interaction 

models with time of the events as continuous variables. 

 The evaluations of the studies and the data extraction were performed manually and 

independently by two researchers. The principal investigators of some studies were contacted to 

assess the additional and missing information when necessary. Errors in the data extractions were 

assessed by a comparison with the established ranges for each variable and by a comparison of 

the data charts with the original articles. Any discrepancies were detected and discussed. 
23 

 Patient populations were classified as surgical, medical, and combined samples.26,27

Adjustments for patient age, race, gender, comorbidities, socioeconomic status, provider 

characteristics, and clustering of patients and providers were extracted from the studies.127

Data Synthesis 

 For questions 1, 2, and 4, the results of individual studies were summarized in an evidence 

table with relation to the sample size and 95 percent CI in outcomes. Weighted by the number of 

patients and hospitals, odds ratios and 95 percent CIs were calculated with fixed and random 

effects models.128 

 We report the nurse to patient ratios as they were used by individual authors; but we have 

also created two standardized rates for purposes of comparison: 

 1. The number of patients cared by one nurse per shift3

 2. RN FTE per patient day 

 FTE per occupied bed ratios were calculated based on FTE per mean annual number of 

occupied bed days (patient days). Therefore, we conducted separated analyses and report the 

results: 

• With definitions the authors used 

• Corresponding to an increase by one RN FTE per patient day 

• In categories of patients per RN per shift in ICUs, and with surgical and medical patients.27

Different methods have been used to estimate nurse hours per patient day from FTEs. Some 

investigators assume a 40 hour week and 52 working weeks per year (2,080 hours per year). 

Others use more conservative estimates (e.g., 37.5 hours per week for 48 weeks = 1,800 hours 

per year).129 In our conversions, we used the latter estimate (Appendix F). 

We estimated that: 

• Nurse hours per patient day = (FTE * 40)/patient days130

• One nurse per patient day = 8 working hours per patient day129

• Then the patient per nurse ratio = 24 hours/nurse hours per patient day130

We made the following assumptions: 

• 37.5 hour work week on average 

• 48 working weeks per year (4 weeks vacation, holidays, sick time); 

• All FTEs are full-time nurses with the same shift distribution (assume three 8-hour shifts) 

• The length of shift does not modify the association between nurse staffing and patient 

outcomes 

• Patient density is the same over the year 

The same estimation was used for each nurse job category—RN, LPN/LVN, and UAP. 

 Meta-analysis was used to assess the consistency of the association between nurse staffing 

and patient outcomes and improvement in economic outcomes including LOS. The analyses 

were conducted separately for classes of patient and hospital characteristics. Assumptions 

underlying meta-analysis included valid measurements of nurse staffing and patient outcomes, 

similarity in target populations, and similarity in reported and not reported variance. 

 Sub-analyses were conducted to test whether the direction and strength of the association was 

independent of study design and financial support.127 Consistency in the results was tested 

comparing the direction and strength of the association in models with nurse staffing variables as 

continuous (overall trend) and categorical, in studies reporting outcome rates and adjusted 

 

3

 We assume an 8-hour shift. 
24 

relative risk, and with goodness of fit tests. Chi squared tests were used to assess heterogeneity in 

study results.131,132 Significant heterogeneity means the effects of nurse staffing on patient 

outcomes were not consistent in the studies (not replicable results). The hypotheses of the 

associations between outcomes and nurse staffing variables were tested with random effects 

models (random intercept for each study) to incorporate between variability in the studies and to 

provide valid pooled estimates weighted by sample size. Individual studies were analyzed with 

simple linear regression to find slopes for each study when possible. Meta-analysis was used to 

estimate pooled regression coefficients: changes in outcomes corresponding to incremental 

changes by one unit in nurse staffing. The analytic framework and algorithms for the metaanalysis are shown in Appendix F. 

 Meta-regression models analyzed possible interactions with the year of publication, analytic 

units, hospital units, adjustment for confounding factors, and patient population.132,133 The 

calculations were performed using the following software: STATA,134,135 and SAS 9.2 Proc 

Mixed.136 To ascertain whether the relationships were linear, two different forms of staffing 

variables were tested: continuous and categorical, where the latter was arranged in quartiles. 

When authors reported outcome rates and relative risks grouped by different exposure cut points 

and reference, we assigned exposure levels as the mean or median of nurse staffing variables, 

assuming a normal distribution. We also transformed nurse staffing levels into a risk estimate per 

unit of exposure and assigned an exposure value to each categorical group, assuming a specific 

parametric distribution for the exposure in the population.137 This method can test a linear doseresponse relation and assess the nonlinearity of the dose-response relation.

 The research question examining factors that influence nurse staffing policies (question 3) 

involved the identification of studies that included one or more of the nurse staffing variables. 

The studies were summarized in evidence tables followed by a synthesis of the studies for each 

staffing policy. 
25 

Chapter 3. Results 

 

 Figure 4 traces the flow of our literature search for questions 1, 2, and 4. Of the 2,858 

potentially relevant references from eight databases identified, we excluded 97 percent of the 

studies; 2 percent were case reports; 20 percent – comments and success stories; 2 percent – legal 

cases; 2 percent – editorials and expert opinions; 5 percent – letters, guidelines, interview, and 

news that reprinted the results of the original reports; and 4 percent – reviews and secondary data 

analyses, and one web survey. We excluded 21 percent of the studies that lacked relevant 

components; 6 percent without eligible outcomes, 30 percent without eligible target populations, 

and 21 percent that did not test associative hypotheses between nurse staffing and patient 

outcomes. Among 101 potentially relevant randomized controlled clinical trials, none was 

eligible; 56 tested ineligible interventions; five reported ineligible outcomes; 38 were conducted 

in European countries or included nurses in long-term nursing facilities. 

 We identified 94 eligible studies presented in 96 reports; 7 percent were case control studies; 

3 percent were case series; 44 percent were cross sectional studies; 46 percent assessed 

temporality in the association between nurse staffing and patient outcomes. 

 The overall quality of the studies averaged 38 (where the maximum possible score was 50) 

(Table 2). Three studies received <50 percent of the maximum quality score; 24 studies had <66 

percent, and 21 studies had >88 percent of the maximum quality score. Within this score, the 

mean external validity was 3.5 ± 1 (70 percent of the maximum score) with 67 percent for the 

sampling of the study populations; random sampling was reported in 16 studies (17 percent), and 

sampling bias was assessed in 15 studies (16 percent). More than 9 percent of the sampled 

analytic units were excluded from 27 studies. Single hospital studies constituted 25 percent of all 

eligible studies (23 reports). Geographical locations of eligible hospitals were reported in 49 

studies (52 percent). The investigators generally obtained national and state administrative 

databases to identify eligible populations. 

 The mean score for adjustment for assessed confounding factors as a characteristic of 

internal validity was 2.9 ± 1.6 (only 58 percent of the possible maximum score); 17 studies did 

not provide information on adjustment for confounding factors. Few studies reported the 

validation to measure nurse staffing variables (11 studies, 12 percent) and patient outcomes (22 

studies, 23 percent). Medical records were obtained to measure patient outcomes in 27 studies 

(29 percent); 58 studies (62 percent) used administrative databases. Thirty-two studies used 

hospitals as analytic units (34 percent); 43 studies (46 percent) used patients; and 13 studies (17 

percent) used hospital units. Medicare populations were used in 11 studies (12 percent). 

 The majority of the studies were conducted in the United States (84 studies) with no 

significant differences in quality (80 percent in Canadian studies vs. 76 percent in American, p = 

0.44). The studies supported by national grants had higher quality (80 percent of maximum) 

compared with unknown sponsorship (73 percent, p = 0.02). The quality scores of the studies did 

not change over the decades (p = 0.15). The test for publication bias was not valid due to a small 

number of studies for each association and heterogeneity in the results.
26 

Association Between Nursing Hours and Ratios and Patient 

Outcomes 

Distribution of Nurse Staffing Hours and Ratios 

 Many investigators obtained administrative databases on national, state, and hospital levels. 

Some relied on surveys of nurse managers to measure nurse staffing variables (Appendix G∗, 

Table G1). The means and distribution of nursing hours and ratios are presented in Table 3. Total 

nursing hours per patient day were measured in 36 studies (38 percent), RN hours in 27 studies 

(29 percent), LPN/LVN hours in 12 studies (13 percent), licensed nurse hours in three studies, 

and UAP hours in three studies. Ratios of patients per RN and RN FTE per patient day were 

examined in 36 studies (38 percent), LPN/LVN ratios in eight studies (9 percent), licensed nurse 

ratios in three studies, and UAP ratios in nine studies (10 percent). The distribution of nurse 

staffing variables in eligible published studies was comparable with that published in literature 

with higher LPN/LVN hours per patient days in medical patients.27,138

Question 1. Association Between Nurse to Patient Ratios 

and Hospital-Related Mortality 

We identified 26 studies that examined the association between hospital related mortality and 

nursing hours or ratios (Appendix G, Table G2).8-21,23,26-28,30,32-34,139-141 The authors defined 

hospital related mortality as in-hospital mortality8,9,13,14,18-20,26,27,30,33,34 or death within 30 days 

after hospital admission.10,11,15-17,21,32,140 For analysis purposes we combined in-hospital mortality 

and 30-day mortality. Estimating hospital-related mortality based only on in-hospital deaths may 

be influenced by hospital discharge practices142 and could result in lower in-hospital mortality 

rates that are independent of the quality or effectiveness of hospital care. 

 One study143 compared the relationship of in-hospital and 30-day mortality rates in 13,834 

patients with congestive heart failure who were admitted to 30 hospitals and found a significant 

correlation in standardized mortality ratios sensitive to individual hospital characteristics. The 

association with nurse ratios or hours was presented as changes in crude death rates and adjusted 

relative risk of death corresponding to one unit increase in nurse staffing or in nurse staffing 

categories defined by authors. 

Nurses Ratios and Mortality 

 The pooled results, overall and within ICUs and surgical units, weighted by the sample size 

(number of hospitals and patients) showed a reduction in the crude death rate in association with 

increase RN staffing. An additional RN FTE per patient day was associated with a 1.24 percent 

reduction in death rate.12,17,34 The same tendency was shown corresponding to one additional RN 

per 1,000 patient days.33 In contrast, one additional patient per RN per shift was associated with 

an increase in hospital-related mortality by 0.1 percent13,16,23 (Table 4). 

 

∗ Appendixes and Evidence Tables for this report are provided electronically at http://www.ahrq.gov/clinic/tp/nursesttp.htm. 
27 

 A pooled analysis showed that an increase by one RN FTE per patient day was associated 

with a 1.2 percent reduction in mortality rates in all studies.12,13,16,17,20,23,34 The association was 

consistent in ICUs.13,16,23

 A nonlinear quadratic association between patients per RN per shift and the death rate was 

noted. The rates increased from 1 to 5 patients per RN per shift (p for heterogeneity <0.001). The 

nadir for the relative risk of death was 1.5 RN FTE per patient day (p for heterogeneity 0.002). 

Table 5 shows both the effects of increasing staff with the authors’ definitions of nurse to patient 

ratios by one RN FTE per patient day and the relative effects in quartiles of patients per RN per 

shift distribution in different clinical settings. More RN staffing was consistently associated with 

a reduction in adjusted relative risk of hospital-related mortality. An increase by one RN FTE per 

patient day was associated with a smaller but consistent across the studies’ reduction in mortality 

by 6 percent (RR 0.94, 95 percent CI 0.93-0.95).8,10-12,17,20

 The relative risk of hospital related death was associated with a decrease by 8 percent 

corresponding to an additional one RN FTE per patient day in pooled analysis.8-21 For studies 

analyzed at the hospital level, the associated decrease in relative risk was 4 percent (95 percent 

CI 0.94-0.98).11,12,18-20 For those analyzed at the patient level, it was 8 percent (95 percent CI 

0.89-0.95).9,10,13-17,21 Among medical patients it was 6 percent (95 percent CI 0.94-0.95)8,10,11,17-19

and among surgical patients, 16 percent (95 percent CI 0.8-0.89)9,12-16,20,21 (Figure 5). In contrast, 

an additional patient per RN per shift was associated with an 8 percent increase in mortality risk 

(RR 1.08; 95 percent CI 1.07-1.09).9,13-16,21

 We calculated the relative risk of death in quartiles of patients per RN per shift and found a 

consistently significant reduction in the relative risk of hospital-related mortality corresponding 

to a reduced number of patients assigned to an RN (Table 5 and Figure 6). The effect was larger 

in surgical patients. The pooled relative risk was 0.76 times less when one RN was assigned to 

less than two patients compared with four to six patients, and 0.62 times less compared with 

more than six patients per RN. The reduction was 6 percent in ICUs when one RN was assigned 

to less than three patients vs. three to four patients. 

 If the relationship between staffing and outcomes was causal, we estimate that an increase by 

one RN FTE per patient day would save five lives per 1,000 hospitalized patients, five lives per 

1,000 medical patients, and six per 1,000 surgical patients (Table 6). Reducing the workload 

from more than six to two to four patients per RN per shift would save 23 lives per 1,000 

hospitalized patients. A reduction from three to four to less than three patients per RN per shift in 

ICUs would save three lives per 1,000 hospitalized patients. The decrease from more than six to 

2-3.5 surgical patients per RN per shift would save 13 lives, and a further reduction to less than 

two patients per RN would result in 15 avoided deaths per 1,000 hospitalized surgical patients. 

 Extrapolating these relationships even further to examine the public health impact of RNs per 

patient ratio, we found that an increase of one RN FTE per patient day would reduce hospital 

mortality by 8 percent. The effect varies from 4 percent at a hospital level analysis to 8 percent at 

a patient level analysis. The reduction in a workload from 3 to 4 to less than three patients per 

RN would eliminate 6 percent of deaths in ICUs. The proportion of deaths attributable to patients 

per RN per shift ratio is larger in surgical patients; 38 percent of deaths were linked to poorer 

nurse staffing in hospitals with more than six patients per RN compared to less than two patients 

in surgical units. 

 To compare the results from individual studies, we calculated changes in death rates and 

relative risk of death corresponding to an increase by one unit in nurse staffing (Appendix G 
28 

Table G2 and Table 7). The majority of the studies (57 percent) reported a significant reduction 

in risk of death corresponding to an increase in RN staffing, but the effect size differed in studies 

that used medical records in contrast to administrative databases to measure mortality among 

hospital units and patient populations (Appendix G Tables G3 and G4). We calculated from the 

individual studies10,15,16 that about 6-7 percent of deaths were attributable to an increase in 

patients per RN per shift (Table 8). The observed death rate could be reduced by 9-10 percent 

when increasing by one RN FTE per 1,000 patient days.18,19 A decrease in the nurse to patient 

ratio in the evening was associated with a 90 percent increase in mortality; 47 percent of deaths 

in patients after abdominal aortic surgery was attributable to nurse staffing in these hospitals.9

Ten percent of avoided deaths in patients with acute myocardial infarction was attributable to an 

increase from 1.06 to 2.7 RN FTE per patient day.17 In patients hospitalized with bladder 

carcinoma, 51 percent of deaths was associated with a reduction from 3.1 to 1.4 RNs per 

occupied bed ratio.20

 Three studies that examined the effect of the LPN/LVN per patient day ratio17,34,94 reported 

inconsistent changes in the death rate. A nonlinear association between patients per LPN/LVN 

per shift ratio and relative risk of hospital-related mortality was observed in medical patients 

with the lowest risk corresponding to 9-12 patients per LPN/LVN (p for quadratic association 

0.0003). The death rate was lowest when one UAP was assigned to 7-12 medical patients (p for 

quadratic association 0.0029).One study reported a significant increase in the death rate of 1.9 

percent (95 percent CI 1.5-2.5 percent) for every additional patient per UAP (p = <.0001).94

 We found some evidence that nurse education and experience are associated with hospitalrelated mortality. Using state level administrative reports on nurse distribution in the United 

States1,144 and the CDC data148 on fatal injuries related to health care, we found a significant 

negative correlation between the percentage of nurses with BSN degrees and the incidence of 

deaths related to health care (r = -0.46, p = 0.02) (Table 9).One study in surgical patients16

reported a 5 percent reduction in mortality with each 10 percent increase in nurses with BSN 

degrees (Table 10). Hospitals with a higher proportion of nurses with BSN degrees (36 percent 

vs.11 percent) had 19-34 percent less mortality.101 Nursing experience did not impact hospitalrelated mortality.16,140 Nurse job satisfaction was associated with a significant reduction in the 

risk of death;101 an increase by 17 percent in nurses reporting they were satisfied or very satisfied 

with their job was associated with a 15 percent decrease in mortality. Hospitals where nurses had 

the freedom to make important patient care and work decisions experienced 21 percent lower 

mortality.101 Nurse manager support was negatively correlated with mortality (r = 0.3) in one 

single hospital study in 21 hospital units.145

Association Between Nurse to Patient Ratios and Nurse Sensitive 

Patient Outcomes 

 Authors used different definitions of nurse sensitive patient outcomes, including a 

combination of medical13,14,23 and surgical13,23 complications related to health care, failure to 

rescue,15,16,20,21,35 and secondary diagnoses of patient nosocomial infections, falls, pressure 

ulcers, pulmonary and cardiac failure, and thrombo-embolic complications related to health care 

(Appendix G, Table G5). The associations were presented as differences in the rates or relative 

risk of outcomes by various categories of nurse staffing. 
29 

 Patient outcomes corresponding to an increase in registered nurse per patient ratio.

Pooled analysis of crude rates (Table 11) showed inconsistent results on patient outcomes. An 

increase by one patient per RN per shift was associated with a significant increase in failure to 

rescue by 0.35 percent,16 and pulmonary failure by 6.54 percent.13,14,23 An increase by one RN 

FTE per patient day was association with 0.03 percent decrease in atelectasis and pulmonary 

failure.13,14,23,33,35 The effect was larger in surgical patients in ICUs with a 12 percent reduction in 

pulmonary failure.13,14,23 However, a 0.71 percent reduction in urinary tract infection was 

associated with one additional patient per RN per shift22,146 and a 5 percent increase 

corresponded to one RN FTE per patient day.22,23,146 Studies that defined RN FTE per patient day 

ratio did not show significant changes in outcomes. One unpublished dissertation33 reported an 

increase in falls, nosocomial infections, and pressure ulcers corresponding to an increase of one 

RN FTE per 1,000 patient days (Appendix G, Table G6). 

 In contrast with the analyses of outcomes rates, pooled analysis of adjusted relative risks 

(Table 12) detected a significant, generally consistent reduction in patient outcomes 

corresponding to an increase in RN staffing. An additional patient per RN per shift was 

associated with a 1.07 times higher risk of hospital acquired pneumonia (95 percent CI 1.03-

1.11),13,14,22 a 1.08 times higher risk of failure to rescue (95 percent CI 1.07-1.09),15,16,21 and a 

1.16 times higher risk of cardiac arrest (95 percent CI 1.05-1.29).13,23,24 The risk of pulmonary 

failure was greater by 53 percent and the risk of unplanned extubation by 45 percent 

corresponding to an additional patient per RN per shift.13,14,23-25 We estimated that an increase by 

one RN FTE per patient day in ICUs was associated with a consistent reduction in the relative 

risk of hospital acquired pneumonia by 30 percent,13,14,22 pulmonary failure by 60 

percent,13,14,23,24 unplanned extubation by 51 percent,13,14,23-25 and cardiac arrest by 28 

percent.13,14,24 An increase by one RN FTE per patient day in surgical patients was associated 

with 0.84 times less risk of failure to rescue12,15,16,20,21 and 0.64 times less risk of nosocomial 

bloodstream infections.13,22-24,147

 In individual studies, the largest decrease in the relative risk of central line associated 

bloodstream infection was seen in surgical patients in ICUs corresponding to increased nurse to 

patient ratio.147 Surgical patients also experienced greater increase in the risk of failure to rescue 

(p for interaction 0.04) in a multi-hospital study15 by 7 percent corresponding to every additional 

patient per RN (RR 1.07, 95 percent CI 1.02-1.11). 

 We found nonlinear quadratic associations between the RN FTE per patient day ratio and 

unplanned extubation in ICUs with the nadir at 1.9 RN FTE per patient day (p for quadratic 

association 0.04). In surgical patients, the ranges of RN FTE per patient day at 0.9-2.2 were 

associated with the lowest relative risk of hospital acquired pneumonia (p for quadratic 

association 0.02) and the ranges of 1.5-2 RN FTE per patient day were associated with the lowest 

risk of failure to rescue (p for quadratic association 0.005). 

Patient outcomes corresponding to an increase by one patient per LPN/LVN per shift

(Appendix G, Table G7). The data on LPNs/LVNs is varied and inconclusive. One large study in 

1,477 hospitals94 examined the association between LPN/LVN per patient ratios and patient 

outcomes (Figure 7) and reported that one additional patient per LPN/LVN per shift increased 

the rates of surgical wound infection by 0.02 percent (95 percent CI 0.01-0. 05), pulmonary 

failure by 0.04 percent (95 percent CI 0.02-0.05), pneumonia by 0.06 percent (95 percent CI 

0.04-0.07), patient falls by 0.03 percent (95 percent CI 0.02-0.04), and cardiac arrest by 0.03 

percent (95 percent CI 0.02-0.04). One study18 reported a nonsignificant risk of pneumonia and 
30 

urinary tract infections (UTI) corresponding to an increase by one LPN/LVN FTE per patient 

day. 

 Few studies examined the association between patient outcomes and licensed nurse ratio 

defining licensed nurses as RN or LPN/LVN. Nonsignificant changes in the rates of pressure 

ulcers were reported in one study64 and in patient falls in two studies64,65 corresponding to an 

additional patient per licensed nurse. 

 Patient outcomes corresponding to an increase by one patient per UAP per shift. An 

examination of the association between UAP per patient ratio and patient outcomes (Figure 8) 

showed that one additional patient per UAP was associated with an increase in the rate of 

surgical wound infection by 0.01 percent (95 percent CI 0.009-0.03), cardiac arrest by 0.04 

percent (95 percent CI 0.02-0.05), and pressure and decubitus ulcers by 0.5 percent (95 percent 

CI 0.2-0.8).Consistently across three studies33,61,75 an increase in the rate of patient falls by 0.03 

percent (95 percent CI 0.02-0.04) (heterogeneity not significant [NS]) was detected 

corresponding to an increase by one patient per UAP per shift (Appendix G, Table G8). 

 Length of stay corresponding to an increase in nurse staffing ratios. The associations 

between nurse staffing ratios and LOS in hospitals and in hospital units were reported in days 

and in relative changes in days adjusted for patients and provider characteristics (Appendix G, 

Table G9). Pooled analysis9,13,14,23,33,35,146,147,150 (Table 13) detected a reduction in length of stay 

by 0.25 days corresponding to an additional RN FTE per patient day (p value for heterogeneity 

<0.05). The reduction by 0.25 days per one RN FTE per patient day was significant but not 

consistent in medical patients. One study94 reported that every additional LPN/LVN FTE per 

1,000 patient days increased the length of stay by 1.8 days (95 percent CI 1.35-2.25). Random 

changes in LOS in relation to UAP workload were reported in one study.33

 Pooled analysis of adjusted relative changes in LOS (Figure 9) detected a 20 percent increase 

in LOS corresponding to one additional patient per RN per shift (95 percent CI 1.08-1.35, 

heterogeneity NS). The significant reduction in LOS was 31 percent in surgical patients (95 

percent CI 0.55-0.86)9,13,14 and 24 percent in ICUs (95 percent CI 0.62-0.94)8,9,13,14

corresponding to an increase by one RN FTE per patient day. In contrast, one study19 reported 

that every patient per LPN/LVN reduced LOS by 22 percent (95 percent CI 0.71-0.86). 

 Patient outcomes in quartiles of nurse to patient distribution. We analyzed the relative 

risk of patient outcomes among different quartiles of patients per RN per shift distribution 

(Figures 10-12). Relative risk of hospital acquired pneumonia was 0.75 times less in surgical 

patients when an RN was assigned to 4.9 patients compared to more than five patients per shift 

(Figure 10). In medical patients, the reduction in ratio from more than six to two or less patients 

per RN per shift was associated with a 41 percent reduction in hospital acquired pneumonia. 

Relative risk of nosocomial infection was 94 percent less in surgical patients corresponding to a 

reduction from 2.8 to two or less patients per RN per shift. A significant consistent across the 

studies reduction in relative risk of nosocomial infection in medical patients was observed by 33-

38 percent when one RN was assigned to less than two patients. In contrast, the relative risk of 

urinary tract infection was higher in medical patients corresponding to an increase in RN 

staffing. 

 The effect of reduction in patients per RN per shift on patient outcomes was greater in ICUs 

and in surgical patients (Figure 11). The relative risk of cardiopulmonary resuscitation was 0.54 

and 0.75 times less when one RN was assigned to 3.3 and more than four patients, respectively 

compared with two patients per RN per shift. Surgical patients experienced cardiac arrest 0.69-
31 

0.75 times less often with less than two patients per RN vs. 2.8 and 4.9 patients per RN 

respectively. The reduction in RN workload was consistently associated with a decrease in 

relative risk of failure to rescue in surgical patients by 25-39 percent when one RN was assigned 

to less than two patients vs.4.9 and more than five patients, respectively. The same direction of 

association in ICUs and in surgical patients was shown with the reduction in relative risk of 

pulmonary failure, and unplanned extubation across quartiles of patients per RN per shift 

distribution (Figure 12). A nonlinear association between patients per RN ratio and medical 

complications was observed in ICUs. The reduction from 3-3.6 patients per RN to less than 1.5 

patients was associated with a relative decrease by 17 percent (p = 0.03, heterogeneity NS) in 

LOS in ICUs. The LOS was 22 percent shorter with a ratio of 1.6-2.5 patients per RN compared 

with 3-3.6 patients per RN in ICUs (p = 0.03, heterogeneity NS). 

 In conclusion, despite the substantial heterogeneity in the studies, some consistent evidence 

from observational studies suggests that increased RN to patient ratio is associated with a 

reduction in hospital-related mortality, failure to rescue, unplanned extubation, pulmonary 

failure, and bloodstream infections after adjustment for patient and provider characteristics and 

reduced LOS of surgical patients. While the effect size is greater in surgical patients and ICUs, 

the optimal ratio seems to be within the first quartiles of distribution of patients per RN per shift 

in ICU and in surgical patients. The evidence in medical patients is less consistent and needs 

further investigation. 

Question 2. Association Between Nurse Hours per Patient 

Day and Patient Outcomes 

Total Nurse Hours per Patient Day and Hospital Related Mortality 

 Four studies examined the association between total nurse hours per patient day and hospital 

related mortality, three at the hospital level26-28 and one at the unit level.139 A consistent and 

significant reduction in death rate by 1.98 percent for every additional nurse hour per patient (95 

percent CI 0.96-3 percent) was observed (p = 0.0005, heterogeneity NS). The rate was slightly 

higher (2.1 percent) in three studies analyzed at the hospital level (95 per cent CI 1-3.1 percent, 

p = 0.0004). Every additional nurse hour per patient day reduced the death rate by 1.4 percent 

(95 percent CI 0.5-2.3) in medical patients26-28 and by 2.3 percent (95 percent CI 1.2-3.3) in 

surgical patients26,27 (heterogeneity NS). One large study reported non-significant changes in the 

relative risk of death corresponding to an increase by one hour in total nursing hours per patient 

day.27 

 RN hours per patient day and hospital related mortality. The association with RN hours 

per patient day did not show significant changes in mortality rates in four studies.26-28,139 Pooled 

analysis that examined the relative risk of death in relation to RN hours per patient day did not 

detect significant association.18,19,26,27,30,141 Random changes in the risk of death were observed 

by pooling three studies at hospital level analysis18,19,26,27,30 in medical units,27 in surgical 

patients,26,27 and in medical patients.26-28 One multi-hospital study reported a 2 percent reduction 

in mortality (RR 0.98, 95 percent CI 0.97-0.99) in medical patients.150 Another study 

demonstrated a small but significant increase in the relative risk of death corresponding to one 

additional RN hour per patient day.141 
32 

 We conducted combined pooled analysis with RN hours per patient day reported by the 

authors and estimated from RN to patient ratios. An increase of one RN hour per patient day was 

associated with a small but consistent reduction in the relative risk of hospital-related mortality. 

A reduction of 1 percent was observed in ICUs (RR 0.96, 95 percent CI 0.99-1.0),8,9,13,14,16 in 

surgical patients (RR 0.90, 95 percent CI 0.98-1.0),12-16 and in medical patients (RR 0.99, 95 

percent CI 0.99-1.0).8,10,11,17-19

 LPN/LVN and UAP hours per patient day and hospital related mortality. Two studies 

examined the association between death rates and LPN/LVN hours per patient day26,27 and 

three18,19,27 reported the relative risk of death corresponding to increased LPN/LVN hours. After 

pooling all three studies, every additional LPN/LVN hour per patient day was associated with an 

increase in the crude death rate of 3.4 percent (95 percent CI 2.1-4.8). One study reported an 

additional LPN/LVN hour was associated with a 2.5 percent increase in the crude death rate in 

medical units (95 percent CI 1.8-3.2),27 with a greater increase in surgical patients by 3.3 percent 

(95 percent CI 2.4-4.2)26,27 (heterogeneity NS). Combined analysis of reported and estimated 

LPN/LVN hours detected inconsistent increases in death rate. The relative risk of hospitalrelated mortality was not significant in individual studies (Appendix G, Table G10) and pooled 

analysis. One study examined the association between mortality and UAP hours per patient day 

reporting random changes in crude death rates and adjusted risk of mortality.27

 Patient outcomes corresponding to an increase of 1 total nurse hour per patient day.

(Appendix G, Tables G11-G13). The results of pooled analysis of changes in patient outcomes 

corresponding to one additional nurse hour per patient day are presented in Table 14. The pooled 

analysis showed a significant consistent reduction in sepsis among surgical patients by 1.33 ± 

0.27 percent,26,27,46 failure to rescue by 3.53 ± 0.48 percent,26,27 urinary tract infection by 4.23 ± 

0.97 percent,26,27,76,78 hospital acquired pneumonia by 2.2 ± 0.52 percent,26,27,151 surgical wound 

infection by 0.31 ± 0.05 percent,26,27 pressure ulcers by 2.26 ± 0.34 percent,26,27,76,78,151 shock by 

0.77 ± 0.14 percent,26,27 pulmonary failure by 2.39 ± 0.49 percent,26,27 and deep venous 

thrombosis by 0.45 ± 0.11 percent.26,27 In medical patients an additional nurse hour per patient 

day was associated with a consistent reduction in failure to rescue by 1.39 ± 0.5 percent,26,27

urinary tract infection by 1.88 ± 0.36 percent,26-28,76-78,81 hospital acquired pneumonia by 0.89 ± 

0.27 percent,26-28,45,79,81 shock by 0.34 ± 0.05 percent,26,27 and deep venous thrombosis by 0.15 ± 

0.05 percent.26,27

 An observed increase in nosocomial infection was not consistent across the studies. 

Differences in patient falls was significant in ICUs only49,61,64,75,139 with a reduction by 0.08 ± 

0.01 percent corresponding to additional nurse hour per patient day. 

 Pooled analysis of the adjusted relative risk (Figure 13) detected a significant 12 percent 

reduction in nosocomial infection corresponding to an increase of one nurse hour per patient day 

(95 percent CI 0.84-0.92), but the heterogeneity was significant (p for heterogeneity = 

0.001).33,45,46,63,80 However, a consistent nonlinear quadratic association was detected (p = 0.02) 

whereby an increase of more than nine total nurse hours per patient day was associated with a 13 

percent reduction in the relative risk of nosocomial infection. One study reported a reduction in 

the risk of shock by 16 percent (95 percent CI 0.71-0.99) and in gastrointestinal bleeding by 1 

percent (95 percent CI 0.98-0.99) per one total nurse hour per patient day. Two studies that 

assessed the relative risk of thrombo-embolic complications reported random changes in 

risk.27,129 Three studies that examined the risk of sepsis found only random changes in relation to 

nurse hours.27,46,62 Four studies that assessed the risk of pressure ulcers and total nurse hours did 
33 

not detect significant changes.27,62,129,151 Two studies that assessed relative risk of pulmonary 

failure also showed random change in risk of the outcomes.27,62 The relative risk of hospital 

acquired pneumonia was not associated with total nurse hours.27,62,81,129,151 Nursing hours were 

not associated with failure to rescue in one study.27

 Patient characteristics can influence the association between outcomes and nurse hours. (We 

rely here largely on broad definitions like surgical vs. medical patients.) The adjustment for 

comorbidities28,29,36,65,75,76,139,153,154 attenuated the effect of nursing hours on patient falls (p for 

interaction <.0001) and the risk of nosocomial infections and nurse hours per patient day (p for 

interaction = 0.001).45,46,81

 Patient outcomes corresponding to an increase by 1 RN hour per patient day. The 

results of a pooled analysis of the rates of various patient outcomes (Appendix G, Tables G14-

G15) corresponding to one additional RN hour per patient day (reported by the authors and 

estimated from RN FTE per patient day ratios) are presented in Table 15. The associations varied 

in different clinical settings. In ICUs, an additional RN hour per patient day was associated with 

a consistent reduction in patient falls by 0.06 ± 0.01 percent61,64,75,139and pulmonary failure by 

1.43 ± 0.23 percent.13,14,23 In medical patients, a consistent reduction in bloodstream infection by 

0.22 ± 0.09 percent was seen22,26-28,45,47,79 with a significant but not consistent decrease in 

pressure ulcers by 1.06 ± 0.32 percent.26-28,33,36,61,63,64,76,77,154-156

 Additional RN hours were associated with an increase in rates of urinary tract infection in 

surgical and medical patients and hospital acquired pneumonia in medical patients (heterogeneity 

significant for all these associations). 

 Pooled analysis of the adjusted relative risk is presented in Figure 14 with a significant but 

not consistent reduction in nosocomial infection by 24 percent (95 percent CI 0.69-0.83) 

corresponding to one additional RN hour per patient day (p for heterogeneity <0.01).45,147 One 

study reported a significant 21 percent reduction in the relative risk of central line associated 

bloodstream infections by (p <.0001) corresponding to an increase of one RN hour per patient 

day in surgical patients in ICUs.147 The large multi-center study showed a significant reduction 

by 1 percent in urinary tract infection in medical patients (RR 0.99, 95 percent CI 0.98-1) 

corresponding to one additional RN hour per patient day and absolute reduction by 3.6 percent in 

rates of urinary tract infection comparing 25th and 75th percentiles of RN hours. The same study 

also reported a relative reduction by 2 percent (RR 0.98, 95 percent CI 0.97-0.99) in upper 

gastrointestinal bleeding in medical patients per additional RN hour per patient day and a 5.2 

percent absolute reduction in the rate of this outcome between the 25th and 75th quartiles of RN 

hours. We conducted a combined pooled analysis using measures reported by the authors and 

estimated from ratios of RN hours per patient day (Figure 15). Additional RN hours per patient 

day in ICUs were associated with a reduction in relative risk of hospital acquired 

pneumonia,13,14,22 pulmonary failure,13,14,23,24 unplanned extubation,13,14,23-25 and nosocomial 

infection.22,45, 47,79,147 In surgical patients, the relative risk of failure to rescue was lower by 1 

percent,12,15,16,20,26,27, 30,31 unplanned extubation by nine percent,13,23,24 and cardiac arrest by four 

percent13,23,24 for every additional RN hour per patient day. Small reductions by 1 percent in 

relative risk of pulmonary failure35,62 and deep venous thrombosis27,35 was detected in medical 

patients. 

 Patient outcomes corresponding to an increase by one LPN/LVN hour per patient day. 

Patient outcome rates from pooled analysis corresponding to one additional LPN/LVN hour per 

patient day are presented in Table 16. The crude rates of most outcomes increased corresponding 
34 

to an additional one LPN/LVN hour per patient day; this raise was consistent across the studies 

(heterogeneity NS for all outcomes). However, additional LPN/LVN hours were associated with 

lower rates of several outcome in medical patients. Patient falls were lower by 0.21 ± 0.03 and 

sepsis was lower by 0.29 ± 0.12 percent per 1 LPN hour per patient day (heterogeneity NS). 

 Pooled analysis of the studies that analyzed relative risk of hospital acquired 

pneumonia26,27,33,157 and studies that assessed the risk of urinary tract infections26,27,33,77,157 did 

not find significant associations with LPN/LVN hours. 

 One study158 reported a reduction in the rate of thrombo-embolic complications by -0.3 ± 0.1 

percent (p = 0.01), of pulmonary failure by -1.2 ± 0.2 percent (p = 0.002), and pneumonia by -1.7 

± 0.3 percent (p = 0.002) corresponding to one additional LPN/LVN hour per patient day 

(Appendix G, Table G16). One study detected a significant reduction by 87 percent in the 

relative risk of hospital acquired pneumonia (p = 0.004) for one LPN/LVN hour per patient 

day.18

 Patient outcomes corresponding to an increase of one licensed hour per patient day. The 

rate of pressure ulcers,64 failure to rescue,27,159 falls,64,65 and CPR159 was not associated with 

licensed hours per patient day. One large study reported a reduction by 11 percent in risk of 

urinary tract infections (RR 0.89, 95 percent CI 0.8-0.99), by 1 percent in gastrointestinal 

bleeding (RR 0.987, 95 percent CI 0.98-1.00) and hospital-acquired pneumonia (RR 0.99 95 

percent CI 0.98-1.00), and by 3-4 percent in pressure ulcers (RR 0.97, 95 percent CI 0.94-0.99) 

and bloodstream infections (RR 0.96 95 percent CI 0.95-0.97) corresponding to an additional 

licensed hour per patient day in surgical patient at hospital level analysis.27 The relative risk of 

shock,27,159 thrombosis,27 combined complications,27 and hospital-acquired pneumonia was not 

associated with licensed hours per patient day27,159

 Patient outcomes corresponding to an increase by 1 UAP hour per patient day. The 

results of the pooled analysis of patient outcomes corresponding to 1 additional UAP hour per 

patient day are presented in Figure 16. An increase of 1 UAP hour per patient day was associated 

with a significant consistent reduction in pressure ulcers by 2.07 percent (0.88-3.26) 

(heterogeneity NS),27,36,76-78 patient falls by 0.2 percent (95 percent CI 0.14-0.26),33,36,61,75,76,78

and urinary tract infection by 1.26 percent (95 percent CI 0.16-2.36).27,33,76-78 We could find no 

studies that examined the relative risk of patient outcomes corresponding to UAP hours 

(Appendix G, Table G17). 

 Length of stay corresponding to an increase by 1 nurse hour per patient day. The results 

from a pooled analysis of changes in the length of stay corresponding to 1 additional total nurse 

hour per patient day are presented in Figure 17. An additional total nurse hour per patient day 

was associated with a decreased LOS by 1.43 days (95 percent CI 0.31-2.25) in eight studies 

(heterogeneity NS),26-28,36,45,48, 82,83 by 0.45 days in medical patients (95 percent CI 0.19 -0.72, 

heterogeneity NS),26-28,36,45,48,82,83 and by 2.36 days in surgical patients (95 percent CI 1.34-3.39, 

heterogeneity NS).26,27,48,82,83 The association between RN hours per patient day and LOS was 

not consistent across the studies with random changes in the pooled estimate and significant 

heterogeneity in the results (p for heterogeneity = 0.05).26-28,36,45 The relationship between nurse 

staffing and LOS in medical patients showed conflicting results (p for heterogeneity = 0.0008).26-

28,36,45 The studies in surgical patients did not find a significant association with RN hours (p for 

heterogeneity = 0.013).26,27 

 The studies that examined the association between LPN/LVN hours and LOS reported a 

significant increase by 3.21 days (95 percent CI 1.88-4.3) corresponding to an additional 
35 

LPN/LVN hour.26,27 The effect was larger in surgical patients with an increase by 4.6 days for 

every LPN/LVN hour per patient day.26,27 An increase by 1.53 days (95 percent CI 0.93-2.13) in 

LOS corresponded to 1 additional UAP hour per patient day (heterogeneity NS).27,36,45 The 

increase in medical patients was 1.6 days (heterogeneity NS)27,36,45

 Patient outcomes in quartiles of the distribution of nurse hours per patient day. We 

analyzed rates of patient outcomes among different quartiles of nurse hours per patient day 

distribution (Table 17). A decrease in nurse hours per patient day from 12.1 hours to 8.3 hours in 

ICUs was associated with an increase in the rate of patient falls by 0.76 ± 0.22 percent. A 

decrease in nurse hours per patient day from more than 11 vs. 9.5 hours in surgical patients was 

associated with an increase in the rate of failure to rescue by 3.22 ± 0.6 percent, surgical wound 

infection by 0.29 ± 0.05 percent, upper gastrointestinal bleeding by 0.81 ± 0.19 percent, shock by 

0.68 ± 0.16 percent, pulmonary failure by 2.17 ± 0.5 percent, deep venous thrombosis by 0.42 ± 

0.1 percent, urinary tract infection by 4.1 ± 0.85 percent, sepsis by 1.3 ± 0.24 percent, and 

pressure ulcers by 2.31 ± 0.31 percent. A reduction in the total nurse hours from more than 9.6 

hours per patient day in medical patients was associated with a 0.36 ± 0.04 percent increase in 

the rate of shock, 2.49 ± 0.19 percent in urinary tract infection, and 1.35 ± 0.15 percent in 

hospital acquired pneumonia. The relative risk of failure to rescue was 8 percent higher in 

medical (RR 1.08, 95 percent CI 1.07-1.1) and 49 percent higher in surgical patients (RR 1.49, 

95 percent CI 1.32- 1.69). When we compared the highest and the lowest quartiles of RN hours 

per patient day (Figure 18), the relative risk of cardiopulmonary resuscitation was 1.52 times 

higher corresponding to a decrease from more than 16 to 8.2 RN hours per patient day in ICUs. 

In surgical patients, a reduction from more than 10 to 8.4 RN hours per patient day was 

associated with a 66 percent increase in the relative risk of cardiac arrest (RR 1.66, 95 percent CI 

1.49-1.85). The relative risk of unplanned extubation was three times higher in ICUs (RR 3.12, 

95 percent CI 1.97-4.96) corresponding to a decrease in RN hours per patient day from more 

than 16 to less than six. 

 In conclusion, the evidence from observational studies suggests that an increase in total nurse 

hours per patient day was associated with reduced hospital mortality, failure to rescue, 

nosocomial bloodstream and urinary tract infections, and other adverse events. The effects of RN 

hours substantially differ among the studies and patient population. A few studies suggest that 

LPN/LVN hours may increase the rates of sepsis, shock, urinary tract infections, and hospital 

inquired pneumonia in surgical patients. Additional UAP hours reduced the rate of pressure 

ulcers, patient falls, and urinary tract infection but not other outcomes. Increasing to more than 

16 RN hours per patient day may reduce the risk of cardiopulmonary resuscitation, pulmonary 

failure, and unplanned extubation in ICUs. Increasing to more than 10 RN hours per patient day 

in surgical patients is associated with reduced risk of CPR, failure to rescue, and unplanned 

extubation. The LOS in hospitals is lower along with additional total nursing, but not LPN/LVN 

and UAP hours. 

 Evidence of the association between nurse characteristics and patient outcomes. Some 

evidence (Appendix G, Table G18) suggests that nurse experience and education can influence 

patient outcomes (Figure 19). The crude rates of complications were reduced by 1.13 percent (95 

percent CI 1.9-0.36) for each additional year of nurse experience in surgical patients in the 

ICU.16 In the same study, an increase by 1 percent in the proportion of nurses with BSN degrees 

reduced the rate of failure to rescue by 0.04 percent (95 percent CI 0.06-0.02). The same study 

reported that an increase in the crude rate of failure to rescue corresponding to 1 year of nurse 
36 

experience was not significant after adjustment for confounding factors (RR1.01, 95 percent CI 

0.96-1.03). The authors reported a 5 percent reduction in failure to rescue corresponding to a 10 

percent increase in the proportion of nurses with BSN degrees (RR 0.95, 95 percent CI 0.91-

0.99).16 The adjusted relative risk of unplanned extubation in neonatal ICUs was not associated 

with nurse experience (relative risk 1.02, 95 percent CI 0.96-1.08 for an additional year of 

experience).25 Other studies did not show significant changes in pressure ulcers, patient falls, or 

urinary tract infections in relation to nurse experience and education. 

 Several nurse surveys assessed perceived nurses’ satisfaction about patient 

outcomes21,36,66,78,88,101,160-164 (Appendix G, Table G19.) One large survey (8,760 nurses)163

examined the relative risk of adverse events among Medicare patients in relation to perceived 

quality of care. Nurses responded to the survey question, “In general, how would you describe 

the quality of nursing care delivered to patients in your unit on your last shift?” A reduction by 

16 percent in the relative risk of patient falls and medication errors corresponded to a 30 percent 

increase in nurses satisfied with the care provided.163 An increase in the proportion of nurses’ 

perceived work related stress by 40 percent increased the rates of patient falls by 1.1 percent.66 A 

2 percent increase in nurse autonomy accompanied a 0.5 percent reduction in pressure ulcer 

rates.162 An increase in nurse turnover by approximately 2 percent increased the rate of patient 

falls by 0.2 percent.36 

There is limited evidence suggesting better nurse staffing is associated with patient 

satisfaction with nursing care and pain management (Appendix G, Table G-20). In an early study 

of this phenomenon, larger proportions of patients treated in magnet-designated hospitals were 

satisfied with provided care compared with conventional (nonmagnet designated) general 

medical units (85percent vs. 74 percent).160 Surgical patients in units using a total patient care 

model (larger proportion of RNs) were more satisfied with pain management compared with a 

team nursing model (84.6 ± 13 vs. 83.4 ± 13 scores on the Parkside Patient Satisfaction 

Survey).165 Medical patients in units with higher proportions of RNs with BSN degrees 

(54percent) expressed satisfaction with care 1.5 times more often.88 An increase by 1 hour in 

total nurse hours per patient day was associated with an increase by 2.44 ± 0.62 patient 

satisfaction scores with pain management, an increase by 1 percent in the proportion of nurses 

with BSN degrees was associated with greater satisfaction by 13.6 ± 3.6 patient satisfaction 

scores.154 Some studies, however, did not detect a significant improvement in patient satisfaction 

in relation to nurse staffing.77,78,166

 In conclusion, some evidence from a few observational studies suggests that an increase in 

nurses with BSN degrees may reduce the risk of hospital-related mortality and failure to rescue. 

Hospitals with higher proportions of nurses with BSN degrees (36 percent vs.11 percent) have 

lower mortality. States with larger proportions of BSN degrees report lower rates of fatal injuries 

related to health care. Nurses’ perceived satisfaction may reflect the quality of care. 

Question 3. What Factors Influence Nurse Staffing Policies? 

 Policies related to nurse staffing in hospitals can vary. There may be policies related to the 

shift length, scheduling nurses to rotate to different shifts, mandatory overtime, weekend 

staffing, use of agency or temporary nurses, assigning nurses to nursing units other than those 

they are regularly assigned to work (floating), use of full-time, part-time, and internationally 
37 

educated nurses, the nurse-to-patient ratio or nursing hours per patient day for nursing units, and 

the skill mix (licensed vs. unlicensed staff) of nursing units (Figure 2). Staffing policies can be 

influenced by patient and patient care unit factors. For example, the fluctuation of patient flow 

on a nursing unit may determine policies for the length of the shift for nurses. Nurse staffing 

policies can also be influenced in hospitals in which nurses are unionized or in which nurses 

have a strong governance structure. The age and/or tenure of nurses in a hospital may have an 

impact on policies regarding rotating shifts or frequency of working weekends. 

 Review of the literature to determine factors that can influence nurse staffing policies did not 

reveal any studies that empirically examined influences on nurse staffing policy. Rather, all 

studies found for this review examined one or more of the staffing policy variables. Thirty-six 

studies were identified as eligible and relating to one or more of the staffing policy variables. 

One hundred forty-seven studies were identified as eligible and relating to one or more of the 

staffing policy variables (Appendix G, Tables G21-G26). One hundred seventeen studies were 

excluded for the following reasons: not related to the variable of interest (87); from conference 

proceedings (2); an integrative review not related to the variables of interest (1); relevant to 

nursing homes (3); not in peer reviewed journals (17); inadequate presentation of data (6); not 

research (1). A review of 30 studies for each of the staffing policy variables is provided. For the 

staffing policy variable staffing ratio/mix/hours, the findings from the studies analyzed for 

questions 1, 2, and 4 are applied. The factors identified in Figure 2 were included in a few of the 

studies reviewed and will be described in the review for each of the staffing policy variables. 

Some studies addressed more than one staffing policy variable and are included in more than one 

evidence table. 

Staffing Ratios/Mix/Hours 

 The research literature related to nurse staffing ratios or hours and staff mix was 

comprehensively reviewed in the first two questions examined for this review using metaanalytic approaches. None of the studies empirically examined the effect or impact of a staffing 

policy related to staffing ratios/hours or staff mix. However, several studies examined the impact 

of the California mandated staffing ratios—an externally imposed staffing policy64,109,162

(Appendix G, Table G21). These findings should be cautiously used to inform staffing policies 

because these studies have limitations in their design and data sources. 

 Licensed nurses working in California acute care hospitals and nurse staffing in those 

hospitals were characterized prior to the implementation of mandated nurse staffing ratios.109 A 

low percentage of RNs (39 percent) have baccalaureate degrees and the mix of RNs ranged from 

30 percent (sub-acute/transitional) to 84 percent (postpartum/labor/delivery) by different types of 

nursing care units. RN-to-patient ratios varied by type of hospital ownership in California (1:3.2 

to 1:7.4)162 as well as RN skill mix (56.9 percent to 66.6 percent). Following the implementation 

of the mandated staffing ratios, total RN hours of care per patient day increased by 20.8 percent 

and the number of patients per RN decreased by 17.5 percent. There was no change in the use of 

contract staff. However, despite the increased exposure of patients to RN time, there was no 

reduction in falls, the prevalence of pressure ulcers, or restraint use.64

 Two recent systematic reviews of nurse staffing and patient, nurse, and hospital outcomes 

reached basically similar conclusions.92,93 Both concluded that the studies reviewed had a 

number of limitations which implies caution in interpretation of the findings and translating 
38 

findings to staffing policies (e.g., data from one unit or hospital, no control for case mix 

variations, variations in staffing and outcome measures, hospital level data, or data presented as 

regression coefficients which are difficult to interpret clinically). Other variables likely 

associated with quality of care should be considered for hospital staffing policies or legislated 

staffing ratios.92 These included acuity of the patients, skill mix, competence of nurses, 

technological support, and institutional support of nursing. This research supports probable 

relationships between richer nurse staffing and several patient and nurse outcomes; whereas 

another study showed strong support for the positive relationship between higher RN skill mix 

and improved outcomes.93 

 Studies with implications for staffing policies that were related to nurse-patient ratios or RN 

skill mix, but found to be ineligible for meta-analysis, are summarized in Appendix G, Table 

G21. A study conducted in 19 teaching hospitals in Ontario, Canada, supported the relationship 

between RN skill mix for patient, nurse, and hospital outcomes. The proportion of Regulated 

Nursing Staff (Canadian equivalent of RNs in the United States) was associated with better 

patient outcomes in regard to function, pain, satisfaction167 infections, nurses’ perceptions of the 

quality of care, and fewer medication errors.168,169 

 Several studies found marginal, and in some cases diminishing effects, of increased RN 

staffing and patient outcomes. Greater than 15 nursing hours per patient day on medical and 

medical-surgical units no longer improved the patient fall rate; however, on surgical units, fall 

rates improved when nursing hours exceeded 15 hours.170 Diminishing effects of increased RN 

staffing on reducing the mortality ratio were also found.18

 The findings from the meta-analyses in this report related to nurse-patient ratios/hours and 

RN skill mix and specifically examined the relationship between nurse staffing and patient and 

nurse outcomes. These studies did not examine relationships between hospital factors, patient 

factors, or nursing characteristics on nurse staffing policy variables. However, the findings from 

the meta-analyses conducted with these studies may have implications for nurse staffing policies 

regarding RN skill mix or nurse-to-patient ratios. The largest proportion of studies for the metaanalysis was associated with nurse to patient ratios and hospital related mortality. The findings 

indicate that a higher RN to patient ratio is associated with a decrease in hospital-related 

mortality. Nurses with baccalaureate degrees in nursing were associated with a reduction in 

mortality. Negative patient outcomes are also reduced by increasing the RN to patient ratio. 

There is less evidence for how LPNs/LVNs and UAPs reduce negative patient outcomes; in fact, 

there is a trend indicating that an increased LPN/LVN and UAP to patient ratio increases 

negative outcomes. The studies examining the relationship between RN hours per patient day 

differed substantially; however, there was stronger evidence that total nurse hours per patient day 

were associated with reduced mortality and negative patient outcomes. Again, there was a trend 

indicating that LPN/LVN and UAP hours per patient day were associated with increased 

negative patient outcomes. The findings from the meta-analysis examining nurse staffing ratios 

suggest hospital staffing policies that provide for a higher RN skill mix. If staffing ratios become 

part of a hospital staffing policy, they need to consider the type of patient as well as other factors 

that may impact desired patient and nurse outcomes (e.g., education of nurse, care delivery 

models, patient factors). Staffing policies that require regular evaluation of staffing effectiveness 

on patient care units serving different types of patients would seem essential. 

 Figure 2 suggests that nursing organizational factors have an intervening effect on the 

relationship between hospital factors and nurse staffing policies. None of the studies reviewed 
39 

for question 3 supported this relationship, although several studies examined the direct 

relationship between hospital factors and nurse staffing policy variables. The technological 

sophistication of hospitals (technology level) was associated with a higher proportion of RNs on 

the unit.171 More sophisticated use of technology predicted increased RN hours.162 For-profit 

hospitals and for-profit systems had fewer RN productive hours for medical-surgical nursing 

units; however, this finding seemed to be driven by two large for-profit health systems in the 

sample.162 Another study did not find that ownership was related to nurse staffing variables.172

The two studies were conducted in two different states. They did find that the type of unit 

(patient care unit factors) affected hospital RN staffing. Intensive care, pediatric, and maternity 

units had significantly higher RN staffing than medical/surgical or gynecologic units. Controlling 

for size, rural hospitals also had higher RN staffing. Primary nursing, a nursing care delivery 

model, explained more than half of the variability in nurse staffing, using about one-third more 

RNs per occupied bed.172 While nursing care delivery models were not hypothesized in Figure 2 

to be a factor influencing nurse staffing policies, it makes sense that it would be a factor because 

the primary nursing care delivery model relies on a higher proportion of RNs to be successfully 

implemented. 

 Shift work of nurses. Seven studies specifically focused on the length of shift nurses work 

(8, 10, and 12 hours) and the types of shifts nurses were scheduled to work (days, evenings, 

nights, or a combination) (Appendix G, Table G22). Two recent survey design studies examined 

the work patterns of hospital staff nurses. A survey of nurses who were members of the ANA 

(n=393)173 and a randomly selected sample of nurses who participated in the National Institute 

for Occupational Safety and Health (NIOSH) Nurse Worklife Survey (n = 2,273)174 both found 

that nurses were working long hours. Nurses worked, on average, 55 minutes longer than 

scheduled each day.173 Of the 5,317 shifts worked by the respondents during a 28 day period, 

38.7 percent of the shifts were 12.5 hours or more. One quarter of the respondents worked 50 

hours per week for two or more weeks of the 28-day period. More than half of hospital nurses 

were working 12 or more hours per day but half as likely to work 6-7 days a week, suggesting 

that more hospital nurses are working 12 hour shifts. Older nurses (≥50 years) were less likely to 

work long shifts.174 

 The likelihood of making medication and procedural errors (actual and near miss errors) 

increased with longer work hours and was three times higher when nurses worked shifts lasting 

12.5 hours or longer.173 Age of the nurse (nurse factor), hospital size (hospital factor), or type of 

unit (unit factor) did not have any affect on errors or near errors. Among 687 RNs and LPNs 

surveyed in one hospital medication and procedural errors were associated with nurses that 

rotated shifts.175 In addition, nurses who rotated shifts had a higher risk of having an automobile 

accident or other injuries. Among nurses from across the country who worked in critical care 

units on the day (n = 67) and night shifts (n = 75) the ones who worked permanently on the night 

shift had significantly more depression and poorer global sleep quality than nurses on the day 

shift.176 There was no significant difference between night and day shift nurses in regards to 

chronic fatigue or anxiety. However, 46 percent of the variance in chronic fatigue was explained 

by depression and global sleep quality. There was no relationship between physical health and 

mental depression of nurses working the day, evening, night, and rotating shifts from five 

hospitals (n = 463).177 Nurses working 12-hour shifts experienced significantly higher levels of 

stress than nurses working 8-hour shifts, but the stress levels were similar when controlling for 

experience.178 Nurses working rotating shifts experienced higher stress and lower perception of 
40 

job performance. Nurses working the night shift reported receiving the least amount of sleep and 

had the most trouble sleeping.177

 The findings from these seven descriptive studies that used survey methodologies indicate 

that nurses are working long hours. Because more nurses are working 12-hour shifts (by 

preference), the risk of working more than 12 hours is high, given that nurses are often not able 

to finish their work by the end of their scheduled shift. There is beginning evidence that working 

more than 12 hours and rotating shifts can lead to errors that compromise patient safety as well 

as accidents, injuries, and higher stress levels of nurses. Implications for staffing policies indicate 

that the length of nurses’ shifts should be no more than 12 hours and strategies should be 

implemented to limit work hours exceeding 12 hours. Requiring nurses to work rotating shifts 

should be curtailed. 

Contract (agency) nurses. There is little research on the use of agency staff (Appendix G, 

Table G23). One descriptive study indicates that nurses choosing to work for a staffing agency 

are not necessarily motivated by nonsalary benefits and hospital nurses are not motivated by the 

higher salary paid to agency nurses.179 In that same survey, agency nurses were more likely to 

work evening and night shifts and weekends. The clinical activities differed by agency and 

hospital nurses reported having less opportunity to use their clinical skill.180 Nurse managers do 

not view agency nurses as cost effective but believe that using agency nurses reduces overtime 

and provides coverage for weekends, vacations, and absenteeism. Managers’ perceptions of 

quality care of supplemental staff did not differ for hospital pool supplemental staff versus 

agency staff.181 Float pool nurses had the highest rate of documentation on two clinical aspects of 

patient care;182 however, there were significant limitations to the study, including being 

conducted on only one unit of a hospital and using medical record documentation as a measure 

of evaluating nursing care quality of agency staff. From a hospital efficiency perspective, agency 

nurses were associated with higher hospital operating cost.50

 These studies provide limited insight to guide implications for staffing policies regarding 

agency nurses. It should be noted that a number of studies were found on the use of agency 

nurses, but these studies were conducted in countries other than the United States and Canada. 

Research is needed to evaluate the effectiveness and effective use of agency staff in hospitals as 

a means to provide adequate staffing for quality patient care. 

 Full- and part-time nurses. Few studies addressed the full or part time status of nurses 

(Appendix G, Table G24). There were discrepancies in the demographics reported for full- and 

part-time nurses. Two large surveys of Canadian nurses demonstrated these differences. In one, 

part-time nurses were reported to be older,183 whereas full-time nurses were older.184 This 

difference may be related to a 10-year difference in the time these studies were done. A trend in 

the studies was that full-time nurses experienced higher role overload,185 heavier workloads, 

higher levels of stress, and poorer physical wellbeing.184 Full-time nurses were statistically more 

involved in their job183 and more likely to be confident, independent, functioning as a leader and 

professional.186 Nurses who worked part time reported liking their work schedules more and 

experienced less interference between their work and nonwork activities. From an organizational 

perspective,187 Part-time nurses were associated with lower personnel and hospital costs.50

 Internationally educated nurses. A strategy to address the nursing shortage and the 

growing demands of staffing in hospitals has been the utilization of IENs (Appendix G, Table 

G25). There is a paucity of research on the use and effectiveness of IENs in U.S. hospitals.37 The 

limited research available includes qualitative exploratory studies38,39 and descriptive studies40-42
41 

that examined IEN use in healthcare. No studies empirically evaluated the interaction of IEN 

staffing policies with organizational, nurse, or patient care unit factors. Lack of research becomes 

more notable when it is recognized that IENs represent approximately 3.7 percent of the RN 

population within the United States.37 Understanding this demographic group may facilitate more 

effective integration and use of nurses who are educated in and emigrate from other countries. 

 IENs experience moderate to high levels of stress for up to 10 years after coming to the 

United States to practice nursing.39 IENs from India experienced racism within the work setting 

with recommendations for interventions to assist with acculturation.38 Other idiosyncrasies noted 

about IENs include the tendency to gravitate to critical care,40,42 younger in age,37,42 the majority 

from the Philippines,37 more likely to work full-time, night, and evening shifts and more 

overtime,37 baccalaureate educated,37,42 and half as likely to leave the organization.37 No 

differences were found between IENs and U.S. nurses when comparing perceptions of their 

control over practice or relationship with the physician,41 job satisfaction as it relates to time to 

do the job or quality of care,42 or general job satisfaction.37,42 Despite the lack of empirical 

evidence that articulates the relationship of IENs within the organization, the accumulation of 

these exploratory and descriptive data may assist in understanding human resource demographics 

more clearly. Further studies are warranted to understand healthful integration of IENs into the 

acute care system of the United States for the purpose of formulating organization policy. 

 Nurse overtime. Another staff policy to secure adequate staffing for increasing patient 

demands and scarce resources is the use of overtime (Appendix G, Table G26). Again, few 

studies were found in regards to this staffing variable. The prevalence of overtime has been 

documented in a recent national survey. Seventeen percent of randomly selected nurses reported 

required mandatory overtime and those whose jobs included mandatory overtime worked 

significantly longer work hours.174 Almost two-thirds of nurses, in a survey of RNs who were 

members of the ANA, worked overtime ten or more times during a 28-day period and more than 

25 percent reported working mandatory overtime.173

 Unionization does not seem to be effective in minimizing overtime. A review of overtime 

use in New York State hospitals for 5 years found that overtime was 22 percent higher for 

unionized nurses.43 Occupancy, average hourly wage, and hours in the average work week were 

not associated with RN overtime within hospitals. When controlling for year-to-year variations 

in overtime for each hospital, higher RN straight hours was significantly associated with higher 

RN overtime. Each 1 hour increase in straight time was associated with an 8.7 percent increase in 

overtime.43,44

 RN overtime does not seem to be associated with the location of the hospital, teaching status 

of the hospital, average hours in a nurse’s work week, acute bed occupancy, acute average daily 

census, or financial margin of the hospital44 however, an analysis of nurse overtime over 7 years 

in New York State hospitals found that overtime increased more in nongovernment unionized 

hospitals and nonteaching hospitals.43 Working overtime increased the odds of making at least 

one medication-related error and the risk of making errors increases when nurses work overtime 

after longer shifts.173 Weekend overtime is associated with anticipated turnover.188 Lost time 

claim rates were associated with increasing overtime worked by nurses.189 A few studies suggest 

that mandatory overtime and overtime in general is prevalent for nurses in U.S. hospitals. There 

is evidence that overtime and excessively long working hours can compromise patient safety and 

impact turnover of nurses. These findings suggest that practices related to nurse overtime and 

associated policies are important. 
42 

Question 4. Association Between Nurse Staffing Strategies 

and Patient Outcomes 

 We defined eligible nurse staffing strategies as skill mix (proportion of productive [i.e., 

direct patient care related] hours worked by registered and licensed nurses), the proportion of 

overtime hours, contract hours, and the proportion of full-time nurses employed in patient care. 

The distribution of nurse staffing strategies is presented in Table 18. We identified 48 studies 

that assessed the proportion of RNs; eight studies addressed licensed nurses; 12 studies examined 

the effects of contract nurse hours on patient outcomes; and only a few studies evaluated 

overtime hours and the proportion of full-time nurses. The details on the sources used to measure 

nurse staffing strategies and on study design are presented in Appendix G, Tables G27-G28. 

Patient Outcomes Corresponding to an Increase by 1 Percent in the 

Proportion of RNs 

 Studies examined the effects of changes in categories of nurse staffing patterns including not 

only the proportion of RNs, but nurse hours and ratios on a number of outcomes. Pooling these 

results with random effects models to examine the main effect of the nursing skill mix on patient 

outcomes detected substantial heterogeneity between studies. For instance, heterogeneity was 

significant when pooling eight studies that examined the rates of in-hospital mortality (p for 

heterogeneity = 0.04),26,28,33,52,139,140,146.190,191 eight studies that measured the rates of nosocomial 

infections (p <0.001),22,45,81,139,192-194 and 11 studies that evaluated the rates of pressure ulcers in 

relation to nursing skill mix (p for heterogeneity <0.001).26,28,33,36,61,64,76,77,81,151,162 

 To estimate whether the direction or strength of the associations can explain the massive 

differences in the results, we calculated and compared the rates of outcomes in individual studies 

(Appendix G, Table G28) when possible (Table 19). Three studies reported significant 

reductions in mortality140,190,191 by 0.1-0.4 percent; one unpublished dissertation showed a small 

but significant increase in mortality86 by 0.04 percent; the rest did not find significant 

associations. The same unpublished study reported a small increase in pulmonary failure and 

other patient outcomes corresponding to an increase in RNs.33 Random changes in the rates of 

nosocomial infections were shown in the majority of the studies. One study detected a reduction 

in hospital-acquired pneumonia by 0.02 percent (95 percent CI 0.01-0.02).28 A seemingly 

paradoxical finding was the increase in the rates of urinary tract infections in four studies, with a 

significant increase by 0.05-0.11 percent for each increase in the percent of RNs in two 

reports.28,33 One study139 reported nonlinear association in patient falls and pressure ulcers: the 

rates increased when more than 87.5 percent of RNs worked in units. Pooled analysis (Figure 20) 

detected a significant reduction in patient falls by 0.03 percent (95 percent CI 0.03-0.04) 

corresponding to one additional percent of RNs in ICUs. Rates of patient outcomes were 

increased in medical and surgical patients per additional percent of RNs. 

 The analysis of the adjusted relative risks of patient outcomes corresponding to an increase 

by 1 percent in RN composition is presented in Figure 21. Random changes in the relative risk of 

all patient outcomes were observed corresponding to each additional percent of RN time. One 

large study27 contributed the most to the analysis. One study reported a 16 percent reduction in 

hospital-related mortality in hospitals with 83 percent of RNs compared with 63 percent (RR 
43 

0.84 percent CI 0.78-0.92).195 Three studies reported a tendency to reduce mortality,8,26,101 and 

one large study27 found substantial differences in the association with mortality in different levels 

of analysis and patient populations, which resulted in significant statistical heterogeneity in the 

results (p for heterogeneity <0.001) (Figure 22). The same study,27 however, reported a 

consistent reduction in failure to rescue by 27 percent (RR 0.73, 95 percent CI 0.65-0.83) for an 

additional percent of RN staffing. Pulmonary failure (Figure 23) was not associated with the 

proportion of RNs in one study.27 Another study reported a nonsignificant reduction by 25 

percent (RR 0.11-4.98) in relative risk of pulmonary failure corresponding to doubling the 

proportion of RNs.62 The relative risk of shock was reduced by 41 percent for each additional 

percent of RN staffing in a large multi-hospital study.27 The studies did not show significant 

associations with nosocomial infections, surgical wounds infections, and bloodstream infections. 

One study reported a significant reduction in the risk of urinary tract infections in surgical 

patients.27 Overall complications and thrombo-embolic complications increased with the increase 

in the proportion of RNs.27 An increase by 1 percent in the proportion of RN staffing was 

associated with a reduction in the risk of upper gastrointestinal bleeding by 42 percent (RR 0.58, 

95 percent CI 0.4-0.84) and in pressure ulcers by 76 percent (RR 0.24, 95 percent CI 0.09-0.62) 

across different settings and patient populations in one study (Figure 24).27 The same study 

reported a reduction in the relative risk of urinary tract infection in medical (RR 0.48, 95 percent 

CI 0.38-0.91) and in surgical patients (RR 0.67, 95 percent CI 0.46-0.98), upper gastrointestinal 

bleeding (RR 0.66, 95 percent CI 0.45-0.96), hospital acquired pneumonia (RR 0.59, 95 percent 

CI 0.44-0.8), and shock (RR 0.46, 95 percent CI 0.27-0.81) corresponding to an increase by 1 

percent in the proportion of RN hours among licensed hours per patient day.27 

 A higher proportion of RNs was associated with shorter lengths of stay by 0.17 days (95 

percent CI 0.03-0.3) but the association was not consistent across studies (p for heterogeneity 

<0.001). The effect was significant in medical patients only with a decrease by 0.19 days for 

each 1 percent of RN staffing (95 percent CI 0.1-0.28) but still not consistent (p for heterogeneity 

<0.05).26,28,33,36,45,48,146,150,194 

Patient Outcomes Corresponding to an Increase by 1 Percent in the 

Proportion of Licensed Nurses 

 Eight studies attempted to assess the proportion of licensed nurses in relation to patient 

outcomes26,27,30,31,35,63-65,159 (Table 20 and Figures 25-26) but one study27 contributed most of the 

data for the overall estimates. An increase by 1 percent in the proportion of licensed nurses was 

associated with a 17 percent reduction in the risk of failure to rescue (RR 0.83, 95 percent CI 

0.78-0.87) (Figure 25). Hospital-related mortality was reduced by 3 percent (RR 0.97, 95 percent 

CI .95-0.98) for every additional percent of licensed nurses. Cardiac arrest occurred 0.59 times 

less often in association with a 1 percent increase in the proportion of licensed nurses in medical 

and surgical patients (RR 0.59, 95 percent CI 0.49-0.71) (Figure 26). Pulmonary failure 

demonstrated random changes in relation to nurse skill mix. Every additional percent of licensed 

nurses was associated with a 47 percent reduction in the relative risk of shock (RR 0.53, 95 

percent CI 0.46-0.61). The risk of hospital acquired pneumonia was reduced by 29 percent (RR 

0.71, 95 percent CI 0.63-0.8) in relation to every additional percent of licensed nurses, but the 

strength of the association differed across patient populations (p for heterogeneity = 0.02). 
44 

Among other nosocomial infections, the risk of urinary tract infections was reduced by 13 

percent (RR 0.87, 95 percent CI 0.83-0.9), while the risk of surgical wound infection and 

bloodstream infections was increased by 60 percent as reported in one study.27 The same 

negative tendency was observed in the risk of thrombo-embolic complications, where a 29 

percent increase corresponded to an additional percent of licensed staff (RR 1.29, 95 percent CI 

1.08-1.54). One study reported a significant increase in the length of stay by 0.05 days (95 

percent CI 0.04-0.05) for each additional 1 percent of licensed nurses.35

Patient Outcomes Corresponding to an Increase by 1 Percent in 

Overtime Hours 

 Two studies30,193 examined the association between overtime hours and patient outcomes 

(Appendix G, Table G29). Every additional 10 percent of overtime hours was associated with a 

1.3 percent increase in hospital related mortality (RR 1.013, 95 percent CI 1.0001-1.65).30 The 

association was nonlinear (p = 0.006) with an increase in hospital-related mortality by 32 percent 

corresponding to an increase in overtime hours by 10 percent from nadir (7 percent) to 17 

percent. 

 The rate of nosocomial infections increased by 1.9 percent (95 percent CI 0.3-3.5 percent) 

with each additional percent of overtime hours.193 The relative risk of shock increased by 12 

percent in medical but not surgical patients (RR 1.12, 95 percent CI 1.001-1.24) corresponding to 

a 5 percent increase in overtime hours.31 The relative risk for bloodstream infections increased 

by 11.5 percent in surgical (RR 1.12, 95 percent CI 1.021-1.22) and by 14 percent in medical 

patients (RR 1.14, 95 percent CI 1.05-1.24).31 That study did not find an association between 

overtime hours and urinary tract infections, failure to rescue, or gastrointestinal bleeding. 

Patient Outcomes Corresponding to an Increase by 1 Percent in 

Contract Hours 

 The majority of the studies that reported the proportion of contract hours did not examine the 

main effect of temporary nurses; rather they reported patient outcomes in units and hospitals with 

different staffing patterns including nursing ratios and hours. Some authors distinguished 

contract hours from hours worked by float nurses;28.46,64,193 others included the hours worked by 

float nurses as temporary hours.45,47 One study showed no association between contract hours 

and the rates of urinary tract infections, pneumonia, pressure ulcers, surgical wound infections, 

or bloodstream infections.28 Two studies reported an increase in rates of patient falls 

corresponding to additional contract hours.28,64 A small increase in the rate of nosocomial 

infections corresponded to an increase in contract hours,193 but another study did not find a 

significant association after adjustment for other factors.46 In contrast with contract hours, the 

proportion of float nurses was positively associated with the risk of nosocomial infection. The 

risk was 2.61-2.71 times higher in patients cared for in units with more than 60 percent of float 

nurses.47 Another study reported an increase in the rate of bloodstream infection by 5 percent 

corresponding to a 23 percent increase in the proportion of float nurses.45 Summarizing the 

results from two studies46,47 that examined the risk of sepsis in relation to float nurses, the risk 

was 2.79 time higher for every percent increase in float hours (RR 2.8, 95 percent CI 2.8-2.79). 
45 

An increase in the proportion of temporary nurses by 1 percent of contract hours increased the 

length of stay by 0.1 day (RR 0.11, 95 percent CI 0.03-0.18, heterogeneity NS).28,45,48,50

 In conclusion, some evidence from a few multi-hospital studies suggests that a higher 

proportion of RNs may reduce the risk of failure to rescue, shock, pressure ulcers, and 

gastrointestinal bleeding. A significant but not consistent reduction on LOS in medical patients 

was observed pooling the results from 12 studies. 

 Overtime hours may increase the risk of hospital-related mortality and bloodstream 

infections. An increase in contract hours may increase in-hospital LOS. A small amount of 

evidence suggests that an increase in hours worked by float nurses is associated with a large 

increase in the risk of bloodstream infections. 
46 

Figure 4. Flow of study selection for questions 1, 2, and 4 

 

101 eligible for review Excluded 2,757 for the reason: 

60 case reports 

574 comments, success stories 

54 editorials, expert opinions 

21 letters 

3 guidelines 

24 interviews 

44 legal cases 

89 news, reprinting of original reports 

1 web survey 

112 review, secondary data analysis 

158 no association tested 

598 no information on nurse staffing and 

strategies 

160 ineligible outcomes 

859 ineligible target population 

Databases: 

The National Library of Medicine via PubMed®

CINAHL - Cumulative Index to Nursing & Allied Health Literature 

The Cochrane Library 

BioMed Central 

Catalog of U.S. Government Publications (U.S. GPO) 

LexisNexisTM Government Periodicals Index 

Digital Dissertations 

Agency of Health Care Research and Quality 

Total Citations 2,858 

96 Included in meta-analysis (94 

studies, 2 duplicates) 

Design: 

7 case-control 

3 case series 

41 cross sectional 

43 that assessed temporality 

5 excluded (inadequate data 

presentation) 
47 

Table 2. Distribution of the studies’ quality* (94 studies)

Quality Measures Mean 

Standard 

Deviation Median 

Study question clearly focused and appropriate 4.69 0.73 5 

Clear definition of exposure 3.96 0.65 4 

Clear definition of the primary and secondary outcomes 4.41 0.65 4.5 

Sampling of study population 3.34 0.81 3 

Statistical analysis: assessment of confounding attempted 3.61 1.11 4 

Adjustment for the effects of various factors 2.89 1.62 3.5 

Statistical methods 3.70 0.94 4 

Measure of effect for outcomes 3.66 1.11 4 

External validity 3.48 0.97 4 

Conclusions 4.01 0.68 4 

Total scores 37.76 6.40 38 

* Maximum possible score of 5; total of 50 for each study 
48 

Table 3. Distribution of nurse hours and ratios (94 studies) 

Nurse Staffing Number of Studies Mean Standard Deviation 

ICUs 

RN FTE/patient day 15 1.3 0.7 

Patients/RN/shift 15 3.1 1.8 

Total nursing hours/patient day 15 13.0 5.2 

RN hours/patient day 10 12.6 5.3 

LPN/LVN hours/patient day 3 0.3 0.6 

UAP hours/patient day 4 2.3 1.2 

Licensed nurse hours/patient day 1 7.3 0.4 

Surgical patients 

RN FTE/patient day 13 1.1 0.8 

Patients/RN/shift 13 4.0 2.3 

Patients/LPN/shift 2 3.1 2.2 

Total nursing hours/patient day 12 8.7 4.3 

RN hours/patient day 11 8.1 5.1 

LPN/LVN hours/patient day 7 1.3 1.1 

UAP hours/patient day 5 2.1 0.6 

Medical patients 

RN FTE/patient day 20 1.1 1.0 

Patients/RN/shift 20 4.4 2.9 

Patients/LPN/shift 6 13.3 8.5 

Patients/UAP/shift 4 12.0 8.9 

Patients/licensed nurse/shift 2 4.1 1.1 

Total nursing hours/patient day 27 8.2 4.4 

RN hours/patient day 23 6.1 3.6 

LPN/LVN hours/patient day 13 2.3 2.0 

UAP hours/patient day 12 2.5 2.1 

Licensed nurse hours/patient day 4 3.3 2.9 
49

Table 4. Hospital-related mortality rates corresponding to changes in patients/RN ratio (pooled weighted estimates from publis

Level of Analysis Number of Studies Change in Death Rate, % Standard Error p Value for the Association p 

He

Authors’ definition of nurse to patient ratio Increase by 1 patient/RN/shift 3 0.095 0.03 0.003 Increase by 1 RN FTE/patient day 3 -1.24 1.13 0.311 Increase by 1 RN FTE/1,000 patient days 1 -1.29 0.54 0.076 Estimated Increase by 1 RN FTE/patient day All studies 8 -1.18 0.49 0.02 ICUs 3 -0.97 0.28 <0.001 Surgical patients 5 -0.89 0.49 0.08 Medical patients 3 -1.18 0.78 0.15 Hospital level analysis 3 -3.48 2.68 0.25 Patient level analysis 5 -1.18 0.55 0.04 
50

Table 5. RN to patient ratios and relative risk* of hospital-related mortality (pooled adjusted estimates from published studies) 

Level of Analysis Number of Studies Relative Risk 95% CI p Value for the Association Con

Authors’ definition of nurse to patient ratio Increase by patient/RN/shift 6 1.08 1.07; 1.09 <.0001 Increase by 1 RN FTE/patient day 6 0.943 0.93; 0.953 <.0001 Increase by 1 RN FTE/1,000 patient days 3 0.995 0.95; 1.04 0.8273 

Estimated Increase by 1 RN FTE/patient day 

All studies 14 0.92 0.90; 0.94 <.0001 Patient level analysis 8 0.919 0.89; 0.95 0.0002 Hospital level analysis 5 0.958 0.94; 0.98 0.0001 ICUs 5 0.908 0.86; 0.96 0.0321 Surgical patients 8 0.84 0.80; 0.89 <.0001 Medical patients 6 0.944 0.94; 0.95 <.0001 Quartiles of patients/RN/shift ratio <2 vs. 2-4 14 0.94 0.92; 0.95 <.0001 <2 vs. 4-5.5 0.76 0.71; 0.81 <.0001 <2 vs. >6 0.62 0.59; 0.66 <.0001 2-4 vs. 4-5.5 0.81 0.76; 0.87 <.0001 2-4 vs.>6 0.66 0.63; 0.70 <.0001 4-5.5 vs. >6 0.82 0.76; 0.88 <.0001 ICUs 5 <3 vs. 3-4 0.94 0.92; 0.97 0.016 Medical patients 6 <2 vs. 2-4 0.94 0.92; 0.96 <.0001 Surgical patients 8 <2 vs. 4-6 0.76 0.70; 0.82 0.000 <2 vs. >6 0.62 0.58; 0.66 <.0001 2-3.5 vs. 4-6 0.80 0.74; 0.87 0.001 2-3.5 vs. >6 0.65 0.61; 0.70 <.0001 4-6 vs. >6 0.81 0.75; 0.88 0.001 

* Relative risk of outcomes - the ratio of the incidence rate of outcomes corresponding to different nurse staffing levels (relative risk =1 mprotective effect of increased nurse staffing, >1 – increased probability of patient outcomes). 95% CI – ranges of relative risk with 95% co

the same results repeating the study many times in the same population. 
51 

Figure 5. Relative risk of patient hospital-related mortality corresponding to change in registered nurse to 

patient ratio (pooled estimation from the studies) 

Relative risk of death

.79 1 1.1

Nurse staffing measure (number of studies)

Relative risk of death

(95% CI)

All studies

Increase by 1 patient/RN/shift (6) 1.08 (1.08, 1.09)

Increase by 1 RN FTE/patient day (6) 0.94 (0.93, 0.95)

Increase by 1 RN FTE/1,000 patient days (3) 0.99 (0.95, 1.04)

Increase by 1 RN FTE/patient day (14) 0.92 (0.90, 0.94)

Hospital level analysis

Increase by 1 RN FTE/patient day (5) 0.96 (0.94, 0.98)

ICUs

Increase by 1 RN FTE/patient day (5) 0.91 (0.86, 0.96)

Medical patients

Increase by 1 RN FTE/patient day (6) 0.94 (0.94, 0.95)

Patient level analysis

Increase by 1 RN FTE/patient day (8) 0.92 (0.89, 0.95)

Surgical patients

Increase by 1 RN 

FTE/patient day (8)

0.84 (0.80, 0.89)
52 

Figure 6. Relative risk of death among different categories of patients/RN/shift (pooled analysis) 

 Relative risk of death

 .5 1

Quartiles of patients/RN/shift distribution

Relative risk of death

(95% CI)

All studies

<2 vs. 2-4 0.94 (0.92, 0.95)

<2 vs. 4-5.5 0.76 (0.71, 0.81)

<2 vs. >6 0.62 (0.59, 0.66)

2-4 vs. 4-5.5 0.81 (0.76, 0.87)

2-4 vs. >6 0.66 (0.63, 0.70)

4-5.5 vs. >6 0.82 (0.76, 0.88)

ICUs

<3 vs. 3-4 0.94 (0.92, 0.97)

Medical patients

<2 vs. 2-4 0.94 (0.92, 0.95)

Surgical patients

<2 vs. 4-6 0.76 (0.70, 0.82)

<2 vs. >6 0.62 (0.58, 0.66)

2-3.5 vs. 4-6 0.80 (0.74, 0.87)

2-3.5 vs. >6 0.65 (0.61, 0.70)

4-6 vs. >6 0.81 (0.75, 0.88)
53

Table 6. Number of avoided deaths/1,000 hospitalized patients attributable to RN FTE/patient day ratio (pooled adjusted estima

studies) 

Level of Analysis Studies RR 95% CI 

Attributable to Nurse 

Staffing, Percentage of 

Death, 95% CI 

NNT* 

H

Authors’ definitions of nurse staffing ratio Increase by patient/RN/shift 6 1.08 1.07; 1.09 7.6 (7.07; 8.04) 198 Increase by 1 RN FTE/patient day 6 0.94 0.93; 0.95 6 (7; 5) 162 Estimated increase by 1 RN FTE/patient day All studies 14 0.92 0.90; 0.94 8 (10; 6) 191 Patient level analysis 8 0.92 0.89; 0.95 8 (11; 5) 154 Hospital level analysis 5 0.96 0.94; 0.98 4 (6; 2) 342 Intensive care units 5 0.91 0.86; 0.96 9 (14; 4) 187 Surgical patients 8 0.84 0.80; 0.89 16 ( 20; 12) 164 Medical patients 6 0.94 0.94; 0.95 6 (6; 5) 211 Quartiles of patients/RN/shift ratio <2 vs. 2-4 14 0.94 0.92; 0.95 6 (8; 5) 247 <2 vs. 4-5.5 0.76 0.71; 0.81 24 (29; 19) 63 <2 vs. >6 0.62 0.59; 0.66 38 (41; 35) 40 2-4 vs. 4-5.5 0.81 0.76; 0.87 19 (24; 13) 80 2-4 vs. >6 0.66 0.63; 0.70 34 (37; 30) 45 4-5.5 vs. >6 0.82 0.76; 0.88 18 (24; 12) 83 ICUs 5 <3 vs. 3-4 0.94 0.92; 0.97 6 (8; 3) 308 Medical patients 6 <2 vs. 2-4 0.94 0.92; 0.96 6 (8; 5) 187 Surgical patients 8 ≤2 vs. 4-6 0.76 0.70; 0.82 24 (30; 18) 107 

≤2 vs. >6 0.62 0.58; 0.66 38 (42; 34) 68 

2-3.5 vs. 4-6 0.80 0.74; 0.87 20 (26; 13) 132 2-3.5 vs. >6 0.65 0.61; 0.70 35 (39; 30) 75 4-6 vs. >6 0.81 0.75; 0.88 19 (25; 12) 141 

* Number needed to treat to generate benefit (saved life) 
54

Table 7. Calculated relative risk of hospital-related mortality corresponding to increased RN staffing (results from individual st

Study, Analytic 

Unit RR 95% CI Data, Definition of RN Ratio Units Patients 

HospitalMark, 200418 1.02 0.9; 1.1 Administrative, RN FTE/1,000 patient days Combined Combined Combined 

Mark, 200519 1.005 0.98;1.03 Administrative, RN FTE/1,000 patient days Combined Combined Combined Robertson, 199911 0.97 0.957; 0.98 Administrative, RN FTE/patient day Combined Medical Chronic obstru

Silber, 200012 0.93* p <0.05 Administrative, RN FTE/patient day Surgical Surgical Combined 

Elting, 200520 0.61* p <0.05 Administrative, RN FTE/patient day Surgical Surgical Bladder carcin

188.9 and 236

PatientAiken, 199910 0.28 0.2; 0.5 Medical records, RN FTE/patient day Combined Medical AIDS 

Aiken, 200215 0.58 0.4; 0.8 Administrative, RN FTE/patient day Combined Surgical General surgic

operation 

Aiken. 200316 0.89 0.848; 0.934 Administrative, RN FTE/patient day ICU Surgical General surgic

operation 

Person, 200417 0.94 0.9; 1 Administrative, RN FTE/patient day Combined Medical Acute myocard

Pronovost, 19999 0.02* p <0.05 Administrative, patients/RN/shift ICU Medical Abdominal ao

Amaravadi, 200013 0.39* NS Administrative, patients/RN/shift ICU Surgical Esophageal re

Dimick, 200114 6.5* NS Administrative, patients/RN/shift ICU Surgical Hepatic resect

Halm, 200521 1.02* NS Administrative, patients/RN/shift Surgical Surgical General, ortho

Hospital unit 

Shortell, 19948 1.13* NS Administrative, RN FTE/patient day ICU Medical Combined * 95% CI were not reported, significance reported by authors 
55

Table 8. Association between RN staffing ratio and mortality and proportion of mortality attributable to nurse staffing (results f

Author Analytic 

Unit 

Hospital 

Unit 

Patients RN Ratio Relative Risk 

Death 

(95% CI) 

Pronovost9 P ICU S, Abdominal aortic 

surgery 

Nurse to patient ratio <1:2 vs. >1:2 in evening 1.9 (1.2; 3) 

Aiken10 P C M, AIDS Increase by 1 patient/RN/shift 2.3 (1.3; 4.2) Aiken15 P ICU S, general surgical, 

orthopedic, or vascular operation 

Increase in workload of 1 patient/RN/shift 1.06 (1.01; 1.1

Aiken16 P ICU S, general surgical, 

orthopedic, or vascular operation 

Increase by 6 patients/RN/shift 1.5 (1.19; 1.97

 Increase by 1 patient/RN/shift 1.07 (1.03; 1.1

Person17 P C M, acute, myocardial, 

infarction 

4th quartile vs.1 quartile of RN staffing (~2.7 RN 

FTE/patient day vs. ~1.6 RN FTE/patient day) 

0.91 (0.86; 0.9

Elting20 H S S, bladder carcinoma 

after total cystectomy 

Hospitals with few RN FTE/occupied bed (median 1.4) vs. many (median 3.1) 

2.04 (1.03; 5.3

Mark19 H C C Increase by 1 RN FTE/1,000 patient days in hospitals with high HMO penetration 0.91 (0.86; 0.9

Increase by 1 RN in RN FTE/patient day ratio in 1989 0.988 1990 0.987 

Robertson11 H C M 

1991 0.978 

Mark18 H C C 75th quartile of RN FTE/1,000patient-days 

7.24 RN hours/patient day 0.96 (0.95; 0.9

 50th quartile of RN FTEs/1,000 patient days 

6.01 RN hours/patient day 0.97 (0.96; 0.9

 25th quartile of RN FTEs/1,000 patient days 

4.79 RN hours/patient day 0.98 (0.96; 0.9

 Increase by 1 RN FTE/1,000 patient days 0.92 (0.87; 0.9

Silber12 H S S Hospitals with 1.6 vs. 2.7 patients/RN/shift 0.95 (0.93; 0.9

P = patient; H = hospital; C = combined; S = surgical; M = medical; Attributable Proportion = proportion of deaths attributable to nurse sta
56 

Table 9. Correlation between nurse staffing and age adjusted fatal adverse events related to medical care at 

the state level1,144,148

r p Value 

Excess or shortage 0.08 0.58 

Percent of shortage -0.10 0.50 

Total number of nurses -0.11 0.62 

Employed in nursing -0.11 0.59 

Percent employed in nursing -0.12 0.56 

RN/100,000 population -0.24 0.26 

Full-time employed -0.09 0.66 

Percent full-time employed 0.13 0.55 

Part-time employed -0.13 0.55 

Percent part-time employed -0.10 0.62 

RN FTE -0.04 0.84 

Number of nurses with diploma -0.04 0.86 

Percent of nurses with diploma -0.10 0.64 

Number of nurses with associate degree 0.33 0.11 

Percent of nurses with associate degree 0.33 0.11 

Number of nurses with BSN -0.15 0.48 

Percent of nurses with BSN -0.46* 0.02 

Number of nurses with MS and PhD -0.14 0.52 

Percent of nurses with MS and PhD 0.16 0.46 

* significant at 95% level 

r = correlation coefficient 
57 

Table 10. Association between nurse education, experience, and mortality 

Author, Unit, 

Patients Nurse Education and Experience Death Rate, % 

Relative Risk, 

95% CI 

Aiken16 40% of hospital workforce with BSN or higher 2.17 

ICU 10% increase in nurses with BSN degree* -0.10 0.95 (0.9; 0.99) 

Surgical Increase by 1 year in nurse experience 0.23 0.09 

Interactions: 

 60% of hospital workforce with BSN or higher, 8 patients/day 1.98 

 40% of hospital workforce with BSN or higher, 4 patient/nurse 1.80 

 20% of hospital workforce with BSN or higher, 4 patients/nurse 1.97 

 60% of hospital workforce with BSN or higher, 6 patients/nurse 1.80 

 40% of hospital workforce with BSN or higher, 6 patients/nurse 1.98 

 20% of hospital workforce with BSN or higher, 6 patients/nurse 2.16 

 60% of hospital workforce with BSN or higher, 4 patients/nurse 1.64 

20-29% of hospital workforce with BSN or higher, 14 years of 

nurse experience 2.20 

<20% of hospital workforce with BSN or higher, 15 years of 

nurse experience 2.30 

 20% of hospital workforce with BSN or higher, 8 patients/nurse 2.38 

>50% of hospital workforce with BSN or higher, 12.5 years of 

nurse experience 1.70 

40-49% of hospital workforce with BSN or higher, 14.3 years 

of nurse experience 1.90 

30-39% of hospital workforce with BSN or higher, 14 years of 

nurse experience 1.80 

Estabrooks101 Hospitals with higher proportion of nurses with BSN 36% vs. 

low (11%) 0.81 (0.68; 96) 

Combined Hospitals with higher proportion of nurses with BSN, 36% vs. 

low (11%) (random effects model) 0.65 (0.6; 0.71) 

Medical 

Tourangeau140 Increase by 1 year in nursing experience in teaching hospitals 0.99 

Combined Increase by 1 year in nurse experience 0.99 

Medical Increase by 1 year in nursing experience in nonurban hospitals 1 

30 days mortality in teaching hospitals, 7.85 years of nurse 

experience 14.02 

30 days mortality in nonurban community hospitals, 9.47 years 

of nurse experience 15.27 

30 days mortality in urban community hospitals, 8.9 years of 

nurse experience 15.05 

*We calculated death rate corresponding to 10% increase in nurses with BSN and to 1 year increase in nurse 

experience, significant at 95% level. 
58 

Table 11. Patient outcomes rates (%) corresponding to an increase in RN staffing ratios (pooled estimation 

from the published studies) 

Outcomes Studies Difference 

in Rate, % 

Standard 

Error 

p Value for the 

Association Consistency 

Authors’ definition of nurse staffing ratio 

Increase by 1 patient/RN/shift 

Failure to rescue 1 0.35 0.12 0.01 

CPR 3 0.45 0.06 0.001 No 

Falls 2 3.88 1.26 0.05 Yes 

Urinary tract infection 2 -0.71 0.41 0.10 Yes 

Pneumonia 2 2.04 1.62 0.43 Yes 

Nosocomial Infection 5 -0.03 0.08 0.68 No 

Pressure ulcers 2 -1.26 0.41 0.06 No 

Pulmonary failure 3 6.54 1.04 0.001 Yes 

Unplanned extubation 3 4.20 0.31 0.001 No 

Estimated increase by 1 RN FTE/patient day 

Failure to rescue 3 -0.67 0.20 0.001 No 

Falls 3 -13.43 1.55 0.001 No 

Urinary tract infection 3 5.18 1.94 0.02 Yes 

Pneumonia 2 -3.57 2.84 0.43 Yes 

Nosocomial Infection 6 0.23 0.40 0.57 No 

Pressure ulcers 2 3.94 1.11 0.04 No 

Pulmonary failure 4 -0.03 0.02 0.11 Yes 

Unplanned extubation 3 -7.35 0.55 0.001 No 

Thrombosis 1 -0.05 0.04 0.29 

Estimated increase by 1 RN FTE/patient day in ICUs 

Failure to rescue 1 -3.69 1.26 0.01 

CPR 3 -0.78 0.10 0.002 No 

Pulmonary failure 3 -11.45 1.82 0.003 Yes 

Unplanned extubation 3 -7.35 0.55 0.001 No 

Estimated increase by 1 RN FTE/patient day in surgical patients 

Failure to rescue 2 -3.32 1.25 0.02 Yes 

CPR 3 -0.78 0.10 0.002 No 

Sepsis 5 -1.15 0.42 0.02 No 
59 

Table 12. Relative risk of patient outcomes corresponding to an increase in RN staffing ratios (pooled 

estimation from the studies) 

Outcomes Studies Relative 

Risk 95% CI p Value for the Association Consistency 

Authors’ definition of nurse staffing ratio 

Increase by 1 patient/RN/shift 

Hospital acquired pneumonia 3 1.07 1.03; 1.11 0.001 Yes 

Failure to rescue 3 1.08 1.07; 1.09 <.0001 No 

Pulmonary failure 4 1.53 1.24; 1.89 0.001 Yes 

Unplanned extubation 5 1.45 1.27; 1.67 <.0001 Yes 

Nosocomial infection 3 1.03 0.98; 1.07 0.24 No 

CPR 3 1.16 1.05; 1.29 0.008 Yes 

Medical complications 3 1.17 1.04; 1.31 0.01 Yes 

Increase by 1 RN FTE/patient day 

Failure to rescue 2 0.92 0.92; 0.92 0.002 No 

Estimated increase by 1 RN FTE/patient day

ICU 

Hospital acquired pneumonia 3 0.7 0.56; 0.88 0.02 Yes 

Pulmonary failure 4 0.4 0.27; 0.59 0.001 Yes 

Unplanned extubation 5 0.49 0.36; 0.67 0.001 Yes 

CPR 3 0.72 0.62; 0.84 0.002 Yes 

Medical complications 3 0.72 0.6; 0.86 0.005 Yes 

Surgical patients 

Urinary tract infection 1 1.68 1.06; 2.67 0.05 

Failure to rescue 5 0.84 0.79; 0.9 0.001 Yes 

Nosocomial infection 2 0.08 0.04; 0.18 <.0001 No 

Surgical wound infection 1 0.15 0.03; 0.82 0.051 

Sepsis 5 0.64 0.46; 0.89 0.015 Yes 

Patient level analysis 

Failure to rescue 4 0.91 0.89; 0.94 0.002 Yes 

Pulmonary failure 5 0.94 0.94; 0.94 <.0001 Yes 
60 

Figure 7. Patient outcomes rates (%) corresponding to an increase by patient per LPN/LVN per shift 

(calculated from one study) 

Difference in outcome rate

-.1 0 .2

Patient outcomes

Difference in outcome rate

(95% CI)

CPR 0.03 (0.02, 0.04)

Falls 0.03 (0.02, 0.04)

Urinary tract infection 0.06 (-0.02, 0.13)

Hospital acquired pneumonia 0.06 (0.04, 0.07)

Surgical wound infection 0.02 (0.01, 0.02)

Pulmonary Failure 0.04 (0.02, 0.05)
61 

Figure 8. Patient outcomes rates (%) corresponding to an increase by patient/UAP/shift (estimates from 

individual studies and pooled analysis) 

Difference in outcome rate

-.78 0 .78

Outcomes (number of studies)

Difference in outcome rate

(95% CI)

CPR (1) 0.04 (0.02, 0.05)

Falls (7) 0.03 (0.02, 0.04)

Urinary tract infection (5) 0.24 (0.04, 0.44)

Hospital acquired pneumonia (2) 0.04 (-0.08, 0.16)

Surgical wound infection (2) 0.01 (0.00, 0.03)

Pressure (decubitus) ulcers (7) 0.47 (0.17, 0.78)

Pulmonary failure (2) 0.03 (-0.01, 0.07)
62 

Table 13. Length of stay corresponding to an increase in RN staffing ratios (pooled analysis) 

Nurse Staffing Studies 

Change in 

Length of Stay, 

Days 

Standard 

Errors 

p Value for 

the 

Association 

Consistency 

Authors’ definitions 

Increase by 1 patient/RN/shift 6 0.7 0.8 0.4 Yes 

Increase by 1 RN FTE/patient day 2 -0.25 0.03 <.0001 Yes 

Estimated increase by 1 RN FTE/patient day 

All studies 10 -0.25 0.02 <.0001 No 

ICUs 5 -0.70 1.64 0.68 Yes 

Surgical patients 5 -0.63 1.50 0.68 Yes 

Medical patients 5 -0.25 0.02 <.0001 No 
63 

Figure 9. Relative changes in LOS corresponding to an increase in RN staffing ratios (pooled estimation 

from the studies) 

Relative change in LOS

 .4 1 1.5

Nurse staffing (number of studies)

Relative change in LOS

(95% CI)

All studies

Increase by 1 patient/RN per shift (3) 1.20 (1.08, 1.35)

Increase by 1 RN FTE/1,000 patient days (1) 0.97 (0.93, 1.02)

Increase by 1 RN FTE/patient day (5) 0.92 (0.80, 1.05)

ICUs

Increase by 1 RN FTE/patient day (4) 0.76 (0.62, 0.94)

Medical patients

Increase by 1 RN FTE/patient day (2) 0.93 (0.78, 1.10)

Surgical patients

Increase by 1 RN FTE/ 

patient day (3)

0.69 (0.55, 0.86)
64 

Figure 10. Relative risk of hospital acquired infections in quartiles of patients/RN/shift distribution (pooled 

analysis) 

*The following table shows how the patients/RN/shift quartiles were established. 

Quartiles ICU Surgical Patients Medical Patients 

0 <1.6 <2 <2 

1 2.0 2.8 3.0 

2 3.3 4.9 4.8 

3 >4 >5 >6 

.3 1 1.3

Quartiles of patients/RN per shift distribution* Relative risk of outcomes

(95% CI) Hospital acquired pneumonia

2 vs. 3 (Surgical patients) 0.75 (0.60, 0.95)

0 vs. 3 (Medical patients) 0.59 (0.40, 0.87)

1 vs. 3 (Medical patients) 0.82 (0.70, 0.95)

Nosocomial infection

0 vs. 1 (Surgical patients) 0.06 (0.01, 0.34)

0 vs. 1 (Medical patients) 0.66 (0.48, 0.91)

0 vs. 2 (Medical patients) 0.67 (0.48, 0.93)

0 vs. 3 (Medical patients) 0.62 (0.45, 0.85)

Sepsis

0 vs. 2 (ICUs) 0.57 (0.36, 0.91)

1 vs. 2 (ICUs) 0.58 (0.36, 0.94)

0 vs. 1 (Surgical patients) 0.56 (0.37, 0.84)

0 vs. 3 (Surgical patients) 0.51 (0.28, 0.91)

2 vs. 3 (Surgical patients) 0.71 (0.55, 0.93)

Surgical wound infection

2 vs. 3 (Surgical patients) 0.80 (0.68, 0.94)

Urinary tract infection

2 vs. 3 (Surgical patients) 1.07 (1.02, 1.11)

0 vs. 1 (Medical patients) 1.11 (1.01, 1.22)

0 vs. 2 (Medical patients) 1.11 (1.01, 1.22)

0 vs. 3 (Medical patients) 1.13 (1.03, 1.23)

Relative risk of outcomes
65 

Figure 11. Relative risk of patient outcomes in quartiles of patients/RN/shift distribution (pooled analysis) 

*The following table shows how the patients/RN/shift quartiles were established. 

Quartiles ICU Surgical Patients 

0 <1.6 <2 

1 2.0 2.8 

2 3.3 4.9 

3 >4 >5 

 Relative risk of outcomes

 .4 1

Quartiles of patients/RN per shift distribution*

Relative risk of outcomes

(95% CI)

CPR

0 vs. 2 (ICUs) 0.66 (0.59, 0.73)

1 vs. 2 (ICUs) 0.54 (0.47, 0.61)

1 vs. 3 (ICUs) 0.75 (0.67, 0.83)

0 vs. 1 (Surgical patients) 0.69 (0.55, 0.87)

0 vs. 2 (Surgical patients) 0.75 (0.59, 0.95)

Failure to rescue

0 vs. 2 (Surgical patients) 0.75 (0.67, 0.83)

0 vs. 3 (Surgical patients) 0.61 (0.56, 0.66)

1 vs. 2 (Surgical patients) 0.79 (0.72, 0.88)

1 vs. 3 (Surgical patients) 0.65 (0.60, 0.70)

2 vs. 3 (Surgical patients) 0.82 (0.73, 0.91)
66 

Figure 12. Relative risk of patient outcomes in quartiles of patients/RN/shift distribution (pooled analysis) 

*The following table shows how the patients/RN/shift quartiles were established. 

Quartiles ICU Surgical Patients 

0 <1.6 <2 

1 2.0 2.8 

2 3.3 4.9 

3 >4 >5 

Relative risk of outcomes

.2 1 1.7

Quartiles of patients/RN per shift distribution*

Relative risk of outcomes

(95% CI)

Medical complications

0 vs. 2 (ICUs) 0.59 (0.49, 0.71)

1 vs. 2 (ICUs) 0.54 (0.44, 0.66)

1 vs. 3 (ICUs) 0.75 (0.62, 0.90)

2 vs. 3 (ICUs) 1.38 (1.17, 1.64)

Pulmonary failure

0 vs. 2 (ICUs) 0.40 (0.23, 0.69)

0 vs. 3 (ICUs) 0.36 (0.19, 0.69)

1 vs. 3 (ICUs) 0.43 (0.21, 0.86)

0 vs. 1 (Surgical patients) 0.38 (0.20, 0.72)

0 vs. 2 (Surgical patients) 0.25 (0.11, 0.55)

Unplanned extubation

0 vs. 2 (ICUs) 0.55 (0.39, 0.78)

0 vs. 3 (ICUs) 0.32 (0.20, 0.51)

1 vs. 3 (ICUs) 0.43 (0.30, 0.62)

2 vs. 3 (ICUs) 0.58 (0.42, 0.80)

0 vs. 1 (Surgical patients) 0.56 (0.38, 0.82)

0 vs. 2 (Surgical patients) 0.29 (0.18, 0.46)

1 vs. 2 (Surgical patients) 0.51 (0.38, 0.69)
67 

Table 14. Patient outcomes rates (%) corresponding to an increase by 1 hour in total nursing hours/patient 

day (pooled analysis) 

Outcomes Studies 

Difference 

in Outcome 

Rate, % 

Standard 

Error 

p Value for the 

Association Consistency 

ICUs 

Falls 5 -0.08 0.01 <0.001 Yes 

Nosocomial infection 4 -0.83 0.31 0.03 No 

Sepsis 3 -0.24 0.47 0.63 Yes 

Pressure ulcers 5 -0.90 0.65 0.30 Yes 

Surgical patients 

Failure to rescue 2 -3.53 0.48 <.0001 Yes 

Falls 3 0.12 0.07 0.16 Yes 

Urinary tract infection 4 -4.23 0.97 0.001 Yes 

Hospital acquired pneumonia 3 -2.20 0.52 0.002 Yes 

Nosocomial infection 2 0.44 0.27 0.19 Yes 

Sepsis 3 -1.33 0.27 0.001 Yes 

Surgical wound infection 2 -0.31 0.05 0.000 Yes 

Pressure ulcers 5 -2.26 0.34 <.0001 Yes 

Gastrointestinal bleeding 2 -0.89 0.18 0.001 Yes 

Shock 2 -0.77 0.14 0.000 Yes 

Pulmonary failure 2 -2.39 0.49 0.001 Yes 

Thrombosis 2 -0.45 0.11 0.002 Yes 

Medical patients 

Failure to rescue 2 -1.39 0.50 0.02 Yes 

Falls 11 -0.17 0.13 0.18 Yes 

Urinary tract infection 7 -1.88 0.36 <.0001 Yes 

Hospital acquired pneumonia 5 -0.89 0.27 0.004 Yes 

Nosocomial infection 5 0.11 0.04 0.01 No 

Sepsis 5 -0.06 0.05 0.25 Yes 

Pressure ulcers 13 0.33 0.20 0.10 Yes 

Gastrointestinal bleeding 2 -0.44 0.10 0.002 Yes 

Shock 2 -0.34 0.05 <.0001 Yes 

Thrombosis 2 -0.15 0.05 0.008 Yes 
68 

Figure 13. Relative risk of patient outcomes corresponding to an increase by 1 hour in total nursing 

hours/patient day 

 0

Relative risk of outcomes

 .7 1.1

Outcomes (number of studies)

Relative risk of outcomes

(95% CI)

Shock (1) 0.84 (0.71, 0.99)

Gastrointestinal bleeding (1) 0.99 (0.98, 1.00)

Nosocomial infection (5) 0.88 (0.84, 0.92)
69 

Table 15. Patient outcomes rates (%) corresponding to an increase by 1 hour in RN hours/patient day 

(pooled analysis reported by the authors and estimated RN hours/patient day) 

Outcomes Studies Difference in 

Outcome Rate, %

Standard 

Error 

p Value for the 

Association Consistency 

ICUs 

Failure to rescue 1 -0.46 0.16 0.013 

CPR 4 -0.10 0.01 0.001 No 

Falls 4 -0.06 0.01 0.001 Yes 

Urinary tract infection 1 1.55 1.12 0.397 Yes 

Hospital acquired pneumonia 3 -0.46 0.25 0.210 Yes 

Nosocomial infection 7 0.01 0.18 0.964 Yes 

Sepsis 7 -0.10 0.07 0.168 Yes 

Pressure ulcers 4 -0.19 0.48 0.760 Yes 

Pulmonary failure 3 -1.43 0.23 0.003 Yes 

Unplanned extubation 3 -0.92 0.07 0.000 No 

Surgical patients 

Failure to rescue 4 -0.73 0.77 0.353 No 

CPR 5 -0.10 0.01 0.001 No 

Urinary tract infection 7 3.22 1.47 0.039 No 

Hospital acquired pneumonia 6 1.15 0.70 0.114 No 

Nosocomial infection 3 0.60 0.08 <.0001 Yes 

Sepsis 7 0.73 0.45 0.120 No 

Surgical wound infection 2 0.10 0.16 0.528 No 

Pressure ulcers 4 -0.04 1.02 0.966 No 

Gastrointestinal bleeding 2 0.53 0.48 0.303 No 

Shock 2 0.43 0.40 0.312 No 

Pulmonary failure 7 1.14 0.63 0.081 No 

Unplanned extubation 3 -0.92 0.07 0.000 No 

Thrombosis 4 0.20 0.15 0.203 No 

Medical patients 

Failure to rescue 3 0.05 0.10 0.612 No 

CPR 3 0.44 0.03 <.0001 No 

Falls 11 0.33 0.05 <.0001 Yes 

Urinary tract infection 9 1.61 0.34 <.0001 No 

Hospital acquired pneumonia 6 0.66 0.17 0.000 No 

Nosocomial infection 7 0.04 0.05 0.461 No 

Sepsis 6 -0.22 0.09 0.023 Yes 

Pressure ulcers 12 -1.06 0.32 0.002 No 

Gastrointestinal bleeding 2 0.18 0.23 0.458 No 

Shock 2 0.05 0.16 0.746 No 

Pulmonary failure 2 0.01 0.01 0.280 Yes 

Thrombosis 3 0.01 0.01 0.105 No 
70 

Figure 14. Relative risk of patient outcomes corresponding to an increase by 1 hour in RN hours/patient day 

(pooled analysis) 

Relative risk of outcomes

 .64 1 1.57

Outcomes (number of studies)

Relative risk of outcomes

(95% CI)

Sepsis (4) 1.00 (0.64, 1.57)

Surgical wound infection (2) 1.00 (0.98, 1.02)

Nosocomial Infection (2) 0.76 (0.69, 0.83)

Pulmonary failure (1) 1.00 (0.90, 1.10)

Pneumonia (4) 0.98 (0.87, 1.10)
71 

Figure 15. Relative risk of outcomes corresponding to an increase by 1 hour in RN hours/patient day (pooled 

analysis combined from reported and estimated hours) 

Relative risk of outcomes

.6 1 1.1

Outcomes (number of studies) Relative risk of outcomes

(95% CI)

ICUs

Hospital acquired pneumonia (3) 0.96 (0.93, 0.98)

Pulmonary failure (4) 0.89 (0.85, 0.94)

Unplanned extubation (5) 0.91 (0.88, 0.95)

Nosocomial infection (4) 0.96 (0.89, 1.03)

Complications (2) 0.98 (0.95, 1.00)

Medical complications (3) 0.96 (0.94, 0.98)

Sepsis (6) 0.98 (0.94, 1.02)

Medical patients

Urinary tract infection (6) 1.00 (0.97, 1.03)

Hospital acquired pneumonia (5) 0.99 (0.95, 1.03)

Failure to rescue (4) 0.99 (0.99, 0.99)

Pulmonary failure (2) 0.99 (0.99, 0.99)

Nosocomial infection (3) 0.99 (0.97, 1.01)

Thrombosis (2) 0.98 (0.98, 0.98)

Sepsis (5) 0.99 (0.84, 1.17)

Surgical patients

Failure to rescue (7) 0.99 (0.98, 0.99)

Unplanned extubation (5) 0.91 (0.88, 0.95)

Nosocomial infection (2) 0.73 (0.66, 0.81)

CPR (3) 0.96 (0.94, 0.98)

Medical complications (3) 0.96 (0.94, 0.98)
72 

Table 16. Patient outcomes rates (%) corresponding to an increase by 1 hour in LPN/LVN hours/patient day 

(pooled analysis) 

Outcomes Studies Difference in 

Outcome Rate,% 

Standard 

Error 

p Value for 

the 

Association 

Consistency 

Surgical patients 

Failure to rescue 2 2.68 1.22 0.05 Yes 

Urinary tract infection 3 6.63 0.60 <.0001 Yes 

Hospital acquired pneumonia 3 3.48 0.26 <.0001 Yes 

Nosocomial infection 1 -2.70 4.61 0.62 

Sepsis 2 1.81 0.27 <.0001 Yes 

Surgical wound infection 2 0.35 0.08 0.001 Yes 

Pressure ulcers 2 2.60 0.60 0.002 Yes 

Gastrointestinal bleeding 2 1.28 0.15 <.0001 Yes 

Shock 2 1.04 0.15 <.0001 Yes 

Pulmonary failure 3 3.31 0.31 <.0001 Yes 

Thrombosis 3 0.67 0.06 <.0001 Yes 

Medical patients 

Failure to rescue 2 1.25 0.89 0.19 Yes 

CPR 2 -0.26 0.02 <.0001 Yes 

Falls 3 -0.21 0.03 <.0001 Yes 

Urinary tract infection 3 0.78 0.40 0.06 No 

Hospital acquired pneumonia 3 0.81 0.28 0.01 No 

Sepsis 2 -0.29 0.12 0.04 Yes 

Pressure ulcers 7 -2.53 0.28 <.0001 No 

Gastrointestinal bleeding 2 0.56 0.11 0.001 No 

Shock 2 0.35 0.10 0.01 Yes 

Pulmonary failure 1 -0.26 0.06 0.002 

Thrombosis 2 0.24 0.04 0.000 Yes 
73 

Figure 16. Patient outcomes rates (%) corresponding to an increase by 1 hour in UAP hours/patient day 

(pooled analysis) 

Difference in outcome rate

-5 0 .5

Outcome (number of studies)

Difference in outcome rate

(95% CI)

CPR (1) -0.23 (-0.30,-0.16)

Falls (6) -0.20 (-0.26,-0.14)

Urinary tract infection (5) -1.26 (-2.36,-0.16)

Hospital acquired pneumonia (3) -0.23 (-0.87, 0.41)

Nosocomial infection (3) -0.42 (-1.59, 0.75)

Sepsis (3) -0.38 (-0.78, 0.03)

Surgical wound infection (2) -0.07 (-0.15,-0.00)

Pressure ulcers (7) -2.07 (-3.26,-0.88)

Shock (1) -0.20 (-0.46, 0.05)

Pulmonary failure (2) -0.20 (-0.44, 0.03)

Thrombosis (1) 0.09 (-0.03, 0.20)
74 

Figure 17. Changes in LOS corresponding to an increase by 1 nursing hour/patient day (pooled analysis) 

Difference in length of stay (days)

-3.5 0 5.5

Level of analysis (number of studies) Difference in length of stay (days)

(95% CI)

All studies

1 nurse hour (8) -1.43 (-2.25, 0.61)

1 RN hour (5) 0.57 (-1.48, 2.62)

1 LPN hour (3) 3.21 (1.88, 4.53)

1 UAP hour (3) 1.53 (0.93, 2.13)

Medical patients

1 nurse hour (7) -0.45 (-0.72, 0.19)

1 RN hour (5) -0.31 (-0.87, 0.25)

1 UAP hour (3) 1.60 (0.97, 2.23)

Surgical patients

1 nurse hour (5) -2.36 (-3.39, 1.34)

1 RN hour (2) 1.65 (-1.73, 5.04)

1 LPN hour (2) 4.56 (3.61, 5.50)

1 UAP hour (1) 1.47 (0.47, 2.47)
75 

Table 17. Differences in outcomes rates (%) in quartiles of total nursing hours/patient day distribution 

(pooled analysis) 

Quartiles Outcomes Difference 

in Rate, % 

Standard 

Error 

p Value for the 

Association Consistency 

ICUs 

1 vs. 2 Falls 0.76 0.22 0.02 Yes 

1 vs. 3 Falls 0.59 0.10 0.002 

1 vs. 2 Nosocomial infection 7.24 1.97 0.01 No 

2 vs. 3 Pressure ulcers 1.13 7.33 0.89 No 

Surgical patients 

2 vs. 3 Failure to rescue 3.22 0.68 0.001 Yes 

2 vs. 3 Surgical wound infection 0.29 0.05 0.00 Yes 

2 vs. 3 Gastrointestinal bleeding 0.81 0.19 0.002 Yes 

2 vs. 3 Shock 0.68 0.16 0.001 Yes 

2 vs. 3 Pulmonary failure 2.17 0.50 0.001 Yes 

2 vs. 3 Thrombosis 0.42 0.10 0.002 Yes 

2 vs. 3 Falls 0.36 1.51 0.83 Yes 

2 vs. 3 Urinary tract infection 4.10 0.85 0.000 Yes 

0 vs. 2 Hospital acquired pneumonia 4.39 97.60 0.97 Yes 

2 vs. 3 Hospital acquired pneumonia 2.01 0.53 0.003 

2 vs. 3 Sepsis 1.30 0.24 0.000 Yes 

2 vs. 3 Pressure ulcers 2.31 0.31 <.0001 Yes 

Medical patients 

2 vs. 3 Gastrointestinal bleeding 0.51 0.06 <.0001 Yes 

2 vs. 3 Shock 0.36 0.04 <.0001 Yes 

2 vs. 3 Thrombosis 0.17 0.03 0.000 Yes 

1 vs. 3 Falls 7.62 1.55 <.0001 No 

2 vs. 3 Falls 5.90 1.63 0.001 

2 vs. 3 Urinary tract infection 2.49 0.19 <.0001 Yes 

2 vs. 3 Hospital acquired pneumonia 1.35 0.15 <.0001 Yes 

The following table shows how quartiles of nurse hours were established. 

Quartiles ICU Surgical Patients Medical Patients 

0 <6.32 <5.1 <5.6 

1 8.3 6.2 7.0 

2 12.1 9.5 9.6 

3 >14.6 >11.37 >10.75 
76 

Figure 18. Relative risk of patient outcomes in quartiles of RN hours/patient day (pooled analysis of RN 

hours reported by the authors and estimated from RN ratios) 

The following table shows how quartiles of nurse hours were established. 

Quartiles ICU Surgical Patients Medical Patients 

0 <6 <4.2 <4 

1 8.2 5.4 4.9 

2 12.9 8.4 6.9 

3 >16 >10.1 >8.1 

Relative risk of outcome

.7 1 5

Quartiles of RN hours/patient day

Relative risk of outcome

(95% CI)

CPR

0 vs. 2 (ICUs) 1.34 (1.20, 1.50)

1 vs. 3 (ICUs) 1.52 (1.36, 1.71)

1 vs. 3 (surgical patients) 1.27 (1.12, 1.43)

2 vs. 3 (surgical patients) 1.66 (1.49, 1.85)

Failure to rescue

0 vs. 2 (surgical patients) 1.39 (1.14, 1.69)

0 vs. 3 (surgical patients) 1.49 (1.32, 1.69)

0 vs. 3 (medical patients) 1.08 (1.07, 1.10)

2 vs. 3 (medical patients) 1.09 (1.06, 1.11)

Pulmonary failure

0 vs. 2 (ICUs) 2.33 (1.16, 4.68)

0 vs. 3 (ICUs) 2.75 (1.46, 5.21)

Thrombosis

2 vs. 3 (medical patients) 1.19 (1.17, 1.21)

Unplanned extubation

0 vs. 1 (ICUs) 1.72 (1.25, 2.37)

0 vs. 2 (ICUs) 2.32 (1.62, 3.32)

0 vs. 3 (ICUs) 3.12 (1.97, 4.96)

1 vs. 2 (surgical patients) 1.59 (1.15, 2.21)

1 vs. 3 (surgical patients) 2.57 (1.82, 3.62)
77 

Figure 19. Patient outcome rates corresponding to an increase in nurses’ education and experience (results 

from individual studies)

Difference in outcome rate

-5 0 5

Outcomes (units)

Difference in outcome rate

(95% CI)

1 year increase in experience

Pressure ulcers (medical-surgical) -1.74 (-4.87, 1.38)

Falls (combined) 0.17 (0.00, 0.33)

Falls (medical-surgical) 0.53 (-3.61, 4.67)

Complications (ICU) -1.13 (-1.90,-0.36)

Urinary tract infection (medical-surgical) 0.44 (-1.42, 2.31)

1% increase in nurses with BSN

Pressure ulcers (medical-surgical) 1.74 (-1.38, 4.87)

Failure to rescue (ICU) -0.04 (-0.06,-0.02)

Falls (combined) 0.04 (0.02, 0.07)

Falls (medical-surgical) -0.53 (-4.67, 3.61)

Complications (ICU) 0.04 (-0.02, 0.10)

Urinary tract infection (medical-surgical) -0.44 (-2.31, 1.42)
78 

Table 18. The distribution of nurse skill and experience mix, nurse education, and proportion of temporary 

and full-time nurse hours 

Number 

of Studies Mean Standard Deviation Median 

% RN 48 69.4 17.1 71.0 

% licensed nurses 8 81.1 7.5 86.0 

% of nurses with BSN 9 39.7 17.9 41.1 

Experience in years 12 10.1 2.8 10.0 

% overtime hours 2 11.7 6.5 15.8 

% temporary nurses 12 16.2 12.6 13.0 

% full-time nurses 3 78.0 11.3 78.0 
79 

Table 19. Calculated changes in rates of patient outcomes corresponding to an increase by 1% in the 

proportion of RNs 

Author, 

Analytic Unit Hospital Unit Patients Outcome Difference in Rate, % 95% CI 

Hospital 

Krakauer191 Combined Medical Mortality -0.095 -0.13; -0.06 

Hartz190 Combined Medical Mortality -0.387 -0.58; -0.19 

Hospital and Patient 

Cho28 Combined Medical Mortality 0.085 -0.03; 0.20 

Aiken52 Combined Medical Mortality -0.001 -0.001; -0.001 

Tourangeau140 Combined Medical Mortality -0.086 -0.16; -0.01 

Cho28 Combined Surgical Surgical wound 

infection 

0.057 -0.01; 0.13 

Cho28 Combined Medical Urinary tract infection 0.107 0.09; 0.12 

Cho28 Combined Medical Pneumonia -0.017 -0.02; -0.02 

Cho28 Combined Medical Pressure ulcers -0.024 -0.04; -0.004 

Cho28 Combined Medical Falls -0.001 -0.02; 0.02 

Hospital and unit 

Needleman26 Combined Medical and surgical Sepsis 0.065 -0.22; 0.35 

Patient 

Unruh33 Combined Combined Mortality 0.039 0.04; 0.04 

Unruh33 Combined Combined Pulmonary failure 0.009 0.007; 0.01 

Unruh33 Combined Combined Cardiopulmonary 

resuscitation 

0.008 0.01; 0.01 

Hope22 Medical and 

surgical 

Medical and surgical Nosocomial infection 0.000 -0.01; 0.01 

Hope22 Medical and 

surgical 

Medical and surgical Urinary tract infection 0.082 -0.06; 0.22 

Simmonds192 Specialized Medical Nosocomial infection -0.546 -1.28; 0.20 

Unruh33 Combined Surgical Surgical wound 

infection 

0.004 0.004; 0.004 

Unruh33 Combined Combined Pneumonia 0.019 0.02; 0.02 

Unruh33 Combined Combined Urinary tract infection 0.051 0.02; 0.08 

Zidek36 Combined Medical Pressure ulcers 0.015 -0.03; 0.06 

Zidek36 Combined Medical Falls 0.002 -0.08; 0.08 

Unruh33 Combined Combined Falls 0.007 0.001; 0.01 

Seago166 Combined Medical Pressure ulcers 0.027 -0.10; 0.16 

Seago166 Combined Medical Falls 0.020 -0.05; 0.09 

Seago154 Combined Medical Falls -0.047 -0.07; -0.02 

Unit 

Blegen29 Combined, 

ICU, 

specialized 

Medical and surgical Mortality -1.449 -3.4; 0.5 

Ritter-Teitel76 Medical and 

surgical 

Medical and surgical Urinary tract infection 0.124 -0.83; 1.07 

Stratton193 Combined, 

ICU, 

specialized 

Medical and surgical Nosocomial infection 0.033 0.02; 0.05 

Blegen29 Combined, 

ICU, 

specialized 

Medical and surgical Nosocomial infection -6.302 -8.16; -4.44 

Ritter-Teitel76 Medical and 

surgical 

Medical and surgical Pressure ulcers -0.111 -0.94; 0.72 

Ritter-Teitel76 Medical and 

surgical 

Medical and surgical Falls 0.006 -0.24; 0.25 

Blegen29 Combined, 

ICU, 

specialized 

Medical and surgical Pressure ulcers -5.308 -6.32; -4.29 
Table 19. Calculated changes in rates of patient outcomes corresponding to an increase by 1% in the 

proportion of RNs (continued) 

80 

Author, 

Analytic Unit Hospital Unit Patients Outcome Difference 

in Rate, % 95% CI 

Blegen29 Combined, 

ICU, 

specialized 

Medical and surgical Falls -0.015 -0.51; 0.48 

Potter75 ICU Medical Falls -0.048 -0.12; 0.06 

Donaldson64 Step-down, 

Medical and 

surgical units 

Medical and surgical Pressure ulcers 0.121 -0.13; 0.37 

Donaldson64 Step-down, 

Medical and 

surgical units 

Medical and surgical Falls -0.059 -0.17; 0.01 
81 

Figure 20. Calculated changes in rates of patient outcomes corresponding to an increase by 1% in the 

proportion of RNs (pooled analysis) 

 

*consistent across the studies (heterogeneity NS)

Difference in outcome rate

-.49 0 .49

Outcomes (number of studies) Difference in outcome rate

(95% CI) ICUs

Falls (3) -0.03 (-0.04,-0.03)

Nosocomial infection (3) 0.01 (-0.19, 0.21)

*Sepsis (2) 0.08 (-0.33, 0.49)

*Pressure ulcers (3) -0.14 (-0.39, 0.12)

Medical patients

CPR (2) 0.01 (0.01, 0.01) Falls (10) 0.01 (0.01, 0.01) Urinary tract infection (8) 0.02 (0.01, 0.03) Hospital acquired pneumonia (6) 0.02 (0.02, 0.02) Nosocomial infection (7) 0.03 (0.02, 0.04) Sepsis (4) 0.05 (0.03, 0.06)

Pressure ulcers (11) -0.01 (-0.03, 0.01)

Surgical patients

*Urinary tract infection (6) 0.06 (0.05, 0.07)

*Hospital acquired pneumonia (4) 0.02 (0.02, 0.03)

Nosocomial infection (2) -0.01 (-0.07, 0.05)

Sepsis (2) 0.10 (0.06, 0.13)

Surgical wound infection (2) 0.02 (0.02, 0.02)

*Pressure ulcers (3) 0.10 (0.05, 0.15)
82 

Figure 21. Relative risk of patient outcomes corresponding to an increase by 1% in the proportion of RNs 

(pooled analysis) 

Relative risk of outcome

.8 1 1.2

Outcomes (number of studies)

Relative risk of outcome

(95% CI)

All studies

Hospital acquired pneumonia (7) 1.00 (0.98, 1.02)

Falls (2) 1.00 (1.00, 1.00)

Pulmonary Failure (2) 1.00 (0.97, 1.03)

Nosocomial infection (2) 1.00 (1.00, 1.00)

Sepsis (3) 1.00 (0.85, 1.18)

Medical patients

Urinary tract infection (4) 1.00 (0.99, 1.02)

Hospital acquired pneumonia (5) 1.01 (1.00, 1.01)

Falls (2) 1.00 (1.00, 1.00)

Nosocomial infection (2) 1.00 (1.00, 1.00)

Surgical patients

Surgical wound infection (3) 1.00 (0.63, 1.58)
83 

Figure 22. Relative risk of hospital related mortality and failure to rescue corresponding to an increase by 

1% in the proportion of RNs (results from individual studies and pooled estimates) 

Relative risk of outcome

 .13 1 3

Author (patients) Relative risk of outcome

(95% CI) Failure to rescue

Needleman (surgical) 0.73 (0.49, 1.09)

Needleman (medical) 0.85 (0.70, 1.03)

Needleman (surgical) 0.64 (0.44, 0.92)

Needleman (medical) 0.85 (0.70, 1.04)

Needleman (surgical) 0.69 (0.45, 1.06)

Needleman (medical) 0.63 (0.47, 0.84)

Needleman (medical) 0.70 (0.54, 0.90)

Needleman (surgical) 0.36 (0.14, 0.89)

Needleman (surgical) 0.44 (0.20, 0.96)

Subtotal 0.73 (0.65, 0.83)

Mortality

Shortell (combined) 0.73 (0.48, 1.10)

Hoover (combined) 0.99 (0.99, 1.00)

Needleman (combined) 0.99 (0.67, 1.47)

Person (medical) 1.00 (1.00, 1.00)

Estabrooks (medical) 0.99 (0.98, 1.00)

Needleman (medical) 0.87 (0.71, 1.05)

Needleman (surgical) 0.96 (0.68, 1.35)

Needleman (medical) 0.84 (0.71, 1.01)

Needleman (surgical) 1.02 (0.70, 1.48)

Needleman (medical, California hospitals) 0.59 (0.45, 0.78)

Needleman (medical, California hospitals) 0.60 (0.46, 0.78)

Needleman (surgical, California hospitals) 1.29 (0.74, 2.26)

Needleman (surgical, California hospitals) 1.69 (1.02, 2.81)

Subtotal 0.98 (0.96, 1.00)
84 

Figure 23. Relative risk of patient outcomes corresponding to an increase by 1% in the proportion of RNs 

(results from individual studies and pooled estimates) 

 Relative risk of outcome

 .03 1 2

Author (patients)

Relative risk of outcome

(95% CI)

Pulmonary failure

Needleman (surgical) 1.00 (0.98, 1.02)

Needleman (surgical) 0.94 (0.56, 1.56)

Needleman (surgical) 0.76 (0.43, 1.34)

Needleman (surgical) 0.81 (0.41, 1.60)

Needleman (surgical) 0.86 (0.46, 1.59)

Subtotal 1.00 (0.98, 1.02)

Shock

Needleman (medical) 0.84 (0.71, 0.99)

Needleman (surgical) 1.08 (0.60, 1.96)

Needleman (medical) 0.52 (0.31, 0.89)

Needleman (surgical) 0.36 (0.14, 0.93)

Needleman (medical) 0.30 (0.12, 0.72)

Needleman (medical) 0.34 (0.16, 0.75)

Needleman (surgical) 0.14 (0.05, 0.43)

Needleman (surgical) 0.17 (0.06, 0.47)

Needleman (combined) 0.38 (0.21, 0.68)

Subtotal 0.43 (0.28, 0.65)
85

Figure 24. Relative risk of treatment complications corresponding to an increase by 1% in the proportion of RNs (results from pooled estimates) 

Relative risk of outcomes

 .02 10.1

Author (patients) Effect size (95% CI) Complications Needleman (surgical) 3.06 (0.94, 10.03) Needleman (surgical) 1.68 (0.66, 4.27) Needleman (medical) 0.68 (0.29, 1.58) Needleman (medical) 0.74 (0.32, 1.68)

 Needleman (surgical) 0.57 (0.17, 1.91) Needleman (surgical) 0.71 (0.20, 2.48)

Falls

Cho (combined) 1.00 (0.98, 1.02)

Upper gastrointestinal bleeding

Needleman (combined)) 0.28 (0.08, 0.96) Needleman (medical) 0.60 (0.36, 0.97)

Needleman (surgical) 0.45 (0.18, 1.11) Needleman (medical) 0.81 (0.58, 1.12) Needleman (surgical) 0.27 (0.09, 0.78)

Needleman (medical) 0.89 (0.52, 1.53) Needleman (medical) 0.93 (0.56, 1.55) Needleman (surgical) 0.02 (0.00, 0.51) Needleman (surgical) 0.04 (0.00, 0.64)

Pressure ulcers

Needleman (combined) 0.06 (0.00, 1.71) Needleman (surgical) 0.44 (0.23, 0.86) Needleman (medical) 0.27 (0.09, 0.83) Needleman (medical) 0.65 (0.36, 1.17)

Needleman (surgical) 0.01 (0.00, 0.29) Needleman (surgical) 0.00 (0.00, 0.11)

Thrombosis

Needleman (medical) 1.05 (0.64, 1.71) Needleman (surgical) 1.39 (0.66, 2.91) Needleman (medical) 0.78 (0.39, 1.57) Needleman (medical) 0.75 (0.40, 1.40) Needleman (surgical) 1.55 (0.51, 4.76) Needleman (surgical) 1.87 (0.69, 5.04)

1
86 

Table 20. Relative risk of patient outcomes corresponding to an increase by 1% in licensed nurse hours 

Outcomes Relative Risk 95% CI 

Author (patients) 

Failure to rescue 

Needleman27 (medical) 0.81 0.66; 1.00 

Needleman27 (surgical) 0.73 0.49; 1.09 

Needleman27 (medical) 0.90 0.80; 1.01 

Needleman27 (surgical) 0.82 0.70; 0.96 

Needleman27 (medical) 0.58 0.40; 0.86 

Needleman27 (medical) 0.69 0.50; 0.95 

Needleman27 (surgical) 0.45 0.22; 0.92 

Needleman27 (surgical) 0.54 0.30; 0.99 

Needleman27 (medical) 0.80 0.64; 0.97 

Needleman27 (surgical) 0.81 0.68; 0.94 

Needleman27 (surgical) 0.70 0.37; 1.03 

Needleman27 (surgical) 0.72 0.42; 1.01 

Needleman7

 (medical) 0.90 0.80; 1.00 

Needleman27 (medical) 0.81 0.64; 0.99 

Needleman27 (medical) 0.81 0.66; 1.00 

Cheung63 (medical) 1.00 1.00; 1.00 

Mortality 

Berney30 (surgical) 0.97 0.95; 0.98 

Needleman27 (medical) 0.90 0.74; 1.09 

Needleman27 (surgical) 0.99 0.67; 1.47 

Needleman27 (medical) 0.98 0.90; 1.08 

Needleman27 (surgical) 0.88 0.75; 1.03 

Needleman27 (medical) 0.91 0.65; 1.27 

Needleman27 (medical) 0.89 0.68; 1.16 

Needleman27 (surgical) 0.76 0.34; 1.69 

Needleman27 (surgical) 0.87 0.47; 1.61 

Needleman27 (medical) 0.90 0.74; 1.09 

CPR 

Needleman27 (surgical) 0.59 0.42; 0.76 

Needleman27 (surgical) 0.42 0.10; 0.74 

Needleman27 (surgical) 0.60 0.19; 1.00 

Needleman27 (medical) 0.66 0.48; 0.85 

Needleman27 (medical) 0.40 0.18; 0.63 

Pulmonary failure 

Needleman27 (surgical) 1.10 0.63; 1.92 

Needleman27 (surgical) 1.21 0.99; 1.47 

Needleman27 (surgical) 1.00 0.39; 2.60 

Needleman27 (surgical) 1.02 0.45; 2.32 

Shock 

Needleman27 (medical) 0.46 0.27; 0.81 

Needleman27 (surgical) 0.54 0.28; 1.04 

Needleman27 (medical) 0.66 0.50; 0.87 

Needleman27 (surgical) 0.59 0.44; 0.78 

Needleman27 (medical) 0.20 0.08; 0.53 

Needleman27 (medical) 0.40 0.19; 0.86 

Needleman27 (surgical) 0.22 0.09; 0.57 

Needleman27 (surgical) 0.27 0.12; 0.61 

Needleman27 (medical) 0.49 0.21; 0.77 

Needleman27 (surgical) 0.59 0.42; 0.76 

Needleman27 (surgical) 0.42 0.10; 0.74 

Needleman27 (surgical) 0.60 0.19; 1.00 

Needleman27 (medical) 0.66 0.48; 0.85 

Needleman27 (medical) 0.40 0.18; 0.63 

Needleman27 (medical) 0.46 0.27; 0.81 
Table 20. Relative risk of patient outcomes corresponding to an increase by 1% in licensed nurse hours 

(continued) 

87 

Outcomes Relative Risk 95% CI 

Nosocomial Infection 

Cheung63 (medical) 1.00 1.00; 1.00 

Pneumonia 

Needleman27 (medical) 0.60 0.44; 0.80 

Needleman27 (surgical) 0.56 0.31; 1.01 

Needleman27 (medical) 0.83 0.71; 0.98 

Needleman27 (surgical) 0.94 0.76; 1.16 

Needleman27 (medical) 0.52 0.32; 0.87 

Needleman27 (medical) 0.69 0.47; 1.03 

Needleman27 (surgical) 0.66 0.26; 1.69 

Needleman27 (surgical) 0.79 0.37; 1.71 

Needleman27 (medical) 0.61 0.42; 0.79 

Needleman27 (surgical) 0.94 0.74; 1.13 

Needleman27 (surgical) 0.36 0.12; 0.59 

Needleman27 (surgical) 0.52 0.20; 0.84 

Needleman27 (medical) 0.83 0.70; 0.96 

Needleman27 (medical) 0.59 0.39; 0.78 

Needleman27 (medical) 0.59 0.44; 0.80 

Surgical wound infection 

Needleman27 (surgical) 1.91 1.34; 2.48 

Needleman27 (surgical) 0.93 0.24; 1.62 

Needleman27 (surgical) 1.33 0.53; 2.13 

Sepsis 

Needleman27 (medical) 1.39 0.85; 1.94 

Needleman27 (surgical) 1.10 0.85; 1.35 

Needleman27 (surgical) 0.86 0.30; 1.42 

Needleman27 (surgical) 1.11 0.47; 1.74 

Needleman27 (medical) 1.24 0.97; 1.51 

Needleman27 (medical) 1.11 0.65; 1.56 

Needleman27 (medical) 1.01 1.00; 1.01 

Berney30 (surgical) 1.01 1.00; 1.01 

Urinary tract infection 

Needleman27 (medical) 0.48 0.38; 0.61 

Needleman27 (surgical) 0.67 0.46; 0.98 

Needleman27 (medical) 0.77 0.68; 0.86 

Needleman27 (surgical) 0.89 0.75; 1.07 

Needleman27 (medical) 0.44 0.28; 0.70 

Needleman27 (medical) 0.60 0.41; 0.87 

Needleman27 (surgical) 0.64 0.30; 1.37 

Needleman27 (medical) 0.49 0.37 0.61 

Needleman27 (surgical) 0.88 0.71; 1.04 

Needleman27 (surgical) 0.68 0.40; 0.95 

Needleman27 (surgical) 0.59 0.36; 0.82 

Needleman27 (medical) 0.76 0.67; 0.85 

Needleman27 (medical) 0.54 0.41; 0.66 

Needleman27 (medical) 0.48 0.38; 0.61 

Berney30 (medical) 1.00 0.99; 1.00 

Berney30 (surgical) 1.00 0.99; 1.00 

Complications 

Needleman27 (surgical) 2.43 1.00; 5.93 

Needleman27 (medical) 1.86 1.32; 2.62 

Needleman27 (surgical) 1.62 1.02; 2.56 

Needleman27 (medical) 1.44 0.39; 5.32 

Needleman27 (medical) 1.04 0.32; 3.35 

Needleman27 (surgical) 4.13 0.53; 32.25 

Needleman27 (surgical) 1.83 0.32; 10.49 
Table 20. Relative risk of patient outcomes corresponding to an increase by 1% in licensed nurse hours 

(continued) 

88 

Outcomes Relative Risk 95% CI 

Gastrointestinal bleeding 

Needleman27 (medical) 0.66 0.46; 0.96 

Needleman27 (surgical) 0.57 0.28; 1.15 

Needleman27 (medical) 0.96 0.79; 1.16 

Needleman27 (surgical) 0.78 0.59; 1.03 

Needleman27 (medical) 0.83 0.40; 1.72 

Needleman27 (medical) 0.87 0.48; 1.58 

Needleman27 (surgical) 0.72 0.22; 2.37 

Needleman27 (surgical) 0.63 0.23; 1.71 

Needleman27 (surgical) 0.77 0.56; 0.98 

Needleman27 (surgical) 0.40 0.07; 0.74 

Needleman27 (surgical) 0.53 0.15; 0.90 

Needleman27 (medical) 0.96 0.77; 1.15 

Needleman27 (medical) 0.68 0.42; 0.95 

Needleman27 (medical) 0.66 0.45; 0.96 

Berney30 (medical) 1.00 1.00; 1.01 

Berney30 (surgical) 1.01 1.00; 1.01 

Pressure ulcers 

Cheung63 (medical) 1.00 1.00; 1.00 

Needleman27 (medical) 0.73 0.49; 1.08 

Needleman27 (surgical) 1.38 0.69; 2.78 

Needleman27 (surgical) 0.94 0.74; 1.19 

Needleman27 (medical) 0.35 0.15; 0.79 

Needleman27 (medical) 0.55 0.28; 1.06 

Needleman27 (surgical) 0.68 0.18; 2.52 

Needleman27 (surgical) 0.71 0.26; 1.94 

Needleman27 (medical) 0.77 0.46; 1.07 

Needleman27 (surgical) 0.90 0.68; 1.12 

Needleman27 (surgical) 0.81 0.14; 1.49 

Needleman27 (surgical) 0.83 0.24; 1.41 

Needleman27 (medical) 0.89 0.70; 1.09 

Needleman27 (medical) 0.71 0.40; 1.02 

Thrombosis 

Needleman277 (medical) 1.39 0.92; 2.11 

Needleman27 (surgical) 1.29 0.66; 2.54 

Needleman27 (medical) 1.28 1.02; 1.60 

Needleman27 (surgical) 1.52 1.12; 2.07 

Needleman27 (medical) 1.97 0.84; 4.58 

Needleman27 (Medical) 1.55 0.78; 3.07 

Needleman27 (surgical) 0.03 0.00; 0.66 

Needleman27 (surgical) 1.11 1.04; 1.18 
89 

Figure 25. Relative risk of hospital related mortality and failure to rescue corresponding to an increase 

by 1% in the proportion of licensed nurses 

Patient populations are in parentheses

Relative risk of outcome

 .2 1 2

Author (patients) Relative risk of outcome

(95% CI) Failure to rescue

Needleman (medical) 0.81 (0.66, 1.00)

Needleman (surgical) 0.73 (0.49, 1.09)

Needleman (medical) 0.90 (0.80, 1.01)

Needleman (surgical) 0.82 (0.70, 0.96)

Needleman (medical) 0.58 (0.40, 0.86)

Needleman (medical) 0.69 (0.50, 0.95)

Needleman (surgical) 0.45 (0.22, 0.92)

Needleman (surgical) 0.54 (0.30, 0.99)

Needleman (medical) 0.80 (0.64, 0.97)

Needleman (surgical) 0.81 (0.68, 0.94)

Needleman (surgical) 0.70 (0.37, 1.03)

Needleman (surgical) 0.71 (0.42, 1.01)

Needleman (medical) 0.90 (0.80, 1.00)

Needleman (medical) 0.81 (0.64, 0.99)

Needleman (medical) 0.81 (0.66, 1.00)

Cheung (medical) 1.00 (1.00, 1.00)

Subtotal 0.83 (0.78, 0.87)

Mortality

Berney (surgical) 0.97 (0.95, 0.98)

Needleman (medical) 0.90 (0.74, 1.09)

Needleman (surgical) 0.99 (0.67, 1.47)

Needleman (medical) 0.98 (0.89, 1.08)

Needleman (surgical) 0.88 (0.75, 1.03)

Needleman (medical) 0.91 (0.65, 1.27)

Needleman (medical) 0.89 (0.68, 1.16)

Needleman (surgical) 0.76 (0.34, 1.69)

Needleman (surgical) 0.86 (0.46, 1.61)

Needleman (medical) 0.90 (0.74, 1.09)

Subtotal 0.96 (0.95, 0.98)
90 

Figure 26. Relative risk of patient outcomes corresponding to an increase by 1% in the proportion of 

licensed nurses 

Patient populations are in parentheses 

Relative risk of outcome

1 1 3

Author (patients) Relative risk of outcome

(95% CI) CPR

Needleman (surgical) 0.59 (0.42, 0.76)

Needleman (surgical) 0.42 (0.10, 0.74)

Needleman (surgical) 0.59 (0.19, 1.00)

Needleman (medical) 0.66 (0.48, 0.85)

0.40 (0.18, 0.63)

Subtotal 0.59 (0.49, 0.71)

Pulmonary failure

Needleman (surgical) 1.10 (0.63, 1.92)

Needleman (surgical) 1.21 (0.99, 1.47)

Needleman (surgical) 1.00 (0.39, 2.60)

Needleman (surgical) 1.02 (0.45, 2.32)

Subtotal 1.18 (0.98, 1.41)

Shock

Needleman (medical) 0.46 (0.27, 0.81)

Needleman (surgical) 0.54 (0.28, 1.04)

Needleman (medical) 0.66 (0.50, 0.87)

Needleman (surgical) 0.59 (0.44, 0.78)

Needleman (medical) 0.20 (0.08, 0.53)

Needleman (medical) 0.40 (0.19, 0.86)

Needleman (surgical) 0.22 (0.09, 0.57)

Needleman (surgical) 0.27 (0.12, 0.61)

Needleman (medical) 0.49 (0.21, 0.77)

Needleman (surgical) 0.59 (0.42, 0.76)

Needleman (surgical) 0.42 (0.10, 0.74)

Needleman (surgical) 0.59 (0.19, 1.00)

Needleman (medical) 0.66 (0.48, 0.85)

Needleman (medical) 0.40 (0.18, 0.63)

Needleman (medical) 0.46 (0.27, 0.81)

Subtotal 0.53 (0.46, 0.61)
91

Chapter 4. Discussion

Association or Cause 

 The present review and meta-analysis confirm previous contentions that increased nurse 

staffing in hospitals is associated with better care outcomes.27,51,93 A persistent question is 

whether this association reflects a causal relationship. One test of such a causal relationship 

should be that higher staffing levels should produce stronger effects for nurse sensitive outcomes 

than for more general outcomes. The evidence across 14 studies consistently suggests that the 

risk of hospital related mortality was 9 percent lower in ICUs, 6 percent lower for medical 

patients, and 16 percent lower for surgical patients for each additional RN FTE per patient day 

(Figure 27). The risk of nurse-sensitive patient outcomes was comparable with those for 

mortality independent of study design. The relative risk of failure to rescue was reduced by 16 

percent in surgical patients and hospital-acquired pneumonia by 30 percent in ICUs, rates 

substantially higher than those for mortality. 

 Another test would be the difference in effect size between longitudinal and cross-sectional 

designs. The former should more directly reflect the effects of changing staffing patterns by 

holding more constant other hospital variables. Studies that attempted to assess temporality in the 

association between nurse staffing and failure to rescue had a lower relative risk per RN FTE per 

patient day ratio (RR 0.84, 95 percent CI 0.75-0.93) than did those using cross-sectional designs 

(RR 0.92, 95 percent CI 0.91-0.93), supporting the presence of an association rather than a cause. 

 We also examined the role of the study characteristics on the association between nurse ratios 

and patient outcomes. We tested the following study characteristics that could modify the 

association between nurse ratios and patient outcomes: quality scores, assessment of temporality 

in the association, analytic units, hospital units, patient populations, the adjustment for patient 

comorbidities, provider characteristic, and clustering of patients and hospitals. The authors 

adjusted for patient comorbidities at patient and hospital levels and for provider characteristics 

including hospital teaching and profit status, size and volume, technology index, HMO 

penetration, and staffing. We examined the association of four aspects of nurse ratios (total, RN, 

LPN/LVN, UAP) licensed and the same four for nursing hours with 16 outcomes expressed as 

rates and 19 expressed as relative risks for a total of 280 (eight effect modifiers times 35 

outcomes). Only a small proportion of tested models showed a significant influence of study 

design on the association with nurse staffing and patient outcomes (Appendix G∗

,Table G30). 

Among the possible interactions, only the LPN effects were significant more the 30 percent of 

the time. The proportion of significant interactions was considerably lower for relative risks. 

 Hospitals that invest in more nurses may also invest in other actions that improve quality. 

Empirical evidence suggests that magnet hospitals provide high quality care and report better 

patient outcomes in relation to nurse staffing.

10,52,57,198,199

 Several lines of evidence suggest that overall hospital commitment to a high quality of care 

in combination with effective nurse retention strategies leads to better patient outcomes, patient 

satisfaction with overall and nursing care, and nurse satisfaction with job and provided care.10,52-

54,57-59 Hospital volume,20 physician practice patterns, and collaboration with nurses8,9 may affect 

 

∗ Appendixes and Evidence Tables for this report are provided electronically at http://www.ahrq.gov/clinic/tp/nursesttp.htm
92

patient outcomes. Professional practice environments in hospitals, which enable nurses to control 

their practice through governance also contribute to nurses’ job satisfaction and positive 

perceptions of nurse autonomy. These factors are associated with nurse retention and better 

patient outcomes in several reports.15,21,78,152,161,164,165,200,201 Hospitals with better professional 

nurse practice environment had improved RN staffing ratios.55,56 Magnet hospitals had lower 

patients per RN ratios, better nurse manager ability and support, and collegial nurse-physician 

relations.53-57,152,202,203 The quality of the nurse professional practice work environment correlated 

with patient safety outcomes in several studies.15,21,66,164,201,204

 The outcomes of hospital care are the result of many factors. The studies reviewed here did 

not, and perhaps could not, address many salient issues. Patient outcomes are affected by patient 

characteristics. Case mix, when addressed, was usually handled as a mean number averaged 

across all patients in a unit or hospital. Such averages can hide a lot of different mixtures. 

Detailed information on comorbidities and disease severity was not included. Likewise, the 

nature of core medical treatments was not addressed. The absence of these measures can have 

varied effects depending on whether one believes they represent noise or bias. Case mix 

differences may hide areas where nurse staffing makes a bigger difference if it is not associated 

directly with staffing levels, but if it is, it could lead to bias. Such bias should result from more 

staff going to patients who need more care and hence would decrease the effects seen. These 

studies best approximate that correction by examining different types of units, which serve 

patients in varying levels of severity. 

 The absence of information on medical care is another important shortcoming of these 

studies, although it would greatly complicate the study designs. Here too, bias needs to be 

separated from noise. There is no strong basis to assume that the quality of medical care is 

necessarily correlated with the level of staffing, but it seems unlikely that it would be inversely 

correlated. With that assumption, any bias would result from hospitals that invested in more 

staffing also pressing for better medical care, an assumption that seems feasible. 

Marginal Effects 

 Previous systematic reviews did not estimate the effect size of different nurse staffing 

measures.92,93 Associations were considered to be clinically important when a 10 percent 

difference in staffing levels was associated with significant changes in outcomes.92 When 

attempting to find optimal nurse staffing ratio and hours, the effect size could not be estimated 

reliably because of differences in the studies and possible curvilinear associations.93 One study26

examined the overall linear trend in adverse events corresponding to a one unit increase in nurse 

staffing and differences in the rates of patient outcomes among the lowest and highest quartiles 

of the nurse staffing distribution to find an optimal staffing pattern.26 

 Hospital mortality shows a decline with increasing staffing, but the decline is not linear. The 

risk increases quickly as the patients per RN per shift ratio rises above four to five. The mean 

increase of 7 percent for each additional patient per RN per shift can be misleading; the goodness 

of fit of the linear slope varied across the distribution of nurse to patient ratio. The effect size of 

this nonlinear association was tested to detect the overall trend and relative and absolute changes 

in patient outcomes among nurse staffing categories using quartiles of the distribution. 

Comparing the lowest with the highest quartiles of patients per RN per shift ratio, the observed 

risk of mortality was 61 percent compared to expected 85 percent (1.61 observed vs. 1.85 

expected) if the slope was applied to the differences in the ratio. Moreover, we would expect the 
93

risk of mortality to be 19 percent lower when the workload of patients per RN per shift decreased 

from four to two patients, but in fact it was only 6 percent lower. 

 We used several ways to analyze strengths and limitations of the individual studies. 

Applicability of the study was estimated according to a sampling of eligible hospitals and 

patients with the highest applicability in studies with random population based sampling and 

random hospital-based sampling and the lowest in the studies with convenient and self-selected 

sampling. We analyzed the internal validity of the studies by the validation of measured nurse 

staffing, patient outcomes, and all confounding factors the authors reported. We graded the 

adjustment for patient characteristics (age, race, comorbidities, socioeconomic status), provider 

characteristics, and clustering of patients and clinics. We included summarized quality scores 

and the fact of adjustment for the each of confiding factors in the meta-regression and sensitivity 

analysis. We compared the direction and the strength of the association from the studies that used 

different definitions of nurse staffing and patient outcomes (rates and relative risk). We 

compared the direction and the strength of the association from the studies at patient level 

analysis that could carefully adjust for patient and nurses characteristics (better internal validity 

but lower applicability) and large multi-centers studies obtained hospital averages from 

administrative databases (low internal validity but better applicability). To examine statistically 

the influence of study quality on tested associations we compared pooled estimates weighted by 

the sample size and weighted by the quality of the studies and did not detect substantial 

differences. 

 Geographical variations in nurse distributions144 and rates of fatal adverse events148 may 

impact the effect size of nurse staffing on patient outcomes. Few multi-hospital studies used 

random effects models to incorporate geographical differences in the estimation;33,49,94 37 

percent of the included studies reported random sampling and assessments of sampling bias. We 

compared means of nurse staffing in the studies we included in the meta-analysis with published 

means26 and did not detect substantial differences. However, the report of the Institute of 

Medicine74 suggested that a larger proportion of hospitals have poorer nurse staffing than 

published in scientific research. Therefore, the effect size of nurse staffing on patient outcomes 

from the present report can be generalized only to hospitals with similar nurse staffing patterns. 

Nurse Staffing and Patient Outcomes in Hospitals 

 The majority of the studies found that hospitals with more RNs working with patients had a 

lower level of patient adverse events related to health care. If these associations were causal, 

Table 21 estimates the effect size in terms of the number of patient adverse events that could be 

avoided by adding 8 RN hours a patient receives during 24 hours in a hospital. Table 22 shows 

the proportion of patient adverse events that could theoretically be avoided by reducing the 

number of patients assigned to an RN during an 8-hour shift. 

Staffing Measures 

 Two general measures of nurse staffing were studied. One looks superficially at hours of care 

provided by different types of nursing staff averaging FTEs of different nurse categories at the 

hospital level,11,18,19 including only productive hours worked in direct care.28,61,62 The other relies 

on a less precise ratio of total nurse staffing to patient volume derived from administrative 

databases63-65 averaging annual nurse-to patient ratios20 at the hospital or unit level. The patients 
94

per RN per shift ratio was more frequently used and provided greater evidence of the effect, but 

both showed generally the same trends. Inconsistency in nurse staffing operational definitions 

and methods to measure with an unknown “gold standard” to assess staffing patterns at the 

patient levels may bias the results of the studies and consequently, pooled analysis.206 Because 

many of the studies of nurse staffing were based on administrative data, they expressed staffing 

levels in terms of RN FTEs per patient or similar measures. However, the individuals charged 

with actually managing staffing are more likely to think in terms of patients per nurse. A simple, 

back-of-the-envelope transformation would be that 1 RN FTE per patient day would translate to 

8 RN hours per patient day or three patients per RN per shift. If the average is 7.8 RN hours per 

patient day (~3 patients per RN per shift), then increasing staffing by 1 RN FTE per patient day 

would mean a decrease to 1.5 patients per nurse. 

 The effect size varied depending on the nurse staffing measure. The reduction in relative risk 

of hospital related mortality is 16 percent for 1 RN FTE per patient day and 1 percent for an 

additional RN hour per patient day in surgical patients. Assuming that every additional RN per 

FTE patient day would provide approximately 8 additional RN hours per patient day, the 

expected reduction should be more than observed in the studies that examined the risk of 

mortality in relation to nurse hours (Table 23). The comparison of the effect size on patient 

outcomes among quartiles of the RN FTE per patient day ratio and nurse hours per patient day 

detected the same pattern (Table 24); the maximal reduction in relative risk of hospital-related 

mortality and adverse events occurred when no more than two patients were assigned to an RN 

in ICUs and in surgical units, and more than 11 nurse hours were spent per one patient day in 

ICUs and more than 7-8 hours in surgical and medical patients. We did not find consistent 

evidence that a further increase in RN FTE per patient day ratio can provide better patient safety. 

Confirming the previous observations,29,93,139 we detected a curvilinear association between the 

RN FTE per patient day ratio and hospital related mortality, nosocomial and bloodstream 

infections, and hospital acquired pneumonia with the optimal association at 2-2.5 patients per 

RN per shift in ICUs and surgical patients. 

 The association between patient outcomes and different definitions of nurse staffing suggest 

several reasons why nurse hours do not always provide a valid estimation of nurse-to-patient 

ratios. Nurse hours per patient day reflect average staffing across a 24-hour period and do not 

reflect fluctuations in patient census, scheduling patterns during different shifts,9,13 and periods 

of the year.66,67 They do not account for the time nurses spend in meetings, educational activities, 

and administrative work. Therefore, “productive hours per patient day” may underestimate nurse 

staffing levels when a large proportion of worked hours was not spent on direct patient care.60,109

These reasons may help to explain why the effect size varied across nurse staffing measures. 

 The majority of studies reviewed in this report focused on registered nurses working in acute 

care hospital settings. Evidence on the association between LPN/LVN and UAP personnel is 

limited and controversial. The authors designed the studies to evaluate the effect of nurse staffing 

on patient outcomes sensitive to RN rather LPN/LVN and UAP work. Skill mix may not directly 

reflect the hospital’s commitment to quality of care and financial strategies. Future research 

should address the role of skill mix and the contributions of LPNs/LVNs, and UAPs on quality 

of care. 
95

Care Setting 

 Nurse staffing had a different effect in different care settings. The addition of one unit of 

nursing care may vary depending on the baseline rate. For example, ICUs have higher staffing 

levels than typical hospital units. The effect of an additional nurse hour might be quite dissimilar 

in that context. We evaluated differences in the association between nurse staffing variables and 

patient outcomes by the type of hospital units (ICU, surgical, medical, neonatal) and by the type 

of patients (medical vs. surgical).27 We found a greater reduction in the relative risk of hospitalrelated mortality (16 percent) in surgical patients for an additional one RN FTE per patient day 

compared to a reduction of 6 percent in medical patients. Given a higher baseline mortality in 

surgical patients, the reduction in nurse workload would save six surgical compared to five 

medical patients per 1,000 hospitalized. Consistent with previous studies,26,27 the present metaanalysis found consistent evidence that surgical patients would demonstrate a greater cost-benefit 

from improved nurse staffing. Increasing the care of surgical patients by one RN FTE per patient 

day would eliminate 16 percent of failure to rescue (26 saved lives per 1,000 hospitalized) 

compared with 9.2 percent in all patients (medical and surgical). Such consistent and large 

improvements in patient safety from increasing the RN FTE per patient day ratio in surgical 

patients and in ICUs suggest heath care administrators can improve quality of care in these 

categories of patients using optimal staffing ratios.207 

Other Factors 

 The primary independent variable examined here is the volume of nursing, tempered by some 

attention to the education level. But other factors may also be relevant. Numbers alone do not 

likely explain all that happens. A nurse is not necessarily a nurse.206 Skill, organization, and 

leadership undoubtedly play a role but are much more difficult to assess. Usually we work in just 

the opposite direction inferring skill from outcomes after other factors have been accounted for. 

Because these studies rarely include data on case mix and other factors that help to explain 

outcomes, they cannot be used to infer differences in skill levels. Included studies did not 

provide the information on the quality of medical and surgical treatment. The importance of 

nurses’ professional competence and performance have been discussed with regard to developing 

standards of nurse performance to encourage high quality of care.70-73

 There are also questions about the association between nurse experience and patient 

outcomes. The independent effects of individual nurse competence in interaction with nurse 

staffing are not well understood and were not the subject of the present review. However, 

implementing the results of the present review to improve the quality of hospital care, we need to 

remember that complex interventions in combination with nurse staffing strategies provided 

better patient benefits. 208-212 Implementing evidence-based clinical pathways that involve nurse 

and physician education and collaboration may increase the effectiveness of nursing work and 

improve patient outcomes.213,214 Several randomized clinical trials reported a significant 

improvement in nurse performance and patient outcomes as a result of quality improvement 

initiatives.215-224

The majority of studies focused on adverse patient events and mortality. However, the 

estimation of quality of care may include patient satisfaction with nursing and overall medical 

care and improved quality of life. Future research should address patient positive outcomes, 
96

compliance with prescribed treatments, patient functional status, and education in association 

with provided care including nurse staffing. 

Policy Implications 

 The case for causation has yet to be made. Nevertheless, if one accepts the results presented 

as suggesting a causal relationship between nurse staffing and outcomes, the next question is one 

of practicality. Possible staffing decisions to improve quality of care would involve comparing 

existing staffing with changes in staffing needed to achieve desirable patient outcomes. The 

effect sizes depend on rich staffing ratios, which are not feasible in most hospitals. Moreover, 

defining the best level of nurse staffing requires addressing cost-effectiveness analysis225 that 

was beyond the present report. Because hospitals are paid a fixed rate under diagnosis related 

groups (DRGs) that does not reflect the quality of care they provide, they are not in a position to 

assume substantial cost burdens. The estimation of the threshold in terms of marginal costs and 

benefits depends on value placed on survival, patient satisfaction, and quality of life (QOL).6

 Policymakers can consider several approaches to regulate nurse staffing. Our calculations 

suggest that it is difficult to set fixed nursing standards. Indeed, fixed minimum nurse-to patient 

ratios implemented in several states did not provide the expected patient safety benefits.226 To 

maintain a reasonable staffing level, the increasing nurse shortage may force hospitals to reduce 

capacity rather than increase staffing. Mandatory nurse to patient ratios without legislative 

agreement to increase reimbursement may result in administrative decisions to reduce support 

staff positions and investments to other quality initiatives.225 Patient acuity-based staffing 

requirements adjust staffing for patient diagnosis and comorbidities but do not regulate shift-to 

shift fluctuations in nurse staffing that have an important influence on quality of care. 175,205

Moreover, no consensus exists about patient classification systems, which are different among 

hospitals and states.113,227-230 Public disclosure of nurse staffing was introduced in one state,227

but its effect on quality of care is not known.226 Pay-for performance has been proposed to 

provide incentives for quality of care, but its effect on cost effectiveness is not well 

understood.226 Ideally we should monitor every hospital in the United States to see how 

differences in policies and financial performance affect the cost effectiveness of staffing and its 

effect on quality of health care.225,226

 Finally, the number of patients a nurse cares for is not a true measure of the “work” of the 

nurse. The patient flow (admissions, discharges, return from surgeries, transfers to other units, 

transfers from other units) can result in nurses providing care for many more patients in a day 

than what is reflected in the RN hour per patient day or nurse to patient ratio. This significant 

factor was not addressed in any of the studies reviewed and should be considered as a nurse 

staffing measure for future studies. Another factor not considered in the studies is the number 

and type of support personnel available to nurses to assist them with care of patients. A recent 

trend in hospitals is having Rapid Response Teams (RRTs). This team is usually comprised of an 

experienced critical care nurse, respiratory therapist, and a physician. The team can be called by 

any nurse in the hospital if the nurse assesses that the patient’s condition is changing such that it 

could potentially result in a negative outcome. Nurses also have access to consultation from 

advanced practice nurses, unit-based nurse educators, charge nurses, assistant nurse managers, 

and nurse managers. These types of nursing hours are not included in the studies or considered as 

nurse staffing measures. 
97

 In conclusion, the present review found consistent statistically and clinically significant 

associations between nurse staffing and adjusted relative risk of hospital related mortality, failure 

to rescue, and other patient outcomes sensitive to nursing care, but we cannot conclude these 

relationships are causal. Hence, they cannot be interpreted as a basis for recommending specific 

staffing levels. The effect size is greater in surgical patients and in ICUs. The associations may 

include other structure and process factors in causal pathway to patient effective and safe care. A 

commitment to a high quality care at hospital level may provide better patient outcomes in 

relation to nurse staffing. 

Strength of the Evidence 

 Taken as a whole, there is consistent evidence of an association between the level of nurse 

staffing and patient outcomes but no clear case for causation. The nature of the study designs 

precludes any efforts to establish a causal relationship. There are no interventions, let alone 

controlled trials. The effect on quality of other salient input, such as medical care, is not tested. 

Adjustments for case mix rely on averages across units or hospitals. The quality of the studies is 

modest by standard measures, and the coverage of salient variables that could affect quality is 

weak. The distinction is still far from clear. The association was somewhat stronger with nursesensitive outcomes than with more generic ones like mortality, but it was also stronger with 

cross-sectional rather than longitudinal designs. 

Recommendations for Future Research 

 While it is not feasible to think about research designs that might be more interventional, 

it may be possible to take advantage of natural experiments where nurse staffing levels are 

changed holding other factors constant. Future observational studies will need to take cognizance 

of the many other factors that can affect the outcomes of interest, especially medical care, patient 

characteristics, and the organization of nursing units and staffs. Larger multi-center studies will 

be needed. Nonetheless, it is unlikely that all the salient variables can be addressed in any one 

study. Future work will need to target specific questions and collect and analyze enough 

information to isolate the effects of nurse staffing levels. 
98 

Figure 27. Relative risk of outcomes corresponding to an increase by RN FTE/patient day consistent across 

the studies 

Relative risk of outcome

.25 9

Settings (number of studies)

Relative risk of outcome

(95% CI)

ICUs

Mortality (5) 0.91 (0.86, 0.96)

CPR (3) 0.72 (0.62, 0.84)

Pulmonary failure (4) 0.40 (0.27, 0.59)

Unplanned extubation (5) 0.49 (0.36, 0.67)

Hospital acquired pneumonia (3) 0.70 (0.56, 0.88)

Medical complications (3) 0.72 (0.60, 0.86)

Medical patients

Mortality (6) 0.94 (0.94, 0.95)

Surgical patients

Mortality (8) 0.84 (0.80, 0.88)

Failure to rescue (5) 0.84 (0.79, 0.90)
99 

Table 21. The number of patient adverse events that could be avoided by additional 8 RN hours a patient 

receives during 24 hours in a hospital 

Patients’ Condition Related to Health Care, 

Not to a Primary Diagnosis 

Number of Avoided Events/1,000 Hospitalized 

Patients (95% CI) 

All patients 

Mortality, overall 9 (6-12) 

Mortality, hospital level analysis 3 (2-4) 

Mortality, medical patients 5 (4-5) 

Hospital acquired pneumonia 5 (1-8) 

Failure to rescue 24 (14-34) 

CPR 2 (1-2) 

ICUs 

Mortality 5 (2-8) 

Hospital acquired pneumonia 7 (3-10) 

Pulmonary failure 7 (5-9) 

Unplanned extubation 6 (4-8) 

CPR 2 (1-2) 

Nosocomial Infection 10 (6-13) 

Surgical patients 

Mortality 6 (4-8) 

Failure to rescue 26 (17-35) 

Surgical wound infection 7 (1-8) 

CPR 1 (1-2) 
100 

Table 22. The proportion of patient adverse events (%) that could be avoided by reducing the number of 

patients assigned to an RN during an 8-hour shift 

Patients’ Conditions Related to 

Health Care, Not to a Primary 

Diagnosis 

Number of Patients 

Assigned to 1 RN 

During a Shift 

Percentage of Patient Adverse 

Events that Could be Avoided by 

Reducing the Number of Patients 

per RN (95% CI) 

ICUs 

Mortality <3 vs. 3-4 5.6 (3.4; 7.7) 

Sepsis <1.6 vs. 3.3 42.7 (8.8; 64.0) 

Sepsis 1 vs. 3.3 42.2 (6.0; 64.4) 

CPR <1.6 vs. 3.3 34.4 (26.7; 41.4) 

CPR 1 vs. 3.3 46.3 (39.2; 52.6) 

CPR 1 vs. >4 25.4 (16.7; 33.2) 

Medical complications <1.6 vs. 3.3 40.8 (28.6; 50.9) 

Medical complications 1 vs. 3.3 46.1 (33.6; 56.3) 

Medical complications 1 vs. >4 25.4 (10.1; 38.1) 

Pulmonary failure <1.6 vs. 3.3 60.0 (30.9; 76.9) 

Pulmonary failure <1.6 vs. 3 63.7 (31.3; 80.8) 

Pulmonary failure 1 vs. >4 57.1 (13.8; 78.6) 

Unplanned extubation <1.6 vs. 3.3 44.8 (22.2; 60.9) 

Unplanned extubation <1.6 vs. 3 68.0 (49.2; 79.8) 

Unplanned extubation 1 vs. 3 56.9 (38.2; 69.9) 

Unplanned extubation 3.3 vs. >4 42.0 (20.2; 57.9) 

Surgical patients 

Mortality ≤2 vs. 4-6 24.3 (17.9; 30.3) 

Mortality ≤2 vs. >6 38.4 (34.1; 42.4) 

Mortality 2-3.5 vs. 4-6 19.8 (13.3;25.9) 

Mortality 2-3.5 vs. >6 34.7 (30.4; 38.7) 

Mortality 4-6 vs. >6 18.6 (11.8; 24.8) 

Hospital acquired pneumonia 4 vs. >5 24.6 (5.2; 40.0) 

Nosocomial infection <2 vs. 3 93.6 (65.7; 98.8) 

Surgical wound infection 4 vs. >5 20.4 (6.5; 32.3) 

Sepsis <2 vs. 3 44.4 (16.4; 63.0) 

Sepsis <2 vs. >5 49.4 (8.8; 71.9) 

Sepsis 4 vs. >5 28.5 (6.6; 45.3) 

CPR <2 vs. 3 30.8 (13.1; 44.9) 

CPR <2 vs. 4 25.4 (5.0; 41.4) 

Failure to rescue <2 vs. 4 25.5 (17.1; 33.0) 

Failure to rescue <2 vs. >5 39.1 (33.6; 44.2) 

Failure to rescue 3 vs. 4 20.6 (12.2; 28.3) 

Failure to rescue 3 vs. >5 35.2 (29.7; 40.2) 

Failure to rescue 4 vs. >5 18.3 (9.1; 26.6) 

Pulmonary failure <2 vs. 3 61.9 (28.2; 79.7) 

Pulmonary failure <2 vs. 4 75.1 (45.4; 88.6) 

Unplanned extubation <2 vs. 3 44.3 (18.4; 62.0) 

Unplanned extubation <2 vs. 4 71.5 (53.8; 82.4) 

Unplanned extubation 3 vs. 4 48.7 (30.6; 62.1) 
101

Table 23. Relative risk of mortality and nurse sensitive patient outcomes corresponding to one unit increase in nurse staffing estimates) 

Outcome N Increment RR 95% CI N Increment RR 

Mortality 14 1 RN FTE/patient day 0.92 0.90; 0.94 1 1 nurse hour/patient day 

4 1 patient/LPN/shift 0.99 0.99; 1 7* 1 RN hour/patient day 1.01 1 patient/UAP/shift 0.99 0.99; 1.07 3 1 LPN hour/patient day 0.8

1 patient/licensed nurse 1 1 UAP hour/patient day 

1 1 licensed hour/patient day 

Length of stay 5 1 RN FTE/patient day 0.92 0.80; 1.05 4* 1 nurse hour/patient day 

1 1 patient/LPN/shift 0.98 0.97; 0.99 3 1 RN hour/patient day 1.0

1 patient/UAP/shift 2 1 LPN hour/patient day 1 patient/licensed nurse 1 1 UAP hour/patient day 

2 1 licensed hour/patient day 

Patient falls, injuries 1 1 RN FTE/patient day 2 1 nurse hour/patient day 

1 1 patient/LPN/shift 1 1 RN hour/patient day 

1 patient/UAP/shift 1 LPN hour/patient day 

1 1 patient/licensed nurse 1 UAP hour/patient day 

1 licensed hour/patient day 

Pressure ulcers 1 RN FTE/patient day 4 1 nurse hour/patient day 

1 patient/LPN/shift 1 1 RN hour/patient day 1 patient/UAP/shift 1 1 LPN hour/patient day 

1 1 patient/licensed nurse 1 1 UAP hour/patient day 

1 1 licensed hour/patient day 

Nosocomial infection rate 3 1 RN FTE/patient day 0.88 0.73; 1.06 5* 1 nurse hour/patient day 0.8

1 patient/LPN/shift 2* 1 RN hour/patient day 0.7

1 1 patient/UAP/shift 1 1 LPN hour/patient day 

1 patient/licensed nurse 1 1 UAP hour/patient day 

2 1 licensed hour/patient day 

Failure to rescue 6 1 RN FTE/patient day 0.91 0.89; 0.94 1 1 nurse hour/patient day 

1 patient/LPN/shift 3 1 RN hour/patient day 1 patient/UAP/shift 1 1 LPN hour/patient day 1 patient/licensed nurse 1 1 UAP hour/patient day 

2 1 licensed hour/patient day 

Urinary tract infection rate 2 1 RN FTE/patient day 1.02 0.94; 1.11 5 1 nurse hour/patient day 

1 1 patient/LPN/shift 0.96 0.94; 0.99 6 1 RN hour/patient day 1.0

1 patient/UAP/shift 4 1 LPN hour/patient day 1.0

1 1 patient/licensed nurse 1 1 UAP hour/patient day 

2 1 licensed hour/patient day 

Surgical bleeding 1 1 RN FTE/patient day 1.02 0.78; 1.34 4 1 nurse hour/patient day 

1 patient/LPN/shift 2 1 RN hour/patient day 1.01 patient/UAP/shift 1 1 LPN hour/patient day 0.91 patient/licensed nurse 1 1 UAP hour/patient day 

2 1 licensed hour/patient day 
Table 23. Relative risk of mortality and nurse sensitive patient outcomes corresponding to one unit increase in nurse staffing 

estimates) (continued) 

102

Outcome N Increment RR 95% CI N Increment RR 

Upper gastrointestinal bleeding 1 RN FTE/patient day 1 1 nurse hour/patient day 

1 patient/LPN/shift 3 1 RN hour/patient day 1 patient/UAP/shift 1 1 LPN hour/patient day 1 patient/licensed nurse 1 1 UAP hour/patient day 

2 1 licensed hour/patient day 

Post surgical thrombosis 1 1 RN FTE/patient day 2 1 nurse hour/patient day 

1 patient/LPN/shift 1 1 RN hour/patient day 1 patient/UAP/shift 2 1 LPN hour/patient day 1 patient/licensed nurse 1 1 UAP hour/patient day 

1 1 licensed hour/patient day 

Atelectasis and pulmonary failure 5 1 RN FTE/patient day 0.94 0.93; 0.94 2 1 nurse hour/patient day 

1 1 patient/LPN/shift 2 1 RN hour/patient day 1.0

1 patient/UAP/shift 2 1 LPN hour/patient day 

1 1 patient/licensed nurse 1 1 UAP hour/patient day 

1 1 licensed hour/patient day 

Accidental extubation 5 1 RN FTE/patient day 0.49 0.36; 0.67 1 nurse hour/patient day 

1 patient/LPN/shift 1 RN hour/patient day 1 patient/UAP/shift 1 LPN hour/patient day 1 patient/licensed nurse 1 UAP hour/patient day 

1 licensed hour/patient day 

Hospital acquired pneumonia 4 1 RN FTE/patient day 0.81 0.67; 0.98 5 1 nurse hour/patient day 

2 1 patient/LPN/shift 4 1 RN hour/patient day 

1 patient/UAP/shift 3 1 LPN hour/patient day 

1 1 patient/licensed nurse 1 UAP hour/patient day 

2 1 licensed hour/patient day 

Postoperative infection 1 1 RN FTE/patient day 1.01 0.70; 1.45 4 1 nurse hour/patient day 1.0

1 1 patient/LPN/shift 2 1 RN hour/patient day 1.0

1 patient/UAP/shift 1 1 LPN hour/patient day 0.91 patient/licensed nurse 1 1 UAP hour/patient day 

2 1 licensed hour/patient day 

Cardiac arrest/shock 3 1 RN FTE/patient day 0.72 0.62; 0.84 1 nurse hour/patient day 

1 patient/LPN/shift 1 RN hour/patient day 1 patient/UAP/shift 1 LPN hour/patient day 1 patient/licensed nurse 1 UAP hour/patient day 

1 1 licensed hour/patient day 

Complications (medical) 3 1 RN FTE/patient day 0.72 0.60; 0.86 2 1 nurse hour/patient day 

1 patient/LPN/shift 1 RN hour/patient day 1 patient/UAP/shift 1 LPN hour/patient day 1 patient/licensed nurse 1 UAP hour/patient day 

1 1 licensed hour/patient day 

* significant heterogeneity between studies
103

Table 24. Consistent across the studies, significant association between nurse staffing and patient outcomes (results from poattributable to nurse staffing proportion of events, and number of avoided events per 1,000 hospitalized patients

Outcome Nurse Staffing Studies RR 95% CI 

Attributable 

to Nurse 

Staffing 

Fraction, % 

95%CI 

(

E

H

All Patients Mortality Increase by 1 patient/RN/shift 6 1.08 1.08; 1.09 7.56 7.07; 8.04 Mortality, hospital level analysis Increase by 1 RN FTE/patient day 5 0.96 0.94; 0.98 4.2 6; 2.4 

Mortality, ICUs Increase by 1 RN FTE/patient day 5 0.91 0.86; 0.96 9.2 14.4; 3.7 Mortality, surgical patients Increase by 1 RN FTE/patient day 8 0.84 0.8; 0.89 16 20.2; 11.5 Mortality, medical patients Increase by 1 RN FTE/patient day 6 0.94 0.94; 0.95 5.6 6.3; 4.8 Mortality, ICUs Increase by 1 RN hour/patient day 5 0.99 0.99; 0.99 0.5 0.7; 0.3 Mortality, surgical patients Increase by 1 RN hour/patient day 9 0.99 0.98; 1 1.4 2.5; 0.3 

Mortality, medical patients Increase by 1 RN hour/patient day 10 0.99 0.99; 1 0.7 0.8; 0.5 Hospital acquired pneumonia Increase by 1 patient/RN/shift 3 1.07 1.03; 1.11 6.5 2.9; 9.9 

Failure to rescue Increase by 1 patient/RN/shift 3 1.08 1.07; 1.09 7.4 6.5; 8.3 

Pulmonary failure Increase by 1 patient/RN/shift 4 1.53 1.24; 1.89 34.6 19.4; 47.1 

Unplanned extubation Increase by 1 patient/RN/shift 5 1.45 1.27; 1.67 31.0 21.3; 40.1 CPR Increase by 1 patient/RN/shift 3 1.16 1.05; 1.29 13.8 4.8; 22.5 Medical complications Increase by 1 patient/RN/shift 3 1.17 1.04; 1.31 14.5 3.8; 23.7 Hospital acquired pneumonia Increase by 1 RN FTE/patient day 4 0.81 0.67; 0.98 19.1 33.1; 2.1 Pulmonary failure Increase by 1 RN FTE/patient day 5 0.94 0.94; 0.94 6 6.4; 5.6 

CPR Increase by 1 RN FTE/patient day 5 0.72 0.62; 0.84 27.6 37.9; 15.6 ICUs Hospital acquired pneumonia Increase by 1 RN FTE/patient day 3 0.7 0.56; 0.88 30.2 44.3; 12.4 Pulmonary failure Increase by 1 RN FTE/patient day 4 0.4 0.27; 0.59 60.3 73.4; 40.6 

Unplanned extubation Increase by 1 RN FTE/patient day 5 0.49 0.36; 0.67 50.9 63.7; 33.5 CPR Increase by 1 RN FTE/patient day 3 0.72 0.62; 0.84 27.6 37.9; 15.6 Nosocomial Infection Increase by 1 hour in total nurse 

hours/patient day 

3 0.87 0.82; 0.92 12.9 17.6; 8 

Relative change in LOS Increase by 1 RN FTE/patient day 4 0.76 0.62; 0.94 24 38; 6 

Surgical patients Failure to rescue Increase by 1 RN FTE/patient day 5 0.84 0.79; 0.9 16 21.4; 10.3 Surgical wound infection Increase by 1 RN FTE/patient day 1 0.15 0.03; 0.82 84.5 97.1; 18.1 Sepsis Increase by 1 RN FTE/patient day 5 0.64 0.46; 0.89 36 54; 11 

Relative change in LOS Increase by 1 RN FTE/patient day 3 0.69 0.55; 0.86 31 45; 14 

105 

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List of Acronyms/Abbreviations 

AHRQ Agency for Healthcare Research and Quality 

ANA American Nurses Association 

AONE American Organization of Nurse Executives 

BSN Bachelor of Science in Nursing 

CDC Centers for Disease Control and Prevention 

CI Confidence Interval 

CPR Cardiopulmonary Resuscitation 

DHHS Department of Health and Human Services 

DRGs Diagnosis Related Groups 

FTE Full Time Equivalent 

HPD Hours per Patient Day 

ICD-9 International Classification of Diseases (9th revision) 

ICU Intensive Care Unit 

IEN Internationally Educated Nurse 

JCAHO Joint Commission on Accreditation of Healthcare Organizations 

LOS Length of Stay 

LPN Licensed Practical Nurse 

LVN Licensed Vocational Nurse 

MOOSE Meta-analysis Of Observational Studies in Epidemiology 

MS Master of Science 

NIOSH National Institute for Occupational Safety and Health 

NQF National Quality Forum 

NS Not Significant 

PhD Doctor of Philosophy 

QOL Quality of Life 

RRT Rapid Response Team 

RN Registered Nurse 

RR Relative Risk 

TEP Technical Expert Panel 

UAP Unlicensed Assistive Personnel 

UTI Urinary Tract Infection 
Nurse Staffing and Quality of Patient Care 

Appendixes 

Appendix A: Exact Search Strings 

Appendix B: List of Excluded Studies 

Appendix C: Technical Expert Panel Members and Affiliation 

Appendix D: Sample Abstraction Forms 

Appendix E: Quality of the Studies 

Appendix F. Analytic Framework 

Appendix G: Evidence Tables 

A-1 

Appendix A: Exact Search Strings 

Search Strategy for Questions 1, 2, and 4

The following data bases were searched: 

• Med Line (PubMed) 

• CINAHL 

• The Cochrane Database of Systematic Reviews

• The Cochrane Central Register of Controlled Trials 

• EBSCO Research Database 

• BioMed Central 

• Government agencies and nurse’s associations’ websites are searched to identify 

unpublished reports of the conducted surveys and regulatory documents of nursing hospital 

staffing: 

• United States Department of Health and Human Services 

• Agency for Healthcare Research and Quality 

• National Database of Nursing Quality Indicators 

• National Center for Health Workforce Analysis 

• American Nurses Association 

• American Academy of Nurse Practitioners 

• Government publications. 

• Database http://www.marcive.com/webdocs

• Catalog of U.S. Government Publications (U.S. GPO)

• Digital Dissertations 

• Internet (www.google.com) with the key words identical MeSH terms 

• Manual search of the references in articles to identify eligible studies published before 

1990 

The following MeSH terms and key words (in databases other than Medline) and their 

combinations were used to search the data bases from 1990 through June 2006: 

“Nurses” [MeSH] (Q 1-4)* 

“Nursing staff, hospital” [MeSH] (Q 1-4) 

“Nursing administration research” [MeSH] (Q 1-4) 

“Nursing audit” [MeSH] (Q 1-2, 4) 

“Nursing education research” [MeSH] (Q 1-2, 4) 

“Clinical competence” [MeSH] (Q 1-2) 

“Health care quality, access, and evaluation” [MeSH] (Q1-2, 4) 

“Health services research” [MeSH] (Q1, 2, 4) 

“Outcome assessment (health care)” [MeSH] (Q1-2, 4) 

“Health care category” [MeSH] (Q1, 2, 4) 

“Patients” [MeSH] (Q1-2, 4) 

“Length of stay” [MeSH] (Q1-2, 4) 

“Patient satisfaction” [MeSH] (Q1-2, 4) 
A-2 

“Hospital units” [MeSH] (Q1, 2, 4) 

“Personnel staffing and scheduling” [MeSH] (Q1-3) 

“Patient centered care” [MeSH] (Q4) 

“Nurse patient relations” [MeSH] (Q1-2, 4) 

“Hospital patient relations” [MeSH] (Q1-2, 4) 

"Models, nursing” [MeSH] (Q 4) 

“Labor unions” [MeSH] (Q 4) 

“Malpractice” [MeSH] 

“Hospitals” [MeSH] (Q4) 

Nurse to patient ratio (keyword) (Q1-3) 

“Skill mix” [MeSH] (Q3) 

“Part time employment [MeSH] (Q3) 

“Foreign nurses [MeSH] (Q3) 

“Registry personnel” [MeSH] (Q3) 

Overtime (keyword) (Q3) 

Flexible scheduling (keyword) (Q3) 

Shift work (key word) (Q3) 

* The numbers in parentheses refer to the question for which this term was relevant 

Search Strategy for Question 3

(Inclusion criteria for all studies: North American hospitals, research in peer reviewed journal, 

published between 1990-2006) 

Shift work staffing policy variable 

58 eligible for review 

51 excluded: 

• 41 Not relevant (not related to variable of interest) 

• 1 Integrative review not related to study variable 

• 2 Conference abstract 

• 2 Nursing home 

• 3 Not peer reviewed journal 

• 2 Inadequate data presentation 

7 included 

Overtime staffing policy variable 

20 eligible for review 

14 excluded: 

• 9 Not relevant (not related to variable of interest) 

• 1 Inadequate data presentation 

• 4 Not peer reviewed journal 

6 included 
A-3 

Full and part time staff use variable

28 eligible for review 

22 excluded: 

• 15 Not relevant (not related to variable of interest) 

• 6 Not peer reviewed journal 

• 1 Inadequate data presentation 

6 included 

Foreign educated nurses variable 

20 eligible for review 

14 excluded 

• 12 Not relevant (not related to variable of interest) 

• 1 Not research 

• 1 Not peer reviewed journal 

6 included 

Agency/contract nurses variable

21 eligible for review 

16 excluded: 

• 10 Not relevant (not related to variable of interest) 

• 1 Nursing home 

• 2 Inadequate data presentation 

• 3 Not peer reviewed journal 

5 included 

Total studies on staffing policy variables

147 eligible for review 

117 excluded: 

• 87 Not relevant (not related to variable of interest) 

• 2 Conference proceedings 

• 1 Integrative review not related to variable of interest 

• 3 Nursing home 

• 17 Not peer reviewed journal 

• 6 Inadequate presentation of data 

• 1 Not research 

30 included 

Literature Search Strings

MeSH terms Studies

The National Library of Medicine via PubMed: 

“Nurses” [MeSH] 51,730 

"Nursing staff, hospital"[MeSH] 28,092 

"Nursing administration research”[MeSH] 1,218 

"Nursing audit"[MeSH] 2,349 
A-4 

MeSH terms Studies

"Nursing education research"[MeSH] 3,285 

"Clinical competence"[MeSH] 33,806 

"Health care quality, access, and evaluation"[MeSH] 3,090,640 

"Health services research"[MeSH] 64,621 

"Outcome assessment (health care)"[MeSH] 286,369 

"Health care category"[MeSH] 4,438,573 

"Personnel administration, hospital"[MeSH] 4,968 

"Patients"[MeSH] 35,872 

"Length of stay"[MeSH] 33,382 

"Patient satisfaction"[MeSH] 28,736 

"Hospital units"[MeSH] 48,491 

"United States/epidemiology"[MeSH] 77,520 

"Personnel staffing and scheduling"[MeSH] 9,484 

"Models, nursing"[MeSH] 7,513 

"Foreign professional personnel"[MeSH] 3,523 

("Safety management"[MeSH] OR "risk management"[MeSH]) 82,840 

("Safety management"[MeSH] OR "risk management"[MeSH]) Limits: 

English, humans 

 70,596 

("Safety management"[MeSH] OR "risk management"[MeSH]) NOT review 

NOT letters NOT editorials Limits: English, humans 

 48,105 

"Nurses"[MeSH] NOT review NOT letters NOT editorials 43,370 

"Nursing staff, hospital"[MeSH] NOT review NOT letters NOT editorials 25,773 

"Nursing administration research "[MeSH] NOT review NOT letters NOT 

editorials 

 994 

"Nursing audit"[MeSH] NOT review NOT letters NOT editorials Limits: 

English, humans 

 1,450 

"Nursing education research "[MeSH] NOT review NOT letters NOT 

editorials Limits: humans 

 2,723 

"Clinical competence"[MeSH] NOT review NOT letters NOT editorials 

Limits: humans 

 22,181 

"Health care quality, access, and evaluation"[MeSH] NOT review NOT letters 

NOT editorials Limits: English, humans 

 1,798,295 

"Health services research"[MeSH] NOT review NOT letters NOT editorials 

Limits: humans 

 43,486 

"Outcome assessment (health care)"[MeSH] AND "health services research" 

[MeSH] NOT review NOT letters NOT editorials Limits: humans 

 15 

"Health care category"[MeSH] NOT review NOT letters NOT editorials 

Limits: English, humans 

 2,320,378 

"Personnel administration, hospital"[MeSH] NOT review NOT letters NOT 

editorials Limits: English, humans 

 1,601 

"Patients"[MeSH] NOT review NOT letters NOT editorials Limits: English, 

humans 

 23,507 

"Length of stay"[MeSH] NOT review NOT letters NOT editorials Limits: 

English, humans 

 22,937 
A-5 

MeSH terms Studies

"Patient satisfaction"[MeSH] NOT review NOT letters NOT editorials Limits: 

English, humans 

 20,849 

"Hospital units"[MeSH] NOT review NOT letters NOT editorials Limits: 

English, humans 

 27,731 

"United States/epidemiology"[MeSH] NOT review NOT letters NOT 

editorials Limits: English, humans 

 57,481 

"Personnel staffing and scheduling"[MeSH] NOT review NOT letters NOT 

editorials Limits: English, humans 

 5,335 

"Models, nursing"[MeSH] NOT review NOT letters NOT editorials Limits: 

English, humans 

 4,544 

"Foreign professional personnel"[MeSH] NOT review NOT letters NOT 

editorials Limits: English, humans 

 1,375 

"Nurses"[MeSH] NOT review NOT letters NOT editorials AND 

"patients"[MeSH] Limits: English, humans 

 396 

"Nurses"[MeSH] NOT review NOT letters NOT editorials AND "clinical 

competence" Limits: English, humans 

 6 

"Nurses"[MeSH] NOT review NOT letters NOT editorials AND "health care 

quality, access, and evaluation"[MeSH] Limits: English, humans 

 49 

"Nurses"[MeSH] NOT review NOT letters NOT editorials AND "health 

services research" Limits: English, humans 

 2 

"Nurses"[MeSH] NOT review NOT letters NOT editorials AND "outcome 

assessment (health care)" Limits: English, humans 

 1 

"Nurses"[MeSH] NOT review NOT letters NOT editorials AND "personnel 

administration, hospital" Limits: English, humans 

 0 

"Nurses"[MeSH] NOT review NOT letters NOT editorials AND "length of 

stay" Limits: English, humans 

 2 

"Nurses"[MeSH] NOT review NOT letters NOT editorials AND "patient 

satisfaction" Limits: English, humans 

 2 

"Nurses"[MeSH] NOT review NOT letters NOT editorials AND personnel 

staffing and scheduling Limits: English, humans 

 2 

"Epidemiologic studies"[MeSH] Limits: English, humans 728,060 

"Epidemiologic studies"[MeSH] AND "nurses"[MeSH] Limits: English, 

humans 

 1,210 

"Epidemiologic studies"[MeSH] AND "nursing staff, hospital"[MeSH] 

Limits: English, humans 

 731 

"Epidemiologic studies"[MeSH] AND "nursing administration research 

"[MeSH] Limits: English, humans 

 99 

"Epidemiologic studies"[MeSH] AND "nursing audit"[MeSH] Limits: 

English, humans 

 210 

"Epidemiologic studies"[MeSH] AND "nursing education research "[MeSH] 

Limits: English, humans 

 187 

"Epidemiologic studies"[MeSH] AND "clinical competence"[MeSH] Limits: 

English, humans 

 2,169 

"Epidemiologic studies"[MeSH] AND "health care quality, access, and 

evaluation"[MeSH] Limits: English, humans 

 728,210 
A-6 

MeSH terms Studies

"Epidemiologic studies"[MeSH] AND "health services research "[MeSH] 

AND "nurses"[MeSH] Limits: English, humans 

 85 

"Epidemiologic studies"[MeSH] AND "nurses"[MeSH] AND "outcome 

assessment (health care)"[MeSH] Limits: English, humans 

 108 

"Epidemiologic studies"[MeSH] AND "nurses"[MeSH] AND "personnel 

administration, hospital" [MeSH] Limits: English, humans 

 0 

"Epidemiologic studies"[MeSH] AND "nurses"[MeSH] AND "patients" 

[MeSH] Limits: English, humans 

 23 

"Epidemiologic studies"[MeSH] AND "nurses"[MeSH] AND "length of 

stay"[MeSH] Limits: English, humans 

 38 

"Epidemiologic studies"[MeSH] AND "nurses"[MeSH] AND "patient 

satisfaction"[MeSH] Limits: English, humans 

 56 

"Epidemiologic studies"[MeSH] AND "models, nursing" Limits: English, 

humans 

 190 

"Epidemiologic studies"[MeSH] AND "nursing staff, hospital"[MeSH] AND 

"safety management" Limits: English, humans 

 1 

"Nursing staff, hospital"[MeSH] AND "patients"[MeSH] Limits: English, 

humans 

 506 

"Nursing staff, hospital"[MeSH] AND "length of stay"[MeSH] Limits: 

English, humans 

 192 

"Nursing staff, hospital"[MeSH] AND "patient satisfaction"[MeSH] Limits: 

English, humans 

 324 

"Nursing staff, hospital"[MeSH] AND "safety management"[MeSH] Limits: 

English, humans 

 188 

"Safety management"[MeSH] AND "nursing administration research 

"[MeSH] Limits: English, humans 

 17 

"Safety management"[MeSH] AND "nursing audit"[MeSH] Limits: English, 

humans 

 18 

"Safety management"[MeSH] AND "clinical competence"[MeSH] Limits: 

English, humans 

 125 

"Safety management"[MeSH] AND "health dare quality, access, and 

evaluation"[MeSH] Limits: English, humans 

 3,253 

"Safety management"[MeSH] AND "health services research"[MeSH] Limits: 

English, humans 

 465 

"Safety management"[MeSH] AND "outcome assessment (health 

care)"[MeSH] Limits: English, humans 

 111 

"Safety management"[MeSH] AND "models, nursing" Limits: English, 

humans 

 27 

"Outcome assessment (health care)"[MeSH] AND "nursing staff, 

hospital"[MeSH] Limits: English, humans 

 344 

CINAHL - Cumulative Index to Nursing & Allied Health Literature: 

“Personnel staffing and scheduling" 9,271 

“Nursing staff, hospital/manpower” 57 

"Length of stay" 5,269 

“Patient safety” 14,395 
A-7 

MeSH terms Studies

“Nurses” 72,321 

“Personnel staffing and scheduling" or “nursing staff, hospital/manpower” 

AND "length of stay" or “patient safety” 

 1,025 

“Personnel staffing and scheduling" or “nursing staff, hospital/manpower” 

AND "length of stay" or “patient safety” limit on English, NOT review or 

letter 

 86 

The Cochrane Library: 

"Nursing staff, hospital” and “outcome assessment (health care)” 0 

“Nurse” AND “patient” 4 

BioMed Central : 

"Nursing staff, hospital” AND “patient safety” 0 

"Nursing staff, hospital” AND “patient outcomes” 0 

Nursing staff, hospital AND health services research 287 

Nursing staff, hospital AND adverse events 79 

Google scholar: “nursing staff, hospital” AND “patient outcomes” NOT longterm care, published after 1990  1,700 

Catalog of U.S. Government Publications (U.S. GPO): 

Nursing Staff, Hospital 9 

LexisNexisTM Government Periodicals Index: 

"Nurses and nursing" AND "Hospitals" 25 

Digital Dissertations: 

Nurse AND patient 1,863 

Nursing staff, hospital 0 

Nurse AND staffing AND hospital AND patient 20 

Agency of Health Care Research and Quality: 

Nurse staffing and Patient 893 

Positive Likelihood of MeSH Terms and Keywords (*) to Identify Studies Eligible for 

Questions 1, 2, and 4

Algorithm: 

 Sensitivity = TP/(TP+FN) 

 Specificity = TN/(FP+TN) 

 Positive Likelihood = SENS/(1-SPEC) 

 Negative Likelihood = (1-SENS)/SPEC 

Study status Eligible Excluded Total 

Keyword Present TP FP 

Keyword absent FN TN 

 96 2,762 2,858 
A-8 

A. Highest Positive Predictive Likelihood 

MeSH terms and keywords Sensitivity, % Specificity, % 

Positive 

Likelihood

*Burnout professional 3.13 99.96 86.31 

Decubitus ulcer/epidemiology 6.25 99.93 86.31 

Nurses/*supply & distribution 3.13 99.96 86.31 

United States Centers for Medicare and 

Medicaid Services 5.21 99.93 71.93 

Accidental falls s & numerical data 9.38 99.86 64.73 

*Mortality 2.08 99.96 57.54 

Comorbidity 2.08 99.96 57.54 

Medicare/*statistics & numerical data 2.08 99.96 57.54 

Nursing service 2.08 99.96 57.54 

Urinary tract infection 2.08 99.96 57.54 

California/epidemiology 5.21 99.89 47.95 

Health services research/methods 3.13 99.93 43.16 

*Anesthesiology 1.04 99.96 28.77 

*Economic competition 1.04 99.96 28.77 

*Economics 1.04 99.96 28.77 

*Outcome and process assessment (health care) 5.21 99.82 28.77 

Acquired immunodeficiency syndrome 1.04 99.96 28.77 

Bacteremia/epidemiology 1.04 99.96 28.77 

Bacteremia/epidemiology/etiology 1.04 99.96 28.77 

Burn units/*manpower 1.04 99.96 28.77 

Contract services/organization & administration 1.04 99.96 28.77 

Cross infection/*prevention & control 2.08 99.93 28.77 

Cross infection/epidemiology 1.04 99.96 28.77 

Cross infection/epidemiology/*etiology/ 

prevention & control 1.04 99.96 28.77 

Delivery of health care/*organization & 

administration 1.04 99.96 28.77 

Disease outbreak 1.04 99.96 28.77 

Economics hospital 1.04 99.96 28.77 

Education nursing 1.04 99.96 28.77 

Health maintenance organizations 1.04 99.96 28.77 

Health maintenance organizations *organization 

& administration 1.04 99.96 28.77 

Hospital restructuring 1.04 99.96 28.77 

Hospitals pediatric 1.04 99.96 28.77 

Hospitals university 1.04 99.96 28.77 

Hospitals urban 1.04 99.96 28.77 

Hospitals/*standards 1.04 99.96 28.77 

Hospitals/classification 1.04 99.96 28.77 

Hospitals/*standards/statistics & numerical data 1.04 99.96 28.77 

Iatrogenic disease 1.04 99.96 28.77 

Insurance claim 1.04 99.96 28.77 
A-9 

MeSH terms and keywords Sensitivity, % Specificity, % 

Positive 

Likelihood

Intensive care units neonatal/economics 1.04 99.96 28.77 

Intensive care units pediatric/*organization & 

administration 1.04 99.96 28.77 

Medicare 2.08 99.93 28.77 

Nurses' aides/supply & distribution 2.08 99.93 28.77 

Nursing staff hospital/*economics/organization 

& administration 1.04 99.96 28.77 

Nursing staff hospital/*education/*standards 1.04 99.96 28.77 

Nursing staff hospital/organization & 

administration/statistics 1.04 99.96 28.77 

Outcome assessment 1.04 99.96 28.77 

Pediatrics 1.04 99.96 28.77 

Pennsylvania/epidemiology 1.04 99.96 28.77 

Personnel management 1.04 99.96 28.77 

Pneumonia/epidemiology 1.04 99.96 28.77 

Postoperative complications/epidemiology 1.04 99.96 28.77 

Quality of health care 1.04 99.96 28.77 

Quality of health care/*classification 1.04 99.96 28.77 

Restraint physical 1.04 99.96 28.77 

Safety management 1.04 99.96 28.77 

Surgical procedures operative/*statistics & 

numerical data 1.04 99.96 28.77 

United States Agency for Healthcare Research 

and Quality 1.04 99.96 28.77 

Urinary tract infections/epidemiology/etiology 1.04 99.96 28.77 

Workload/ psychology 2.08 99.93 28.77 

Workload/standards 2.08 99.93 28.77 

*Hospital mortality 13.54 99.49 26.72 

Cross Infection/epidemiology 3.13 99.86 21.58 

Medication error 6.25 99.71 21.58 

Iatrogenic disease 2.08 99.89 19.18 

Morbidity 2.08 99.89 19.18 

Nursing care/psychology 2.08 99.89 19.18 

Probability 2.08 99.89 19.18 

Odds ratio 5.21 99.67 15.98 

United States/epidemiology 14.58 99.02 14.92 

*Educational standards 1.04 99.93 14.39 

*Treatment outcome 1.04 99.93 14.39 

Catheterization 1.04 99.93 14.39 

Databases factual 1.04 99.93 14.39 

Diagnosis related groups/statistics & numerical 

data 1.04 99.93 14.39 

Education nursing baccalaureate 2.08 99.86 14.39 
A-10 

MeSH terms and keywords Sensitivity, % Specificity, % 

Positive 

Likelihood

Hospital units/*organization & administration/ 

standards 1.04 99.93 14.39 

Hospitals public 1.04 99.93 14.39 

Hospitals teaching 1.04 99.93 14.39 

Length of stay/epidemiology 1.04 99.93 14.39 

Maryland 2.08 99.86 14.39 

Matched-pair analysis 1.04 99.93 14.39 

Minnesota/epidemiology 1.04 99.93 14.39 

Nursing service 2.08 99.86 14.39 

Nursing staff hospital 1.04 99.93 14.39 

Patient isolation 1.04 99.93 14.39 

Personnel hospital 1.04 99.93 14.39 

Referral and con 1.04 99.93 14.39 

Sentinel surveillance 1.04 99.93 14.39 

Workload/psychology 1.04 99.93 14.39 

*Outcome assessment (health care ) 15.63 98.84 13.49 

Nurses' aides/* 2.08 99.82 11.51 

*Education nursing 1.04 99.89 9.59 

Nursing staff hospital/*organization & 

administration/standards 1.04 99.89 9.59 

Accidental falls 1.04 99.89 9.59 

Chronic disease 2.08 99.78 9.59 

Health services research/*method 1.04 99.89 9.59 

Hospital costs/*statistics & numerical data 1.04 99.89 9.59 

Hospital restructuring 1.04 99.89 9.59 

Hospitals teaching/standards 1.04 99.89 9.59 

Hospitals teaching/statistics & numerical data 1.04 99.89 9.59 

Mortality 1.04 99.89 9.59 

Nursing assessment/organization & 

administration 1.04 99.89 9.59 

Nursing staff hospital/*organization & 

administration/*standard 1.04 99.89 9.59 

Nursing staff hospital/economic/psychology/* 

supply & distribution 1.04 99.89 9.59 

Ontario/epidemiology 1.04 99.89 9.59 

Patient discharge 1.04 99.89 9.59 

Personnel staffing and scheduling/*legislation 

& jurisprudence/*standards 1.04 99.89 9.59 

Personnel staffing and scheduling/*standards/ 

statistics & numerical data 1.04 99.89 9.59 

Poisson distribution 1.04 99.89 9.59 

Psychology industrial 1.04 99.89 9.59 

Quality of health care/standards 1.04 99.89 9.59 

Risk adjustment 1.04 99.89 9.59 
A-11 

MeSH terms and keywords Sensitivity, % Specificity, % 

Positive 

Likelihood

Statistics 1.04 99.89 9.59 

Personnel staffing and scheduling/*statistics & 

numerical data 5.21 99.46 9.59 

Multivariate analysis 9.38 98.95 8.93 

Diagnosis related 3.13 99.64 8.63 

*Quality indicators, health care 5.21 99.38 8.46 

Logistic models 9.38 98.84 8.09 

Pennsylvania 4.17 99.46 7.67 

Hospital mortality 7.29 99.02 7.46 

Continuity of patient care/standards 1.04 99.86 7.19 

Medication error 1.04 99.86 7.19 

Models theoretical 1.04 99.86 7.19 

Outcome and process assessment (health 

care)/*organization & 1.04 99.86 7.19 

Ownership 1.04 99.86 7.19 

Patient education 1.04 99.86 7.19 

Patient readmission 1.04 99.86 7.19 

Personnel staffing and scheduling/economics/* 

standards 1.04 99.86 7.19 

Personnel staffing and scheduling/statistics & 

numerical data/*trends 1.04 99.86 7.19 

Risk 1.04 99.86 7.19 

Administration/utilization 1.04 99.86 7.19 

Acute disease/nursing 3.13 99.57 7.19 

Linear models 3.13 99.53 6.64 

Research support 23.96 96.16 6.24 

Research support 4.17 99.31 6.06 

*Licensure nursing 1.04 99.82 5.75 

American Hospital Association 1.04 99.82 5.75 

Confidence intervals 1.04 99.82 5.75 

Feasibility studies 1.04 99.82 5.75 

Hospital bed capacity 1.04 99.82 5.75 

Least-squares analysis 1.04 99.82 5.75 

Likelihood function 1.04 99.82 5.75 

Medical staff hospital/statistics & numerical data 1.04 99.82 5.75 

Nurses 1.04 99.82 5.75 

Nursing staff hospital/*standards/supply & 

distribution 1.04 99.82 5.75 

Population surveillance 1.04 99.82 5.75 

Postoperative care 1.04 99.82 5.75 

Proportional hazard 1.04 99.82 5.75 

Salaries and fringes 1.04 99.82 5.75 

Tennessee 1.04 99.82 5.75 

Health care survey 6.25 98.91 5.75 
A-12 

MeSH terms and keywords Sensitivity, % Specificity, % 

Positive 

Likelihood

Benchmarking 4.17 99.28 5.75 

Case-control study 4.17 99.24 5.48 

Outcome and process assessment (health care) 3.13 99.42 5.39 

Sampling studies 2.08 99.60 5.23 

Workload/*statistics 2.08 99.60 5.23 

Midwestern United States 3.13 99.38 5.08 

Health services 10.42 97.94 5.05 

B. MeSH Terms and Keywords in Eligible Studies (Sensitivity >0) 

MeSH terms Sensitivity Specificity 

Positive 

Predictive 

Likelihood

*Models statistics 1.04 99.78 4.80 

Alberta 1.04 99.78 4.80 

Critical pathway 1.04 99.78 4.80 

District of Columbia 1.04 99.78 4.80 

Nursing staff hospital/*legislation & 

jurisprudence/*supply & 1.04 99.78 4.80 

Patient care planning 1.04 99.78 4.80 

Patients 1.04 99.78 4.80 

Length of stay 10.42 97.79 4.72 

Regression analysis 9.38 97.97 4.62 

Intensive care units 4.17 99.09 4.60 

Length of stay/standards 5.21 98.84 4.50 

Quality indicators health care 4.17 99.06 4.43 

Hospital bed capacity 2.08 99.53 4.43 

Length of stay/economics 2.08 99.53 4.43 

Cohort studies 3.13 99.28 4.32 

*Patients 1.04 99.75 4.11 

Bed occupancy 1.04 99.75 4.11 

Consumer satisfaction 1.04 99.75 4.11 

Hospital costs/standards 1.04 99.75 4.11 

Hospital-patient relations 1.04 99.75 4.11 

Hospitalization 1.04 99.75 4.11 

Intensive care units/*organization & 

administration 1.04 99.75 4.11 

Medical errors 1.04 99.75 4.11 

Patient satisfaction 1.04 99.75 4.11 

Southeastern union 1.04 99.75 4.11 

Nursing supervisory 2.08 99.49 4.11 

American Nurses' Association 2.08 99.46 3.84 

Personnel turnover 2.08 99.46 3.84 

Outcome assessment (health care) 9.38 97.54 3.81 

*Length of stay 1.04 99.71 3.60 
A-13 

MeSH terms Sensitivity Specificity 

Positive 

Predictive 

Likelihood

*Models organizational 1.04 99.71 3.60 

Choice behavior 1.04 99.71 3.60 

Forms and records 1.04 99.71 3.60 

Nurses' aides/*organization & administration 1.04 99.71 3.60 

Safety 2.08 99.42 3.60 

Risk assessment 2.08 99.38 3.38 

*Patient care team 1.04 99.67 3.20 

Education nursing 1.04 99.67 3.20 

Hospital bed cap 1.04 99.67 3.20 

Hospitals public 1.04 99.67 3.20 

Medical staff hospital/standard 1.04 99.67 3.20 

Missouri 1.04 99.67 3.20 

Nursing staff hospital/education*organization 1.04 99.67 3.20 

Physician-nurse relations 1.04 99.67 3.20 

Hospital restructuring/*organization & 

administration 2.08 99.35 3.20 

Patient satisfaction/*statistics & numerical data 2.08 99.35 3.20 

Predictive value 3.13 98.99 3.08 

Risk factors 15.63 94.71 2.96 

*Intensive care 1.04 99.64 2.88 

*Personnel staff 1.04 99.64 2.88 

Health policy 1.04 99.64 2.88 

Nursing care/*organization 1.04 99.64 2.88 

Nursing service 1.04 99.64 2.88 

Safety management 1.04 99.64 2.88 

Administration/standards 1.04 99.64 2.88 

*Quality of health care 10.42 96.16 2.71 

Quality of health care 8.33 96.92 2.71 

Nursing administration research 14.58 94.61 2.70 

Severity of illness 4.17 98.44 2.68 

*Efficiency organization 1.04 99.60 2.62 

Hospitals/*standards 1.04 99.60 2.62 

Length of stay/*statistics & numerical data 1.04 99.60 2.62 

Stress psychological 1.04 99.60 2.62 

Personnel staffing and scheduling/standards 3.13 98.77 2.54 

Personnel turnover 3.13 98.73 2.47 

Acute disease 2.08 99.13 2.40 

*Clinical competition 3.13 98.70 2.40 

Clinical nursing 1.04 99.57 2.40 

Connecticut 1.04 99.57 2.40 

Night care/*manpower 1.04 99.57 2.40 

Nursing staff hospital/psychology/supply & 

distribution 1.04 99.57 2.40 
A-14 

MeSH terms Sensitivity Specificity 

Positive 

Predictive 

Likelihood

Numerical data 2.08 99.09 2.30 

Nursing care/*standards 3.13 98.62 2.27 

*Quality assurance health care 1.04 99.53 2.21 

Absenteeism 1.04 99.53 2.21 

Nursing staff hospital/organization & 

administration 1.04 99.53 2.21 

Pain measurement 1.04 99.53 2.21 

Case management 1.04 99.49 2.06 

Nursing care/statistics 1.04 99.49 2.06 

Outcome assessment 1.04 99.49 2.06 

Nursing staff hospital/economic 2.08 98.91 1.92 

Internal-external control 1.04 99.46 1.92 

Organizational case studies 1.04 99.46 1.92 

Prevalence 2.08 98.88 1.86 

*Nursing staff 1.04 99.42 1.80 

Total quality management 1.04 99.42 1.80 

Treatment outcome 2.08 98.81 1.74 

Costs and cost assessment 1.04 99.38 1.69 

Patient discharge 1.04 99.38 1.69 

Health services 2.08 98.73 1.64 

Models organizational 2.08 98.73 1.64 

Ontario 2.08 98.73 1.64 

*Personnel management 1.04 99.35 1.60 

Nursing research 1.04 99.35 1.60 

Nursing staff hospital/*supply distribution 16.67 89.54 1.59 

Aged 14.58 90.55 1.54 

Pilot projects 4.17 97.28 1.53 

Personnel staffing and scheduling/*standards 7.29 95.22 1.53 

*Occupational health 1.04 99.31 1.51 

Evidence-based 1.04 99.31 1.51 

Hospital costs 1.04 99.31 1.51 

Statistics nonparametric 1.04 99.31 1.51 

Incidence 2.08 98.59 1.48 

*Professional autonomy 1.04 99.28 1.44 

Hospital bed capacity 1.04 99.28 1.44 

Hospital units 1.04 99.28 1.44 

Research support 23.96 83.09 1.42 

*Leadership 1.04 99.24 1.37 

Educational status 1.04 99.24 1.37 

Distribution 3.13 97.68 1.35 

Retrospective studies 5.21 96.13 1.34 

Risk management 1.04 99.20 1.31 

Administration 1.04 99.20 1.31 
A-15 

MeSH terms Sensitivity Specificity 

Positive 

Predictive 

Likelihood

Prospective studies 7.29 94.28 1.27 

California 3.13 97.54 1.27 

Workload 7.29 94.24 1.27 

*Decision making 1.04 99.17 1.25 

Analysis of variance 3.13 97.50 1.25 

Data 1.04 99.17 1.25 

Michigan 1.04 99.13 1.20 

Longitudinal studies 3.13 97.36 1.18 

Nurse-patient relations 4.17 96.45 1.17 

Organizational innovation 4.17 96.45 1.17 

Age 80 and over 4.17 96.38 1.15 

Male 25.00 78.17 1.15 

Job satisfaction 6.25 94.42 1.12 

Quality assurance 1.04 99.06 1.11 

administration/psychology 1.04 99.06 1.11 

Patient satisfaction 6.25 94.32 1.10 

United States 15.63 85.37 1.07 

Cross-sectional 7.29 93.16 1.07 

Cost control 1.04 98.99 1.03 

Patient care team 1.04 98.99 1.03 

Time factors 4.17 95.87 1.01 

Factor analysis 1.04 98.95 0.99 

Power (psychology) 1.04 98.95 0.99 

*Patient satisfaction 4.17 95.80 0.99 

Canada 1.04 98.91 0.96 

Nursing evaluation on research 6.25 93.41 0.95 

Middle age 14.58 84.43 0.94 

Nurse administrators 1.04 98.88 0.93 

Texas 1.04 98.88 0.93 

Female 25.00 72.88 0.92 

Evaluation studies 1.04 98.84 0.90 

Personnel staffing and scheduling 7.29 91.64 0.87 

Child 4.17 95.22 0.87 

Data collection 2.08 97.57 0.86 

*Job satisfaction 3.13 96.31 0.85 

*Inpatients 1.04 98.77 0.85 

*Personnel staff 7.29 91.24 0.83 

Cost-benefit 1.04 98.62 0.76 

Humans 71.88 2.75 0.74 

Efficiency organization 1.04 98.59 0.74 

Comparative study 6.25 90.84 0.68 

Adult 14.58 77.62 0.65 

Infant 1.04 98.37 0.64 
A-16 

MeSH terms Sensitivity Specificity 

Positive 

Predictive 

Likelihood

Medical staff hospital 1.04 98.33 0.63 

Nursing audit 1.04 98.30 0.61 

Attitude of health 5.21 91.31 0.60 

Child preschool 1.04 98.23 0.59 

Inpatients/*psychology 1.04 98.19 0.58 

Job description 1.04 98.12 0.55 

Organizational care 2.08 96.20 0.55 

Professional autonomy 1.04 98.04 0.53 

Reproducibility 1.04 98.04 0.53 

Adolescent 2.08 96.05 0.53 

Hospitals teach 1.04 97.97 0.51 

*Nursing staff hospital 4.17 91.67 0.50 

Nurse's role 2.08 95.58 0.47 

*Nurse's role 1.04 97.72 0.46 

Personnel staffing and scheduling/*organization 

& administration 3.13 93.12 0.45 

Personnel staffing and scheduling/*legislation 

& jurisprudence 1.04 97.61 0.44 

Social support 1.04 97.61 0.44 

Clinical competence 1.04 97.57 0.43 

*Models nursing 2.08 95.11 0.43 

Clinical compete 1.04 97.47 0.41 

Questionnaires 6.25 82.48 0.36 

Infant newborn 1.04 97.07 0.36 

Interprofessional relations 1.04 96.85 0.33 

Needs assessment 1.04 96.02 0.26 

Models nursing 1.04 95.37 0.22 

C. MeSH Terms and Keywords in Excluded Studies (Sensitivity = 0) 

MeSH Terms 

*Absenteeism 

*Accidental fall 

*Accidental falls/economics 

*Accidents 

*Accidents occupational 

*Accidents occupational/prevention & control/statistics & numerical data 

*Accreditation 

*Aftercare/statistics & numerical data 

*Allied health personnel 

*American Nurses Association 

*Ancillary services hospital/statistics & numerical data 

*Automatic data processing 
A-17 

*Automation 

*Bed occupancy 

*Bed occupancy/economics 

*Benchmarking 

*Bereavement 

*Burnout professional/epidemiology/etiology/psychology 

*Burnout professional/etiology/prevention & control 

*Burnout professional/etiology/ prevention & control/psychology 

*Burnout professional/prevention & control/psychology 

*Caregivers 

*Case management 

*Cause of death 

*Clinical nursing research 

*Clinical protocols 

*Communication 

*Communication barriers 

*Consumer satisfaction 

*Continuity of patient care 

*Contract services 

*Contract services/economics 

*Cost of illness 

*Cost-benefit analysis 

*Counseling/education/standards 

*Credentialing 

*Cross infection 

*Cross infection/nursing/transmission/virology 

*Cross-cultural comparison 

*Data collection 

*Data interpretation statistical 

*Death 

*Decision making 

*Decision support 

*Decision support systems management 

*Decision support techniques 

*Decision trees 

*Delivery of health care 

*Diagnosis-related groups 

*Diagnostic errors 

*Disease transmission professional-to-patient 

*Documentation 

*Drug combinations 

*Drug compounding 

*Drug delivery systems 

*Drug labeling 

*Drug therapy computer-assisted 

*Economics hospital 
A-18 

*Economics nursing 

*Education medical continuing 

*Education nursing baccalaureate 

*Education nursing continuing 

*Educational measurement 

*Efficiency 

*Emergency medicine/organization & administration*emergency nursing 

*Emergency nursing/organization & administration 

*Emergency service hospital 

*Emergency service hospital/organization & administration 

*Employee discipline 

*Employee incentive plans 

*Employee performance appraisal 

*Employment 

*Episode of care 

*Ethics 

*Ethics business 

*Ethics clinical 

*Ethics institutional 

*Ethics nursing 

*Evidence-based medicine 

*Expert testimony/*legislation & jurisprudence 

*Foreign professional personnel 

*Foreign professional personnel/education/psychology 

*Foreign professional personnel/standards 

*Health care rationing 

*Health care reform 

*Health care surveys 

*Health education 

*Health education/methods 

*Health facility closure 

*Health facility environment 

*Health facility environment/ethics/organization & administration*health facility merger 

*Health knowledge attitudes practice 

*Health manpower 

*Health services accessibility 

*Health services needs and demand 

*Health services statistics & numerical data 

*Health services research 

*Hospital administration 

*Hospital communication systems/organization & administration 

*Hospital costs 

*Hospital design and construction*hospital information systems 

*Hospital information systems/organization & administration 

*Hospital restructuring 

*Hospital units 
A-19 

*Hospital-patient relations 

*Hospitalization 

*Hospitalization/economics 

*Hospitalization/statistics & numerical data 

*Hospitals 

*Infection control practitioners 

*Inpatients/education/psychology 

*Inpatients/psychology 

*Inpatients/psychology/statistics & numerical data 

*Intensive care units/manpower 

*Intensive care units/statistics 

*Interpersonal relations 

*Inter professional relations 

*Joint Commission on Accreditation of Healthcare Organizations 

*Labor unions 

*Labor unions/trends 

*Legislation hospital 

*Legislation nursing 

*Length of stay/legislation & jurisprudence/statistics & numerical data 

*Liability legal 

*Linear models 

*Malpractice 

*Medical errors/adverse effects 

*Medical staff hospital 

*Medical staff hospital/education/psychology 

*Medical staff hospital/psychology/statistics & numerical data 

*Medication errors/adverse effects 

*Medication errors/classification 

*Medication errors/methods/nursing/prevention & control/statistics & 

*Medication errors/statistics & numerical data 

*Models nursing 

*Models organizational 

*Monitoring intra operative/methods/nursing 

*Nurse administrators 

*Nurse administrators/education/psychology 

*Nurse administrators/organization & administration/psychology 

*Nurse practitioners 

*Nurse practitioners/economics 

*Nurse's role/psychology 

*Nurse-patient relations 

*Nurseries hospital 

*Nurses 

*Nurses' aides 

*Nurses' aides/education 

*Nurses' aides/education/organization & administration/psychology*nursing 

*Nursing administration research 
A-20 

*Nursing assessment 

*Nursing assessment/methods/standards 

*Nursing audit 

*Nursing care 

*Nursing care/manpower 

*Nursing care/organization & administration/psychology 

*Nursing care/psychology/standards 

*Nursing care/psychology/statistics & numerical data 

*Nursing diagnosis 

*Nursing methodology research 

*Nursing process 

*Nursing process/standards 

*Nursing records 

*Nursing research 

*Nursing service hospital 

*Nursing staff 

*Nursing staff hospital 

*Nursing staff hospital/economics/standards 

*Nursing staff hospital/economics statistics & numerical data 

*Nursing staff hospital/economics/supply & distribution 

*Nursing staff hospital/education 

*Nursing staff hospital/education/organization 

*Nursing staff hospital/education/organization & administration 

*Nursing staff hospital/education/psychology 

*Nursing staff hospital/education/psychology/supply & distribution 

*Nursing staff hospital/education/standards 

*Nursing staff hospital/education/supply & distribution 

*Nursing staff hospital/legislation & jurisprudence/supply & distribution 

*Nursing staff hospital/organization & administration/standards 

*Nursing staff hospital/organization & administration/statistics & 

*Nursing staff hospital/organization & administration/supply & 

*Nursing staff hospital/psychology 

*Nursing staff hospital/psychology/standards 

*Nursing staff hospital/psychology/statistics & numerical data 

*Nursing staff hospital/psychology/supply & distribution 

*Nursing staff hospital/statistics & numerical data 

*Nursing staff hospital/supply & distribution 

*Nursing staff hospital/utilization 

*Nursing staff/education/organization & administration/psychology 

*Nursing theory 

*Nursing practice 

*Nursing supervisory 

*Nursing team 

*Nutrition assessment 

*Nutrition/education 

*Outcome assessment (health care)/economics (health care) 
A-21 

*Outcome and process assessment (health care)/methods 

*Outcome and process assessment (health care)/statistics & numerical data 

*Personnel administration hospital 

*Personnel management/*methods 

*Personnel selection 

*Personnel selection/*organization & administration 

*Personnel selection/trends 

*Personnel staffing and scheduling/*legislation & jurisprudence 

*Personnel staffing and scheduling/ economics/legislation & 

*Personnel staffing and scheduling/legislation & jurisprudence 

*Personnel staffing and scheduling/organization 

*Personnel staffing and scheduling/organization & administration 

*Personnel staffing and scheduling/standards 

*Personnel staffing and scheduling/statistics & numerical data 

*Personnel turnover 

*Personnel turnover/statistics & numerical data 

*Personnel turnover/statistics & numerical data/ trends 

*Professional-patient relations 

*Program development 

*Program evaluation 

*Programmed instruction/standards 

*Progressive patient care 

*Qualitative research 

*Quality indicators health care/standards 

*Quality of health care/legislation & jurisprudence 

*Quality of health care/legislation & jurisprudence/statistics & numerical 

*Quality of life 

*Restraint physical 

*Restraint physical/adverse effects 

*Resuscitation 

*Risk assessment 

*Risk management 

*Risk management/methods/organization & administration 

*Safety 

*Safety management 

*Salaries and fringe benefits 

*Staff development 

*Staff development/methods 

*Total quality management 

*Work schedule tolerance 

*Work schedule tolerance/psychology 

*Workload 

*Workload/economics 

*Workload/psychology 

*Workload/statistics & numerical data 

*Workplace 
A-22 

*Workplace/organization & administration/psychology 

*Workplace/psychology 

Academic medical centers/*manpower 

Academic medical centers/*organization & administration 

Academic medical centers/*organization & administration/*statistics & 

Academic medical centers/economics/*manpower/organization & administration 

Academic medical centers/economics/standards/statistics & numerical data 

Academic medical centers/manpower 

Access to information/*legislation & jurisprudence 

Accidental falls/*prevention & control 

Accidental falls/* statistics & numerical data 

Accidental falls/economics/statistics & numerical data 

Accidental falls/prevention & control 

Accidental falls/prevention & control/*statistic/prevention & control/*statistics & numerical data 

Accidental falls/prevention & control/*statistic/*statistics & numerical data 

Accidents occupational/*prevention & control 

Accidents occupational/*statistics & numerical data 

Accidents occupational/economics/*prevention & control/statistics 

Accidents occupational/economics/prevention & control/*statistics 

Accidents occupational/prevention & control 

Accidents/*statistics & numerical data 

Accreditation 

Accreditation/*legislation & jurisprudence 

Accreditation/*methods 

Accreditation/*standards 

Administrative personnel 

Adverse drug reaction reporting systems 

Adverse drug reaction reporting systems/*statistics & numerical data 

Adverse drug reaction reporting 

Systems/*utilization 

Adverse drug reaction reporting systems/standard 

Adverse drug reaction reporting 

Systems/statistics & numerical data 

Adverse drug reaction reporting systems/utilization 

Allied health personnel 

Allied health personnel/*psychology 

Allied health personnel/*supply & distribution 

Allied health personnel/*utilization 

Allied health personnel/economics/statistics & numerical data 

Allied health personnel/organization & administration 

Allied health personnel/psychology 

Allied health personnel/standards/supply & distribution 

Allied health personnel/statistics & numerical data/supply & distribution 

Allied health personnel/supply & distribution 

American Nurses' Association/organization & administration 

Analgesia/*nursing 
A-23 

Analgesia/methods/*nursing 

Analgesia/nursing/*standards 

Analgesia/nursing/*utilization 

Ancillary services hospital/*trends 

Ancillary services 

Bed occupancy/classification 

Bed occupancy/economics 

Bed occupancy/statistics & numerical data 

Bed rest/*adverse effects/nursing 

Bed rest/adverse effects/nursing 

Benchmarking/*methods 

Benchmarking/*methods/standards 

Benchmarking/*organization & administration 

Benchmarking/methods 

Benchmarking/organization & administration 

Benchmarking/standards 

Burnout professional 

Burnout professional/*diagnosis/*psychology 

Burnout professional/*epidemiology/*psychology 

Burnout professional/*epidemiology 

Burnout professional/*etiology 

Burnout professional/*etiology/psychology 

Burnout professional/*etiology/psychology 

Burnout professional/*prevention & control 

Burnout professional/*prevention & control/*psychology 

Burnout professional/*prevention & control/psychology 

Burnout professional/*psychology 

Burnout professional/classification/diagnosis/etiology/*prevention 

Burnout professional/complications/*epidemiology 

Burnout professional/diagnosis/*epidemiology/prevention & 

Burnout professional/diagnosis/*epidemiology/psychology 

Burnout professional/diagnosis/epidemiology/*psychology 

Burnout professional/diagnosis/epidemiology/psychology 

Burnout professional/diagnosis/etiology/*prevention & control 

Burnout professional/diagnosis/etiology/prevention & control/*psychology 

Burnout professional/diagnosis/physiopathology/*prevention & 

Burnout professional/epidemiology 

Burnout professional/epidemiology/*etiology 

Burnout professional/epidemiology/etiology/*psychology 

Burnout professional/epidemiology/etiology/prevention & 

Burnout professional/epidemiology/etiology/psychology 

Burnout professional/epidemiology/psychology 

Burnout professional/etiology/prevention & control 

Burnout professional/etiology/prevention & control/psychology 

Burnout professional/etiology/psychology 

Burnout professional/prevention control 
A-24 

Burnout professional/prevention & control/*psychology 

Burnout professional/prevention & control/psychology 

Burnout professional/psychology 

Cardiac surgical procedures/*adverse effects/*nursing 

Cardiac surgical procedures/*nursing 

Cardiac surgical procedures/*nursing/standards 

Cardiac surgical procedures/adverse effects/mortality/*nursing 

Cardiac surgical procedures/economics/*nursing 

Cardiac surgical procedures/nursing 

Cardiology service hospital/*manpower 

Cardiology service hospital/economics/manpower/*organization & 

Cardiopulmonary resuscitation/*education/*methods/nursing 

Cardiopulmonary resuscitation/education/*nursing 

Cardiovascular diseases/*nursing 

Case management 

Case management/*trends 

Case management/organization & administration* 

Causality 

Cause of death 

Censuses 

Centralized hospital services 

Centralized hospital services/*organization & administration 

Cerebrovascular accident/*nursing/rehabilitation 

Cerebrovascular accident/classification/nursing 

Cerebrovascular accident/nursing 

Cerebrovascular disorders/*nursing 

Cerebrovascular disorders/*nursing/*rehabilitation 

Cerebrovascular disorders/*nursing/rehabilitation 

Certificate of need/legislation & jurisprudence 

Certification/*organization & administration 

Certification/*standards 

Cesarean section/*nursing/psychology 

Clinical competence/*legislation & jurisprudence/*standards 

Clinical competence/*legislation & jurisprudence/standards 

Clinical competence/*standards 

Clinical competence/*statistics & numerical data 

Clinical competence/legislation & jurisprudence 

Clinical competence/legislation & jurisprudence/*standards 

Clinical competence/legislation & jurisprudence/standards 

Clinical competence/standards/*statistics & numerical data 

Clinical competence/statistics & numerical data 

Clinical nursing research/*methods 

Clinical nursing research/*organization & administration 

Clinical nursing research/method 

Clinical nursing research/organization & administration/*standards 

Clinical protocols 
A-25 

Clinical protocols/standards 

Collective bargaining 

Collective bargaining/*legislation & jurisprudence 

Collective bargaining/*organization & administration 

Collective bargaining/organization & administration 

Confounding factors (epidemiology) 

Confusion/*nursing 

Confusion/*nursing/psychology 

Confusion/etiology/nursing/*psychology 

Conscious sedation/*nursing 

Conscious sedation/adverse effects/*nursing 

Conscious sedation/nursing/*psychology 

Consumer satisfaction/*statistics & numerical data 

Continuity of patient care 

Continuity of patient care/*organization & administration 

Continuity of patient care/*standards 

Continuity of patient care/organization & administration 

Continuity of patient care/organization & administration/statistics & 

Contract services 

Contract service/*organization & administration 

Contract services/*standards 

Contract services/legislation & jurisprudence 

Contract services/statistics & numerical data/*utilization 

Contracts 

Coronary disease/*nursing 

Coronary disease/*nursing/surgery 

Cost control/methods 

Cost control/trends 

Cost of illness 

Costs and cost analysis/*methods 

Costs and cost analysis/economics 

Costs and cost analysis/statistics & numerical data 

Critical care/*manpower/methods 

Critical care/*manpower/standard 

Critical care/*methods 

Critical care/*organization & administration 

Critical care/economics/*manpower 

Critical pathways 

Critical pathway/*standards 

Cross infection/*epidemiology/*etiology 

Cross infection/*epidemiology/microbiology 

Cross infection/*epidemiology/transmission 

Cross infection/*microbiology 

Cross infection/diagnosis/drug therapy/*prevention & control/*transmission 

Cross infection/economics/*epidemiology/*etiology/prevention & control 

Cross infection/epidemiology/*microbiology/*transmission 
A-26 

Cross infection/epidemiology/*microbiology/prevention & 

Cross infection/epidemiology/*microbiology/transmission 

Cross infection/epidemiology/*prevention & control 

Cross infection/epidemiology/*prevention & control/virology 

Cross infection/epidemiology/etiology/*prevention & control 

Cross infection/epidemiology/microbiology/*prevention & 

Cross infection/epidemiology/microbiology/*transmission 

Cross infection/etiology 

Cross infection/etiology/*prevention & control 

Cross infection/microbiology/*prevention & 

Cross infection/microbiology/*prevention & control/transmission 

Cross infection/mortality/*prevention & control 

Cross infection/nursing/*prevention & control/*psychology 

Cross infection/prevention & control 

Cross infection/prevention & control/*transmission 

Data collection 

Data collection/*methods/*standards 

Data collection/ methods/standards 

Data collection/*methods/standards/*statistics & numerical data 

Data collection/methods 

Data collection/ methods/*standards 

Data collection/methods/standards 

Data display 

Data interpretation statistical/statistics & numerical data 

Day care/manpower/*organization & administration/statistics & numerical 

Decision making 

Organizational decubitus ulcer *classification/nursing/pathology 

Decubitus ulcer/*economics/epidemiology/*therapy 

Decubitus ulcer/*epidemiology/*prevention & control 

Decubitus ulcer/*etiology/*prevention & control 

Decubitus ulcer/*etiology/nursing/*prevention & control 

Decubitus ulcer/*nursing 

Decubitus ulcer/*nursing/*psychology 

Decubitus ulcer/*prevention & control 

Decubitus ulcer/economics/ epidemiology/*prevention & control 

Decubitus ulcer/epidemiology/etiology 

Decubitus ulcer/epidemiology/etiology/*prevention & control 

Decubitus ulcer/etiology 

Decubitus ulcers/prevention & control 

Decubitus ulcer/etiology/*prevention & control 

Decubitus ulcer/nursing/*prevention & control 

Delivery of health care 

Delivery of health care integrated 

Delivery of health care integrated/*manpower 

Delivery of health care integrated/*organization & administration 

Delivery of health care integrated/*standards 
A-27 

Delivery of health care integrated/organization & administration 

Delivery of health care/*economics 

Delivery of health care/*history 

Delivery of health care/*manpower 

Delivery of health care/*standards 

Delivery of health care/economics/standards/*trends 

Delivery of health care/organization & administration 

Delivery obstetric/*methods 

Delivery obstetric/*nursing/statistics & numerical data 

Diabetes mellitus/*nursing 

Diagnosis-related groups/*classification 

Direct service costs/*statistics & numerical data 

Direct service costs/statistics & numerical data 

Disease management 

Disease outbreaks/*prevention & control/statistics & numerical data 

Disease transmission professional-to-patient 

Disease transmission professional-to-patient/*prevention & control 

Disease transmission professional-to-patient/*statistics & numerical data 

Disease transmission professional-to-patient/prevention & control 

Disease transmission professional-to-patient/statistics & numerical data 

Drug administration schedule 

Drug monitoring/*nursing 

Drug monitoring/nursing/standards 

Drug monitoring/methods/nursing 

Drug monitoring/nursing/standards 

Economics nursing education continuing 

Education continuing/*methods 

Education nursing associate/*trends 

Education nursing baccalaureate/*methods 

Education nursing baccalaureate/*organization & administration 

Education nursing baccalaureate/*standards 

Education nursing baccalaureate/*trends 

Education nursing baccalaureate/standards 

Education nursing baccalaureate/statistics & numerical data 

Education nursing continuing 

Education nursing continuing/*manpower 

Education nursing continuing/*methods 

Education nursing continuing/*organization & administration 

Education nursing continuing/*standards 

Education nursing continuing/methods 

Education nursing continuing/methods/*standard 

Education nursing continuing/organization & administration 

Education nursing continuing/standards 

Education nursing continuing/statistics & numerical data 

Education nursing diploma programs 

Education nursing diploma programs/*standards 
A-28 

Education nursing graduate/*manpower 

Education nursing graduate/*organization & administration 

Education nursing graduate/*trends 

Education nursing/*organization & administration 

Education nursing/*statistics & numerical data 

Education nursing/economics 

Education nursing/economics/legislation & jurisprudence 

Education nursing/history 

Education nursing/methods 

Education nursing/standards 

Education nursing/standards/trends 

Education nursing/trends 

Efficiency organizational/standards 

Emergencies/*nursing 

Emergency nursing 

Emergency nursing/*education 

Emergency nursing/*education/*methods 

Emergency nursing/*education/standards 

Emergency nursing/*manpower 

Emergency nursing/*methods 

Emergency nursing/*methods/standards 

Emergency nursing/*organization & administration 

Nursing/*standards 

Emergency nursing/*standards/trends 

Emergency nursing/*statistics & numerical data 

Emergency nursing/education/*methods 

Emergency nursing/education/*methods/standards 

Emergency nursing/education/*organization & administration 

Emergency nursing/education/*standards 

Emergency nursing education/organization & administration 

Emergency nursing/manpower 

Emergency nursing/manpower/*standards 

Emergency nursing/manpower/standards 

Emergency nursing/standards 

Emergency service hospital/economics/*manpower 

Emergency service hospital/economics/*manpower/organization & 

Employee discipline 

Employee performance appraisal/*methods/standards 

Employment/*legislation & jurisprudence 

Employment/*organization & administration 

Employment/*psychology 

Epidemiologic studies 

Ethics nursing evidence-based medicine/*organization & administration 

Evidence-based medicine/organization & administration 

Evidence-based medicine/standards 

Foreign medical graduates 
A-29 

Foreign medical graduates/*legislation & jurisprudence/supply & 

Foreign medical graduates/psychology/statistics & numerical data 

Foreign professional personnel 

Foreign professional personnel/*education 

Foreign professional personnel/*education/*psychology/supply & 

Foreign professional personnel/*education/psychology 

Foreign professional personnel/*education/psychology/supply & distribution 

Foreign professional personnel/*education/supply & distribution 

Foreign professional personnel/*history 

Foreign professional personnel/*legislation & jurisprudence 

Foreign professional personnel/*legislation & jurisprudence/supply & 

Foreign professional personnel/*psychology 

Foreign professional personnel/*psychology/supply & distribution 

Foreign professional personnel/*standards 

Foreign professional personnel/*supply & distribution 

Foreign professional personnel/*utilization 

Foreign professional personnel/education 

Foreign professional personnel/education/*psychology 

Foreign professional personnel/education/*psychology/supply & distribution 

Foreign professional personnel/education/*supply& distribution 

Foreign professional personnel/education/legislation & 

Foreign professional personnel/education/psychology/*supply & distribution 

Foreign professional personnel/legislation & jurisprudence/supply 

Foreign professional personnel/standards 

Foreign professional personnel/standards/statistics & numerical 

Foreign professional personnel/supply & distribution 

Foreign professional personnel/utilization 

Government agencies 

Government agencies/organization & administration 

Government regulation 

Guideline adherence/*standards 

Health care coalitions/*organization & administration 

Health care costs 

Health care costs/standards 

Health care costs/statistics & numerical data 

Health care rationing 

Health care rationing/*methods 

Health care rationing/*organization & administration 

Health care reform 

Health care reform/*organization & administration 

Health care reform/*trends 

Health care reform/economics/*standards 

Health care reform/organization & administration 

Health care reform/trends 

Health care sector 

Health care sector/trends 
A-30 

Health insurance portability and accountability act 

Health insurance portability and accountability act/legislation 

Health maintenance organizations/manpower 

Health manpower 

Health manpower/*classification/statistics & numerical data 

Health manpower/*economics 

Health manpower/*statistics & numerical data/trends 

Health manpower/*trends 

Health manpower/statistics & numerical data/*trends 

Health manpower/trends 

Health personnel/*education 

Health services accessibility/*organization & administration 

Health services accessibility/*standards 

Health services accessibility/economics/standards 

Health services accessibility/organization & administration 

Health services accessibility/standards/*statistics & numerical data 

Health services misuse/*statistics & numerical data 

Health services misuse/economics/*statistics & numerical data 

Health services needs and demand/*organization & administration 

Health services needs and demand*statistics & numerical data 

Health services needs and demand/trends 

Health services research/*methods/*standards 

Health services research/*organization & administration 

Heart arrest/nursing 

Heart diseases/nursing 

Heart failure congestive/*nursing 

Heart failure congestive/classification/nursing 

Heart failure congestive/complications/*nursing 

Holistic nursing/*education/*organization & administration 

Holistic nursing/*organization & administration 

Holistic nursing/*standards 

Holistic nursing/education/*standards 

Holistic nursing/methods/*standards 

Hospital administration 

Hospital administration*/economics 

Hospital administration*/standards 

Hospital administration/*economics/*legislation & jurisprudence 

Hospital administration/*methods 

Hospital administration/*organization & administration 

Hospital administration/economic 

Hospital administration/education 

Hospital administration/manpower/*statistics & numerical data 

Hospital administration/methods 

Hospital administrators 

Hospital administrators/*organization & administration 

Hospital administrators/*supply & distribution 
A-31 

Hospital administrators/organization & administration/psychology 

Hospital administrators/psychology/*supply & distribution 

Hospital administrators/supply & distribution 

Hospital departments/*organization & administration 

Hospital departments/*organization & administration/statistics &numerical 

Hospital departments/*standards 

Hospital design and construction economics/*legislation & jurisprudence 

Hospital design and construction/standards 

Hospital distribution systems 

Hospital distribution systems/*standards 

Hospital distribution systems/organization & administration/ 

Hospital mortality/*trends 

Hospital mortality/trends 

Hospital planning/*organization & administration 

Hospital records 

Hospital restructuring/*manpower 

Hospital restructuring/*standard 

Hospital restructuring/*trends 

Hospital restructuring/manpower 

Hospital restructuring/manpower/*organization & administration 

Hospital restructuring/manpower/methods 

Hospital restructuring/manpower/organization & administration/*trends 

Hospital restructuring/manpower/standards 

Hospital restructuring/organization & administration 

Hospital restructuring/organization & administration/*standards 

Hospital restructuring/trends 

Hospital units/*economics/manpower 

Hospital units*/economics/organization & administration 

Hospital units/*legislation & jurisprudence/*manpower 

Hospital units/*manpower 

Hospital units/*manpower/organization & administration 

Hospital units/*organization & administration 

Hospital units/*standards 

Hospital units/*statistics & numerical data 

Hospital units/*supply & distribution 

Hospital units*/utilization 

Hospital units/classification/*standards 

Hospital units/classification/manpower 

Hospital units/economics/*organization & administration 

Hospital units/economics/manpower/organization & administration 

Hospital units/economics/organization & administration/*standards 

Hospital units/manpower 

Hospital units/manpower/*organization & administration 

Hospital units/manpower/*organization & administration/statistics & 

Hospital units/organization & administration 

Hospital units/organization & administration/*standards 
A-32 

Hospital units/organization & administration/*statistics & numerical data 

Hospital units/organization & administration/*trends 

Hospital units/standards 

Hospital/*manpower/standards/utilization 

Hospitalization/*statistics & numerical data 

Hospitalization/statistics & numerical data 

Hospitals 

Hospitals community 

Hospitals community/*legislation & jurisprudence 

Hospitals community/*manpower/organization & administration 

Hospitals community/*organization & administration 

Hospitals community/legislation & jurisprudence 

Hospitals community/manpower 

Hospitals community/manpower/organization & administration 

Hospitals community/organization & administration 

Hospitals community/organization & administration/*standards 

Hospitals community/standards 

Hospitals district/manpower 

Hospitals general/classification/*manpower 

Hospitals general/manpower 

Hospitals general/manpower/organization & administration 

Hospitals general/standards 

Hospitals general/statistics & numerical data 

Hospitals group practice/*manpower/utilization 

Hospitals maternity 

Hospitals maternity/manpower 

Hospitals municipal/*manpower 

Hospitals pediatric 

Hospitals pediatric/*organization & administration/standards 

Hospitals pediatric/*standards 

Hospitals pediatric/*standards/statistics & numerical data 

Hospitals pediatric/manpower 

Hospitals pediatric/manpower/*organization & administration 

Hospitals private 

Hospitals private/*manpower 

Hospitals private/economics/manpower 

Hospitals private/organization & administration 

Hospitals psychiatric/*manpower 

Hospitals psychiatric/manpower/*statistics & numerical data 

Hospitals psychiatric/manpower/statistics & numerical data 

Hospitals psychiatric/organization & administration/*standards 

Hospitals public/*manpower 

Hospitals public/*organization & administration 

Hospitals public/*organization & administration/statistics & numerical 

Hospitals public/*standards 

Hospitals public/*statistics & numerical data 
A-33 

Hospitals public/economics/manpower 

Hospitals public/manpower/*standards 

Hospitals public/manpower/organization & administration 

Hospitals public/organization & administration 

Hospitals public/organization & administration* 

Hospitals public/organization & administration/standards 

Hospitals public/organization & administration/standards/*utilization 

Hospitals public/standards 

Hospitals public/utilization 

Hospitals rural 

Hospitals rural/*organization & administration 

Hospitals special/organization & administration/standards 

Hospitals state/manpower/*statistics & numerical data 

Hospitals state/manpower/statistics & numerical data 

Hospitals teaching/*organization & administration 

Hospitals teaching/*organization & administration/utilization 

Hospitals teaching/*standards 

Hospitals teaching/*statistics & numerical data 

Hospitals teaching/economics/manpower/organization & administration 

Hospitals teaching/manpower 

Hospitals teaching/manpower/*organization & administration/standards 

Hospitals teaching/manpower/*standards 

Hospitals university 

Hospitals university/*economics/utilization 

Hospitals university/*manpower 

Hospitals university/*standards 

Hospitals university/economics 

Hospitals university/economics/organization & administration 

Hospitals university/manpower 

Hospitals university/manpower/organization & administration/statistics & 

Hospitals university/manpower/statistics & numerical data 

Hospitals urban 

Hospitals urban/*manpower 

Hospitals urban/manpower/*standards 

Hospitals veterans/*standards/statistics & numerical data 

Hospitals veterans/manpower 

Hospitals veterans/manpower/*standards 

Hospitals/*manpower 

Hospitals/*manpower/trends 

Hospitals/*statistics & numerical data 

Hospitals/classification/*manpower/statistics & numerical data 

Hospitals/statistics & numerical data 

Iatrogenic disease/prevention & control 

Infection control/methods/standards 

Infection control/organization & administration/*standards 

Infection/epidemiology/etiology/inpatients 
A-34 

Inpatients/*classification 

Inpatients/*education 

Inpatients/*legislation & jurisprudence/*psychology 

Inpatients/*psychology 

Inpatients/*psychology/statistics & numerical data 

Inpatients/*statistics & numerical data 

Inpatients/classification 

Inpatients/education/*psychology/inpatients/history/psychology 

Intensive care units neonatal/economics/*manpower 

Intensive care units neonatal/economics/manpower/utilization 

Intensive care units neonatal/manpower 

Intensive care units neonatal/manpower/*organization & administration 

Intensive care units neonatal/manpower/*statistics & numerical data 

Intensive care units pediatric 

Intensive care units pediatric/*economics/manpower 

Intensive care units pediatric/economics/manpower/utilization 

Intensive care units pediatric/manpower/*organization & administration 

Intensive care units pediatric/organization & administration/*standards 

Intensive care units/*economics 

Intensive care units/*legislation & jurisprudence/*manpower 

Intensive care units/*manpower/*utilization 

Intensive care units/*manpower/organization & administration 

Intensive care units/*manpower/organization & administration/statistics & 

Intensive care units/*manpower/standards 

Intensive care units/economics/*manpower 

Intensive care units/economics/manpower 

Intensive care/manpower/*organization & administration 

Intensive care/methods/*standards 

Interdisciplinary communication 

Internal medicine/manpower/*standards 

Internal medicine/organization & administration 

Interpersonal relations 

Intervention studies on accreditation of healthcare 

Joint Commission on Accreditation of Healthcare Organizations 

Labor unions 

Labor unions/*organization & administration 

Labor unions/organization & administration 

Legislation nursing 

Length of stay/*economics 

Length of stay/economics/*statistics & numerical data 

Length of stay/trends 

Licensure nursing 

Licensure nursing/*legislation & jurisprudence 

Licensure nursing/legislation & jurisprudence 

Licensure nursing/statistics & numerical data 

Malpractice 
A-35 

Malpractice/*economics/*legislation & jurisprudence 

Malpractice/*legislation & jurisprudence 

Malpractice/legislation & jurisprudence 

Malpractice/legislation & jurisprudence/*statistics & numerical data 

Managed care programs 

Managed care programs/*economics 

Managed care programs/*organization & administration 

Managed care programs/economics 

Managed care programs/manpower 

Managed care programs/standards 

Maternal-child nursing 

Maternal-child nursing/*manpower 

Maternal-child nursing/*organization & administration 

Maternal-child nursing/*standards 

Maternal-child nursing/*trends 

Maternal-child nursing/education/*methods 

Maternal-child nursing/education/*organization & administration 

Maternal-child nursing/education/organization & administration 

Maternal-child nursing/manpower/*standards 

Maternal-child nursing/methods/*standards 

Medical errors/*adverse effects/*prevention & control 

Medical errors/*nursing/prevention & control/*statistics & numerical data 

Medical errors/*nursing/statistics & numerical data 

Medical errors/nursing/prevention & control/*statistics & numerical data 

Medical staff hospital/*economics/supply & distribution 

Medication errors/*nursing/standards/statistics & numerical data 

Medication errors/methods/nursing/*prevention &control 

Neonatal nursing/*manpower/*methods 

Neonatal nursing/*organization & administration 

Neonatal nursing/*standards 

Neonatal nursing/education/*organization & administration 

Night care/*organization & administration 

Nurse administrators/*education 

Nurse administrators/*education/*organization & administration/psychology 

Nurse administrators/*legislation & jurisprudence 

Nurse administrators/*organization & administration 

Nurse administrators/*organization & administration/*psychology 

Nurse administrators/*organization & administration/psychology 

Nurse administrators/economics/supply & distribution 

Nurse administrators/education 

Nurse administrators/education/*organization & administration 

Nurse administrators/education/*psychology 

Nurse administrators/education/organization & administration/*psychology 

Nurse administrators/education/organization & administration/psychology 

Nurse administrators/legislation & jurisprudence/psychology 

Nurse administrators/statistics & numerical data 
A-36 

Nurse clinicians 

Nurse clinicians/*organization & administration 

Nurse clinicians/*organization & administration/*psychology 

Nurse clinicians/*organization & administration/psychology 

Nurse clinicians/*organization & administration/standards 

Nurse clinicians/*standards 

Nurse clinicians/*supply & distribution 

Nurse clinicians/education 

Nurse clinicians/education/*organization & administration 

Nurse clinicians/education/*organization & administration/psychology 

Nurse clinicians/education/standards/supply & distribution 

Nurse clinicians/legislation & jurisprudence 

Nurse clinicians/organization & administration 

Nurse clinicians/psychology/*supply & distribution 

Nurse's role* 

Nurse's role/*psychology 

Nurse-patient relations/*ethics 

Nurses' aides 

Nurses' aides/*economics/education/supply & distribution 

Nurses' aides/*education 

Nurses' aides/*organization & administration/psychology 

Nurses' aides/*psychology 

Nurses' aides/*standards 

Nurses' aides/distribution 

Nurses' aides/education/*organization & administration 

Nurses' aides/education/*organization & administration/psychology 

Nurses' aides/education/*psychology 

Nurses' aides/education/*supply & distribution 

Nurses' aides/education/*utilization 

Nurses' aides/education/organization & administration 

Nurses' aides/education/organization & administration/psychology 

Nurses' aides/education/psychology 

Nurses' aides/education/supply & distribution 

Nurses' aides/legislation & jurisprudence 

Nurses' aides/legislation & jurisprudence/utilization 

Nurses' aides/organization & administration 

Nurses' aides/organization & administration/psychology 

Nurses' aides/psychology/*supply & distribution 

Nurses' aides/standards 

Nurses' aides/statistics & numerical data/*utilization 

Nurses/*organization & administration 

Nurses/*psychology 

Nurses/economics/organization & administration/utilization 

Nurses/economics/statistics & numerical data/*supply & distribution 

Nurses/psychology 

Nurses/psychology/*statistics & numerical data 
A-37 

Nurses/supply & distribution 

Nursing administration research/*education 

Nursing administration research/*methods 

Nursing administration research/*methods/standards 

Nursing administration research/*methods/statistics & numerical data 

Nursing administration research/*organization & administration 

Nursing administration research/methods 

Nursing administration research/methods/standards 

Nursing administration research/organization & administration 

Nursing assessment 

Nursing assessment/*ethics/methods 

Nursing assessment/*legislation & jurisprudence 

Nursing assessment/*methods 

Nursing assessment/*methods/*statistics & numerical data 

Nursing assessment/*methods/standards 

Nursing assessment/*organization & administration 

Nursing assessment/methods/standards/statistics & numerical data 

Nursing audit/*methods 

Nursing audit/*organization & administration 

Nursing audit/organization & administration 

Nursing care 

Nursing care/*classification 

Nursing care/*classification/methods 

Nursing care/*methods 

Nursing care/*methods/*psychology 

Nursing care/*psychology 

Nursing care/*psychology/*standards 

Nursing care/*standards/statistics & numerical data 

Nursing care/*utilization 

Nursing care/classification 

Nursing care/classification/*methods/standards/*statistics & numerical 

Nursing care/classification/*psychology/*standards 

Nursing care/manpower/methods/*statistics & numerical data 

Nursing care/methods/*psychology 

Nursing care/methods/organization & administration 

Nursing care/organization & administration 

Nursing care/psychology/standards 

Nursing care/statistics & numerical data 

Nursing diagnosis 

Nursing diagnosis/*standards 

Nursing diagnosis/*utilization 

Nursing education research 

Nursing evaluation research/*methods 

Nursing evaluation research/*methods/standards 

Nursing evaluation research/*organization & administration 

Nursing evaluation research/methods 
A-38 

Nursing methodology research 

Nursing methodology research/*methods 

Nursing methodology research/*methods/*standards 

Nursing methodology research/*methods/standards 

Nursing methodology research/education/*methods 

Nursing methodology research/methods/standards 

Nursing process 

Nursing process/*organization & administration 

Nursing process/*statistics & numerical data 

Nursing process/classification/standards/*statistics & numerical data 

Nursing records 

Nursing records*legislation & jurisprudence 

Nursing records/*standards 

Nursing records/*standards/statistics & numerical data 

Nursing records/legislation & jurisprudence/*standards 

Nursing records/standards 

Nursing records/standards/statistics & numerical data 

Nursing records/statistics & numerical data 

Nursing research/*methods/standards 

Nursing research/*methods/statistics & numerical data 

Nursing research/*organization & administration 

Nursing research/education 

Nursing research/education/*organization & administration 

Nursing service hospital 

Nursing service hospital/*classification 

Nursing service hospital/*economics 

Nursing service hospital/*history/manpower/organization & administration 

Nursing service hospital/*manpower 

Hospital/*manpower/*standards 

Nursing service hospital/*organization & administration 

Nursing service hospital/*organization & administration/trends 

Nursing service hospital/classification/*utilization 

Nursing service hospital/classification/manpower/*organization 

Nursing service hospital/economics 

Nursing service hospital/economics/*organization & administration 

Nursing service hospital/economics/*standards 

Nursing service hospital/economics/*trends 

Nursing service hospital/economics/manpower/*organization & 

Nursing service hospital/manpower/*organization & 

Nursing service hospital/manpower/*organization & administration 

Nursing service hospital/manpower/*organization & administration/trends 

Nursing service 

Nursing staff 

Nursing staff hospital 

Nursing staff hospital/*economics 

Nursing staff hospital/*economics/*legislation & jurisprudence 
A-39 

Nursing staff hospital/*economics/*supply & distribution 

Nursing staff hospital/*economics/legislation & jurisprudence 

Nursing staff hospital/*economics/legislation & jurisprudence/statistics 

Nursing staff hospital/*economics/organization & administration/trends 

Nursing staff hospital/*economics/psychology 

Nursing staff hospital/*economics/standards 

Nursing staff hospital/*economics/standards/supply & distribution 

Nursing staff hospital/*economics/supply & distribution 

Nursing staff hospital/*education 

Nursing staff hospital/*education/*legislation & jurisprudence 

Nursing staff hospital/*education/*organization & 

Nursing staff hospital/*education/*organization administration 

Nursing staff hospital/*education/*psychology 

Nursing staff hospital/*education/*psychology/supply & distribution 

Nursing staff hospital/*education/*supply & distribution 

Nursing staff hospital/*education/*supply & distribution/trends 

Nursing staff hospital/*education/organization 

Nursing staff hospital/organization & administration 

Nursing staff hospital/*ethics/organization & administration/*psychology 

Nursing staff hospital/*ethics/psychology 

Nursing staff hospital/*legislation & jurisprudence 

Nursing staff hospital/*legislation & jurisprudence/*standards 

Nursing staff hospital/*legislation & jurisprudence/statistics 

Nursing staff hospital/*legislation & jurisprudence/supply & distribution 

Nursing staff hospital/*organization & 

Nursing staff hospital/*organization & administration/*psychology 

Nursing staff hospital/*organization & administration/*statistics & 

Nursing staff hospital/*organization & administration/*supply & 

Nursing staff hospital/*organization & administration/psychology 

Nursing staff hospital/economics/*legislation & jurisprudence 

Nursing staff hospital/economics/*statistics & numerical data 

Nursing staff hospital/economics/*supply & distribution/utilization 

Nursing staff hospital/economics/*utilization 

Nursing staff hospital/economics/education 

Nursing staff hospital/legislation & jurisprudence 

Nursing staff hospital/legislation & jurisprudence/*organization & 

Nursing staff hospital/legislation & jurisprudence/psychology/*supply & 

Nursing staff hospital/organization & administration/*standards 

Nursing staff hospital/organization & administration/*utilization 

Nursing staff hospital/standards/*utilization 

Nursing staff hospital/standards/supply & distribution 

Nursing staff hospital/statistics & numerical data 

Nursing staff hospital/statistics & numerical data/*supply & distribution 

Nursing staff hospital/supply & distribution 

Nursing staff hospital/supply & distribution/*trends 

Nursing staff hospital/supply & distribution/*utilization 
A-40 

Nursing staff hospital/trends 

Nursing theory 

Nursing practical 

Nursing practical 

Nursing practical methods 

Nursing practical/*legislation & jurisprudence 

Nursing practical/*manpower 

Nursing practical/*statistics & numerical data 

Nursing practical/economics/*manpower 

Nursing practical/education 

Nursing practical/education/*manpower 

Nursing practical/education/organization & administration 

Nursing practical/education/standards 

Nursing practical/legislation & jurisprudence 

Nursing practical/standards 

Nursing practical/statistics & numerical data 

Nursing supervisory/*economics 

Nursing supervisory/*legislation & jurisprudence 

Nursing supervisory/*methods 

Nursing supervisory/*organization & administration 

Nursing supervisory/*standards 

Nursing supervisory/economics 

Nursing supervisory/legislation & jurisprudence 

Nursing supervisory/methods 

Nursing supervisory/organization & administration 

Nursing supervisory/standards 

Nursing team 

Nursing team/*organization & administration 

Nursing team/organization & administration 

Nursing team/statistics & numerical data 

Nursing/*manpower 

Nursing/*manpower/trends 

Nursing/*organization & administration 

Oncologic nursing 

Oncologic nursing/*manpower 

Oncologic nursing/*methods/standards 

Oncologic nursing/*organization & administration 

Oncologic nursing/*standards 

Oncologic nursing/economics/education/*manpower 

Oncologic nursing/education 

Oncologic nursing/legislation & jurisprudence 

Oncologic nursing/manpower 

Oncologic nursing/manpower/*standards 

Oncologic nursing/methods/*standards 

Oncologic nursing/statistics & numerical data 

Orthopedic nursing/*organization & administration/standards 
A-41 

Outcome assessment (health care)/economics/*statistics & numerical data 

Outcome assessment (health care) /methods 

Outcome assessment (health care)/organization & administration 

Outcome assessment (health care)/standards 

Outcome and process assessment (health care)/*statistics & numerical data 

Outcome and process assessment (health care)/economics 

Process assessment (health care)/methods 

Outcome and process assessment (health care)/organization & administration 

Pain postoperative/*nursing 

Pain postoperative/diagnosis/etiology/*nursing/*prevention & control 

Pain postoperative/diagnosis/etiology/*nursing/psychology 

Pain/*nursing 

Pain/*nursing/*therapy 

Pain/diagnosis/nursing 

Patient care 

Patient care planning 

Patient care planning/*classification 

Patient care planning/*economics/standards 

Patient care planning/*methods 

Patient care planning/*organization & administration 

Patient care planning/economics/statistics & numerical data 

Patient care planning/organization & administration 

Patient care planning/organization & administration/*standards 

Patient care team/*organization & administration 

Patient care team/*standards 

Patient care team/*statistics & numerical data 

Patient care team/economics 

Patient care team/economics/*organization & administration 

Patient care team/economics /statistics & numerical data/*utilization 

Patient care team/organization & administration 

Patient care team/standards 

Patient care/*economics 

Patient care/economics 

Patient readmission 

Patient readmission/*statistics & numerical data 

Patient readmission/economics 

Patient readmission/statistics & numerical data 

Patient transfer/manpower/*organization & administration/standards 

Patient transfer/methods/*organization & administration 

Patient transfer/methods/*standards 

Patient transfer/methods/organization & administration/*standard 

Patient-centered care 

Patient-centered care/*economics 

Patient-centered care/*ethics/organization & administration 

Patient-centered care/*manpower 

Patient-centered care/*manpower/*organization & administration 
A-42 

Patient-centered care/*methods 

Patient-centered care/*organization & administration 

Patient-centered care/*organization & administration/*statistics 

Patient-centered care/*standards 

Patient-centered care/*trends 

Patient-centered care/economics/*manpower/standards 

Patient-centered care/history 

Patient-centered care/methods 

Patient-centered care/methods/*organization & administration 

Patient-centered care/methods/*standards 

Patient-centered care/organization & administration 

Care/standards 

Pediatric nursing 

Pediatric nursing/*education 

Pediatric nursing/*education/*organization & administration 

Pediatric nursing/*history 

Pediatric nursing/*legislation & jurisprudence 

Pediatric nursing/*manpower 

Pediatric nursing/*methods 

Pediatric nursing/*methods/standards 

Pediatric nursing/*organization & administration 

Pediatric nursing/*organization & administration/*standards 

Pediatric nursing/*standards 

Pediatric nursing/*statistics & numerical data 

Pediatric nursing/education 

Pediatric nursing/education/*manpower 

Pediatric nursing/education/*methods 

Pediatric nursing/education/*methods/standards 

Pediatric nursing/education/*organization & administration 

Pediatric nursing/education/*standards 

Pediatric nursing/history 

Pediatric nursing/manpower 

Pediatric nursing/manpower/standards 

Pediatric nursing/methods 

Pediatric nursing/organization & administration 

Pediatric nursing/statistics & numerical data 

Perioperative care/manpower 

Perioperative care/nursing/organization & administration 

Perioperative nursing 

Perioperative nursing/*education 

Perioperative nursing/*manpower 

Perioperative nursing/*manpower/standards 

Perioperative nursing/*manpower/statistics & numerical data 

Perioperative nursing/*methods 

Perioperative nursing/*organization & administration 

Perioperative nursing/*organization & administration/standards 
A-43 

Perioperative nursing/*standards 

Perioperative nursing/education 

Perioperative nursing/education/*manpower 

Perioperative nursing/education/*methods 

Perioperative nursing/education/*methods/*standards 

Perioperative nursing/education/methods/standards 

Personal autonomy 

Personal satisfaction 

Personal space 

Personality 

Personality inventory 

Personnel administration hospital 

Personnel administration hospital/*legislation & jurisprudence 

Personnel administration hospital/*methods 

Personnel administration hospital/*methods/statistics & numerical data 

Personnel administration hospital/*standards 

Personnel administration hospital/*statistics & numerical data 

Personnel administration hospital/economics 

Personnel administration hospital/economics/*methods/trends 

Personnel administration hospital/legislation & jurisprudence/*standards 

Personnel administration hospital/methods 

Personnel administration hospital/standards 

Personnel administration hospital/standards/statistics & numerical data 

Personnel management/*legislation & jurisprudence 

Personnel management/*methods 

Personnel management/*organization & administration 

Personnel management/*standards 

Personnel management/*trends 

Personnel management/economics/*methods 

Personnel management/methods 

Personnel management/standards 

Personnel staffing and scheduling information 

Personnel staffing and scheduling information systems 

Personnel staffing and scheduling information systems/*organization & 

Personnel staffing and scheduling/*classification 

Personnel staffing and scheduling/*classification/organization & 

Personnel staffing and scheduling/*economics/organization & administration 

Personnel staffing and scheduling/*legislation & 

Personnel staffing and scheduling/*legislation & jurisprudence/standards 

Personnel staffing and scheduling/*organization 

Personnel staffing and scheduling/*organization & administration/standards 

Personnel staffing and scheduling/*statistics & numerical data/*trends 

Personnel staffing and scheduling/*statistics & numerical data/trends 

Personnel staffing and scheduling/economics/*legislation & jurisprudence 

Personnel staffing and scheduling/legislation & jurisprudence/standards 

Personnel staffing and scheduling/organization & administration/*standards 
A-44 

Personnel staffing and scheduling/organization & administration/standards 

Personnel staffing and scheduling/organization & administration/statistics 

Personnel turnover/*statistics & numerical data 

Personnel turnover/*trends 

Personnel turnover/economics 

Personnel turnover/economics/*statistics & numerical data 

Personnel turnover/statistics & numerical data/*trends 

Personnel hospital/*statistics & numerical data 

Personnel hospital/classification/economics/*supply & distribution 

Personnel hospital/economics 

Personnel hospital/education/*standards 

Personnel hospital/education/psychology 

Personnel hospital/legislation & jurisprudence 

Personnel hospital/standards/*supply & distribution 

Personnel hospital/statistics & numerical data/*utilization 

Personnel hospital/statistics & numerical data/supply & distribution 

Philosophy nursing 

Pneumonia/classification/nursing 

Postnatal care/economics/manpower/*organization & postoperative care/*nursing/*standards 

Postoperative care/methods/nursing 

Postoperative care/nursing/*standards 

Postoperative care/nursing/psychology/statistics & numerical data 

Preoperative care/*preoperative care/economics/* 

Primary health care 

Primary health care/*manpower 

Primary health care/*organization & administration 

Primary health care/organization & administration 

Primary nursing care 

Primary nursing care/*manpower 

Primary nursing care/*methods 

Primary nursing care/*organization & administration 

Primary nursing care/manpower 

Primary nursing care/methods/*standard 

Primary nursing care/organization & administration 

Primary nursing care/organization & administration/*standards 

Primary nursing care/statistics & numerical data 

Process assessment (health care) 

Process assessment (health care) /organization & administration 

Process assessment (health care)/methods 

Professional competence 

Professional competence/*standards 

Progressive patient care 

Progressive patient care/*manpower 

Progressive patient care/*organization & administration 

Progressive patient care/classification/*standards 

Progressive patient care/organization & administration 
A-45 

Qualitative research 

Quality assurance health care/*legislation & jurisprudence 

Quality assurance health care/*methods 

Quality assurance health care/*organization & administration 

Quality assurance health care/*statistics & numerical data 

Quality assurance health care/economics/trends 

Quality assurance health care/legislation & jurisprudence 

Quality assurance health care/methods 

Quality assurance health care/organization & administration 

Quality assurance health care/standards 

Quality assurance health care/statistics & numerical data 

Quality control 

Quality indicators health care 

Quality indicators health care/organization & administration 

Quality indicators health care/*statistics & numerical data 

Quality indicators health care/legislation & jurisprudence 

Quality indicators health care/standards 

Quality of health care/*legislation & 

Quality of health care/*statistics & numerical data 

Quality of health care/*trends 

Quality of health care/legislation & jurisprudence 

Quality of health care/organization & administration 

Quality of health care/organization & administration/standards 

Quality of health care/standards 

Rehabilitation nursing/*legislation & jurisprudence 

Rehabilitation nursing/*manpower/*methods 

Restraint physical 

Resuscitation 

Resuscitation orders 

Resuscitation/*education/standards 

Resuscitation/*standards/statistics & numerical data 

Risk management/*organization & administration 

Risk management/*organization & administration/statistics & numerical data 

Risk management/*standards 

Risk management/*statistics & numerical data 

Safety management/* 

Safety management/*methods 

Safety management/*organization & administration 

Safety management/*standards 

Safety management/legislation & jurisprudence 

Safety management/methods 

Safety management/methods/standards 

Safety management/organization & administration 

Safety/*legislation & jurisprudence 

Safety/standards 

Total quality management/*organization & administration 
A-46 

Total quality management/organization & administration 

Unnecessary procedures/nursing/statistics & numerical data 

Urinary catheterization/*adverse effects/*nursing 

Urinary catheterization/adverse effects/*nursing 

Urinary catheterization/nursing/*standards 

Work schedule tolerance 

Workload/*classification/economics 

Workload/*legislation & jurisprudence 

Workload/*legislation & jurisprudence/*standards 

Workload/*legislation & jurisprudence/standards 

Workload/*psychology 

Workload/*psychology/statistics & numerical data 

Workload/*standards 

Workload/economics/statistics & numerical data 

Workload/legislation & jurisprudence 

Workload/legislation & jurisprudence/*standards/statistics & numerical data 

Workload/legislation & jurisprudence/standards 

Workload/legislation & jurisprudence/statistics & numerical data 

Workload/psychology/*statistics & numerical data 

Workload/statistics & numerical data 

Workplace 

Workplace/*organization & administration 
B-1 

Appendix B: List of Excluded Studies 

1. Anonymous. Temporary or pseudo-permanent? Qld 

Nurse. Nov-Dec 1990;9(6):13. Comment. 

2. Anonymous. Four easy ways to lose a job in nursing. 

Am J Nurs. Jun 1990;90(6):27-28. Comment. 

3. Anonymous. Time oriented score system (TOSS): a 

method for direct and quantitative assessment of 

nursing workload for ICU patients. Italian Multicenter 

Group of ICU research (GIRTI). Intensive Care Med. 

1991;17(6):340-345. Not eligible target population.

4. Anonymous. Flexible scheduling and part-time work. 

Focus Crit Care. Jun 1991;18(3):195-196, 198-199. 

Comment. 

5. Anonymous. Infamous acuity system. Am J Nurs. Jun 

1991;91(6):14. Comment. 

6. Anonymous. An HIV-infected nurse must be 

reinstated. Am J Nurs. Dec 1992;92(12):9. News. 

7. Anonymous. A case in point: "catch-all" clause 

protects nurses' rights. Mich Nurse. Mar 

1992;65(3):19. Legal cases.

8. Anonymous. Draft guidelines on preventable 

medication errors. Am J Hosp Pharm. Mar 

1992;49(3):640-648. Guideline. 

9. Anonymous. Humanising the shiftwork systems. Qld 

Nurse. May-Jun 1992;11(3):23. Comment. 

10. Anonymous. Nursing "cannibalistic" toward its 

elders, too. Nurs Manage. Oct 1993;24(10):8. Letter. 

11. Anonymous. Mandatory AIDS testing could create 

hospital staffing problems. N J Med. May 

1993;90(5):411. News. 

12. Anonymous. Measuring neonatal nursing workload. 

Northern Neonatal Network. Arch Dis Child. May 

1993;68(5 Spec No):539-543. Not eligible target 

population. 

13. Anonymous. Self-scheduling guidelines. Pediatric 

unit. Mercy Hospital and Medical Center, San Diego, 

California. Aspens Advis Nurse Exec. Aug 

1993;8(11):suppl 1. Guideline. 

14. Anonymous. Low nursing staffing levels causing 

stress. OR Manager. Mar 1993;9(3):15, 26. Comment. 

15. Anonymous. The challenge of operating within 

staffing budgets on the maternity unit at New England 

Memorial Hospital despite a fluctuating census. Qual 

Lett Healthc Lead. Feb 1993;5(1):15-17. No 

association tested. 

16. Anonymous. NLN survey informs Dept. of Labor 

study. NLN Research & Policy PRISM Jun 

1994;2(2):4-8. Not relevant.

17. Anonymous. Some guidelines for staffing in the 

absence of patient classification systems. Qld Nurse. 

Jul-Aug 1994;13(4):12. Not eligible target 

population.

18. Anonymous. Sister Susie. Lights, camera, traction! 

Nurs Stand. Feb 2-8 1994;8(19):47. Not eligible 

target population.

19. Anonymous. An issue of floating. Nursing. Nov 

1994;24(11):76-77. Legal cases.

20. Anonymous. Enterprise bargaining in the private 

sector. Qld Nurse. Nov-Dec 1994;13(6):10-11. 

Comment.

21. Anonymous. Staffing patterns for patient care and 

support personnel in a general pediatric unit. 

American Academy of Pediatrics Committee on 

Hospital Care. Pediatrics. May 1994;93(5):850-854. 

No association tested.

22. Anonymous. And speaking of patient safety. AARN 

News Lett. Apr 1994;50(4):11. Comment.

23. Anonymous. Medication incident reporting forms. 

Lamp. Apr 1995;52(3):22-25. Comment.

24. Anonymous. Rebuilding a unit for seamless surgical 

care. OR Manager. Dec 1995;11(12):15-16. 

Comment.

25. Anonymous. Employees speak out. Testimonials help 

hospital recruit in- and out-of-state, boost staff morale 

and patient satisfaction. McLeod Regional Medical 

Center, Florence, SC. Profiles Healthc Mark. MarApr 1995(64):2-7. Comment. 

26. Anonymous. Stroke path calls for care when 

evaluating variances. Hosp Case Manag. Nov 

1995;3(11):176-177. Comment. 

27. Anonymous. Integrating an understanding of sleep 

knowledge into your practice (continuing education 

credit). Am Nurse. Mar 1995;27(2):20-21. Comment. 

28. Anonymous. How do you know if your paycheck is 

correct? Ky Nurse. Jan-Mar 1995;43(1):11. Comment. 

29. Anonymous. 38 hour week--your questions answered. 

Qld Nurse. Jan-Feb 1995;14(1):15-17. Not eligible 

target population.

30. Anonymous. A review of the use of DySSSy. Nurs 

Stand. Oct 9 1996;11(3):32. Not eligible target 

population.

31. Anonymous. Patient nurse dependency. Qld Nurse. 

Sep-Oct 1996;15(5):18. Comment. 

32. Anonymous. IOM issues nursing staffing report: 

some positive recommendations yet report fails to 

address immediacy of hospital staffing problems. Am 

Nurse. Mar 1996;28(2):8; 23. Comment. 

33. Anonymous. Position statement on minimum staffing 

in NICUs. Neonatal Netw. Mar 1996;15(2):48. 

Review. 

34. Anonymous. Hospital nixes pathways, keeps case 

management. Hosp Case Manag. Jan 1996;4(1):6, 11-

12. Comment. 

35. Anonymous. Colorado case blurs line between board 

of nursing admin. law and criminal action. Am Nurse. 

Sep-Oct 1997;29(5):3. Legal cases. 

36. Anonymous. Wound care team nips costly bed sore 

problems, slashes hospital expenses. Health Care Cost 

Reengineering Rep. Dec 1997;2(12):181-185; suppl 

181-184. Not eligible exposure.

37. Anonymous. Nurses' report card project under way. 

Hosp Peer Rev. Jun 1997;22(6):76-78. Comment. 

38. Anonymous. Renal transplantees have special 

education needs. Hosp Case Manag. Mar 

1997;5(3):43-44, 49-51. Not eligible exposure.
B-2 

39. Anonymous. Rx for cutting labor costs: add more 

registered nurses. Health Care Cost Reengineering 

Rep. Jun 1997;2(6):81-85. No association tested.

40. Anonymous. Patient commits suicide; hospital, 

nursing agencies settle for $700,000. Hosp Secur Saf 

Manage. Oct 1997;18(6):8-10. Comment. 

41. Anonymous. Who should own case management 

within the continuum of care? Hosp Case Manag. Mar 

1997;5(3):37-39. Comment. 

42. Anonymous. Does an RN have the right to refuse to 

be floated to an area that she/he believes they are 

unqualified for? Chart. Apr 1997;94(4):5. Comment. 

43. Anonymous. Cook County Hospital RNs take on 

restructuring. Chart. Nov 1997;94(11):1. Comment. 

44. Anonymous. Issue: we never seem to have enough 

staffing on my unit. What can we do? Ohio Nurses 

Rev. Nov-Dec 1997;72(10):16. Comment. 

45. Anonymous. Nurse staffing and quality of care in 

health care organizations research agenda of the 

Department of Health and Human Services, Agency 

for Health Care Policy and Research, National 

Institute for Nursing Research, Division of Nursing of 

HRSA. Nurs Outlook. Jul-Aug 1997;45(4):190-191. 

News. 

46. Anonymous. What can you do to assist float nurses 

who are assigned to your unit? J N Y State Nurses 

Assoc. Jun 1997;28(2):19. Comment. 

47. Anonymous. Patient abandonment. Nursing. Apr 

1997;27(4):69. Legal cases. 

48. Anonymous. Approaches to organising nursing shift 

patterns. Nurs Stand. Jan 22 1997;11(18):32-33. No 

association tested.

49. Anonymous. Hospital fails to diagnose CVA; 

EMTALA suit follows. Regan Rep Nurs Law. Mar 

1998;38(10):1. Comment. 

50. Anonymous. Voices from Colorado. Nurs Manage. 

Jun 1998;29(6):52-53. Legal cases. 

51. Anonymous. To err is human to forgive is divine, as 

one nurse found out. Nurs Times. May 6-12 

1998;94(18):49. Comment. 

52. Anonymous. Cut pneumonia length of stay, costs, 

readmissions. Health Care Cost Reengineering Rep. 

Jan 1998;3(1):1-5; suppl 1-4. Not eligible exposure.

53. Anonymous. Telemetry unit moves from worst to best 

using redesign process. Patient Focus Care Satisf. Dec 

1998;6(12):137-139. Comment. 

54. Anonymous. Improving pain management for 

orthopedic patients at Hermann Hospital, Houston, 

TX. Qual Connect. Winter 1998;7(1):9. Not eligible 

target population.

55. Anonymous. The "take a nurse to lunch" program. A 

unique focus group improves and promotes food 

services. Health Care Food Nutr Focus. Oct 

1998;15(2):5-7. Not eligible exposure.

56. Anonymous. Study reveals satisfaction with hospital 

experience major factor in decision to donate. Plus 

study finds health professionals not prepared to 

recommend donation. Nephrol News Issues. Jun 

1998;12(6):64-66, 68. Not eligible exposure.

57. Anonymous. CVA (cerebrovascular accident) 

pathway cuts across seven hospital units. Hosp Case 

Manag. Feb 1998;6(2):33-34. Not eligible exposure.

58. Anonymous. Counter misleading data: adjust for 

patient acuity, indirect nursing hours. ED Manag. Mar 

1998;10(3):29-30. Comment. 

59. Anonymous. Are ED nursing staff levels under 

attack? Patient Focus Care Satisf. May 1998;6(5):59-

62. No association tested.

60. Anonymous. How do you know you're productive in 

PACU (postanesthesia care unit)? OR Manager. Apr 

1998;14(4):24-25. Comment. 

61. Anonymous. Nursing staff levels under attack? 

Respond with data, increased efficiency. ED Manag. 

Mar 1998;10(3):25-29. No association tested.

62. Anonymous. Massachusetts board reprimands DanaFarber nurses. Am Nurse. Sep-Oct 1999;31(5):6. 

Comment. 

63. Anonymous. Court rules 'no duty to consult with Dr. 

Re Meds.' Case on point: Silves v. King, 970 P.2d 

791-WA (1999). Regan Rep Nurs Law. Mar 

1999;39(10):. Legal cases. 

64. Anonymous. Fund to pay $10M: seeks contribution 

from nurse. Regan Rep Nurs Law. Mar 

1999;39(10):1. Legal cases.

65 Anonymous. Defining provider roles. More work + 

changing roles = less satisfaction for providers and 

patients. Patient Focus Care Satisf. Nov 

1999;7(11):121-123. Comment. 

66. Anonymous. Foreign-educated nurses participate in 

the computerized clinical simulation testing (CST) 

pilot study. Issues 1999;20(1):5. Not relevant.

67. Anonymous. More RNs means fewer post-surgical 

complications. Mich Nurse. Mar 1999;72(3):9. News. 

68. Anonymous. Cross-training programs offer 

scheduling flexibility. Patient Focus Care Satisf. Dec 

1999;7(12):139-140. Comment. 

69. Anonymous. Patient acuity profiles can keep you on 

budget. Patient Focus Care Satisf. Dec 

1999;7(12):137-139. No association tested.

70. Anonymous. Take California's word: nurse staffing 

levels do impact quality of care. Patient Focus Care 

Satisf. Dec 1999;7(12):133-136. Comment. 

71. Anonymous. Conscious sedation raises safe staffing 

concerns. Dimens Crit Care Nurs. Jan-Feb 

1999;18(1):35. Comment. 

72. Anonymous. Cutting RNs a false economy? Hosp 

Peer Rev. Feb 1999;24(2):29-30. Comment. 

73. Anonymous. More RNs lower risk of UTIs, 

pneumonia. OR Manager. Jan 1999;15(1):7. 

Comment. 

74. Anonymous. Appealing for compensation. Nursing. 

Mar 1999;29(3):25. Legal cases.

75. Anonymous. Critical care services and personnel: 

recommendations based on a system of categorization 

into two levels of care. American College of Critical 

Care Medicine of the Society of Critical Care 

Medicine. Crit Care Med. Feb 1999;27(2):422-426. 

Review. 

76. Anonymous. Defining provider roles. Hartford uses 

report cards to teach nurses to teach. Patient Focus 

Care Satisf. Jan 2000;8(1):1-4. Comment. 

77. Anonymous. Shortage spurs hunt for hospital staffing 

ratios. Patient Focus Care Satisf. Feb 2000;8(2):18-

21. No association tested.
B-3 

78. Anonymous. 'It's about safe care'. Nurses strike 

Tenet-owned St. Vincent over mandatory overtime. 

Revolution. Mar-Apr 2000;1(2):10. News. 

79. Anonymous. Texas' nursing education system. Can it 

respond to this nursing shortage? Tex Nurs. Apr 

2000;74(4):4-5, 11-12. Comment. 

80. Anonymous. Staffing shortages mean increased 

opportunities. Crit Care Nurse. Feb 2000;Suppl:16. 

Comment. 

81. Anonymous. NHS Direct will not cure ward-level 

staffing and skill-mix problems. Nurs Times. Mar 23-

29 2000;96(12):3. Not eligible target population.

82. Anonymous. State of the nursing shortage. Am J 

Nurs. Dec 2000;100(12):20-21. News. 

83. Anonymous. Frustrated by the nursing shortage? Try 

these tactics instead of bonuses. ED Manag. Oct 

2000;12(10):109-113. Comment. 

84. Anonymous. California nurses win landmark victory. 

Am J Nurs. Jan 2000;100(1):20. News. 

85. Anonymous. Patient safety alert. Has the nursing 

shortage decreased health care quality? Hosp Peer 

Rev. Jan 2001;26(1):1-2. Comment. 

86. Anonymous. ED makes nurses happy by outsourcing 

calls. ED Manag. Oct 2001;13(10):113-115. Not 

eligible exposure.

87. Anonymous. Striving to become the employer of 

choice: the relationship of employee and patient 

satisfaction. Healthc Leadersh Manag Rep. Jul 

2001;9(7):9-15. No association tested.

88. Anonymous. Has the nursing shortage decreased 

health care quality? Healthc Benchmarks. Jan 

2001;8(1):suppl 1-2. Comment. 

89. Anonymous. For safety's sake, bill aims to eliminate 

overtime. Hosp Case Manag. May 2001;9(5):78, 66. 

Interview. 

90. Anonymous. Rules proposal intended to clarify nurse 

staffing. Tex Nurs. Mar 2001;75(3):4-5. Comment. 

91. Anonymous. Terminated nurse alleges hospital 

violated ADA. Case on point: Phelps v. Optima 

Health Inc., 2001 WL 563921 N.E.2d-NH. Nurs Law 

Regan Rep. Jul 2001;42(2):4. Legal cases.

92. Anonymous. Occupational health. Court told 

overwork led to breakdown. Nurs Times. Jun 28-Jul 4 

2001;97(26):7. Legal cases.

93. Anonymous. Staff safety. Violent patients get the red 

card. Nurs Times. Jun 21-27 2001;97(25):4. 

Comment. 

94. Anonymous. Brief encounters costing the NHS dear. J 

Nurs Manag. Nov 2001;9(6):353-356. News. 

95. Anonymous. Guidelines for nurse staffing in intensive 

care: a consultation document (3rd draft, July 2001). 

Intensive Crit Care Nurs. Oct 2001;17(5):254-258. 

News. 

96. Anonymous. Mandatory overtime bill caps off 

successful legislative year. Am Nurse. Nov-Dec 

2001;33(6):3, 17. Comment. 

97. Anonymous. 2001 salary survey results. Are you 

losing staff to other facilities? Here's what ED 

managers need to do. ED Manag. Nov 

2001;13(11):suppl 1-4. Comment. 

98. Anonymous. The staffing shortage: dealing with the 

here and now. Healthc Leadersh Manag Rep. Jul 

2001;9(7):1-7. No association tested.

99. Anonymous. Linking staffing and quality issues. Jt 

Comm Perspect. Aug 2001;21(8):8-9. Comment. 

100. Anonymous. Perspectives. Work environment a top 

issue in nurse retention. Med Health. Aug 13 

2001;55(31):7-8. News. 

101. Anonymous. Nurses rally to ban forced overtime. OR 

Manager. Jul 2001;17(7):6-7. Comment. 

102. Anonymous. Senate confronts the nursing shortage. 

ED Manag. Apr 2001;13(4):45-46. Review. 

103. Anonymous. Temp staff become a fixture in ORs. OR 

Manager. Jun 2001;17(6):15. Comment. 

104. Anonymous. Interviews find some ORs have 

vacancies, others waiting lists. OR Manager. Jun 

2001;17(6):1, 13-14. Comment. 

105. Anonymous. New study gauges scope of nursing 

shortage. Hosp Peer Rev. Jun 2001;26(6):83-85, 74. 

Comment. 

106. Anonymous. Staffing watch. Hosp Health Netw. Apr 

2001;75(4):26. News. 

107. Anonymous. Off-shift choices help to keep nurses. 

OR Manager. Feb 2001;17(2):20. Comment. 

108. Anonymous. Anger over double HIV test. Nurs 

Times. Mar 8-14 2001;97(10):7. News. 

109. Anonymous. Solutions to health care's labor 

shortages. Russ Coiles Health Trends. Nov 

2001;14(1):8-12. Comment. 

110. Anonymous. Nurse's unintentional error is not 'willful 

misconduct'. Nurs Law Regan Rep. Jan 2002;42(8):1. 

Legal cases.

111. Anonymous. Staff collaboration boosts adoption of 

best practices. Rn. Nov 2002;65(11):34hf32-35. 

Comment. 

112. Anonymous. Patient safety alert. Closer link made 

between nursing shortage, safety. Healthcare 

Benchmarks Qual Improv. Oct 2002;9(10):suppl 1-3. 

Comment. 

113. Anonymous. JCAHO: nurse shortage threat to patient 

safety. OR Manager. Sep 2002;18(9):8. Review. 

114. Anonymous. JCAHO: nursing shortage puts patients 

at risk, demands immediate attention. Hosp Peer Rev. 

Sep 2002;27(9):117-119. Comment. 

115. Anonymous. Nurses may be your best tool for 

improving quality of care. Hosp Peer Rev. Aug 

2002;27(8):105-108. No association tested.

116. Anonymous. Sentinel event leads to safety checklist. 

Hosp Peer Rev. Jul 2002;27(7):91-94, 99. Comment. 

117. Anonymous. Medication error. Salty language. 

Nursing. Apr 2002;32(4):12. Comment. 

118. Anonymous. Greater nursing staff levels result in 

better care for hospital patients. Health Care Strateg 

Manage. Jun 2002;20(6):12. Comment. 

119. Anonymous. California releases proposed nurse-topatient ratios for acute care hospitals. Prairie Rose. 

Mar-May 2002;71(1):1, 3. Comment. 

120. Anonymous. In our hands and in our hearts: finding 

solutions to the staffing crisis. Healthc Leadersh 

Manag Rep. Dec 2002;10(12):1-8. Comment. 
B-4 

121. Anonymous. The business planning framework--

nursing resources. Qld Nurse. Sep-Oct 2002;21(5):13. 

Comment. 

122. Anonymous. Developing a plan to improve the odds 

of retaining your staff. OR Manager. Dec 

2002;18(12):1, 10-11. Review. 

123. Anonymous. Spotlight on nursing. A focus on lasting 

workplace solutions. Tex Nurs. Aug 2002;76(7):8-10, 

14. Comment. 

124. Anonymous. Inadequate staffing linked to poor 

patient outcomes. Nurs Manage. Sep 2002;33(9):20. 

Review. 

125. Anonymous. Senate and Assembly hold joint health 

committee hearing on nursing shortage and nurse 

staffing crisis. N J Nurse. Jul-Aug 2002;32(6):1, 6. 

Review. 

126. Anonymous. OR staffing holds up, but coping with 

shortage is more challenging. OR Manager. Sep 

2002;18(9):1, 11, 14-16 passi. Comment. 

127. Anonymous. PSNA mandatory overtime survey 

summary. Pennsylvania Nurse Aug-Sep 

2002;57(7):8-9. Not peer reviewed.

128. Anonymous. Proposed staffing rules pass. 

Implementation begins. Tex Nurs. Mar 2002;76(3):8-

9. Comment. 

129. Anonymous. Web survey. March results: 'nurse 

staffing--beyond the ratios'. Mod Healthc. Apr 8 

2002;32(14):35. Web survey. 

130. Anonymous. Tough times in healthcare. J Nurs Adm. 

Mar 2002;32(3):122. Letter. 

131. Anonymous. Hashing out California's staffing ratios. 

Am Nurse. Mar-Apr 2002;34(2):1, 16-17. Comment. 

132. Anonymous. Position statement on intensive care 

nursing staffing. Aust Crit Care. Feb 2002;15(1):6-7. 

Not eligible target population.

133. Anonymous. Faced with staffing minimums, hospitals 

lure nurses with sign-on bonuses. Nephrol News 

Issues. Apr 2002;16(5):63. Comment. 

134. Anonymous. Guidance paper: refocusing the role of 

the midwife. RCM Midwives J. Apr 2002;5(4):128-

133. Not eligible target population. 

135. Anonymous. Survey shows increasing vacancy rates. 

Synergy News Aug 2002:20-1. Not peer reviewed. 

136. Anonymous. By the numbers. Staffing. Mod Healthc. 

Dec 23 2002;Suppl:44, 46, 48. Comment. 

137. Anonymous. Data trends. The true cost of overtime. 

Healthc Financ Manage. Dec 2002;56(12):90. No 

association tested. 

138. Anonymous. NY: nurse learns of pt's doubt re surgery 

site: hospital liabile for operation on wrong hand. 

Nurs Law Regan Rep. Dec 2003;44(7):3. Legal cases. 

139. Anonymous. Deplorable ICU nursing results in $2.4 

million judgment. Case on point: Mobile Infirmary 

Medical Center v. Hodgen, 2003 WL 22463340 

so.2d--AL. Nurs Law Regan Rep. Nov 2003;44(6):2.

Legal cases.

140. Anonymous. AL: wrong epinephrine dose--cardiac 

arrest: Ct. emphasizes the '5 Rs' of drug 

administration. Nurs Law Regan Rep. Sep 

2003;44(4):3. Legal cases.

141. Anonymous. Making your mark. Nursing. Aug 

2003;33(8):18. News. 

142. Anonymous. Nurses and pharmacists partner for 

patient safety. Healthcare Benchmarks Qual Improv. 

Aug 2003;10(8):92-93. Comment. 

143. Anonymous. IL: Discovery of disciplining of RN post 

pt.'s death: RN's voluntary termination too remote in 

time. Nurs Law Regan Rep. Jan 2003;43(8):3. Legal 

cases.

144. Anonymous. RN's comp. claim based on PTSD 

resulting from short staffing, etc. Case on point: 

Smith-Price v. Charter Pines Behavioral Ctr., 584 

S.E.2d 881-NC. Nurs Law Regan Rep. Sep 

2003;44(4):2. Legal cases. 

145. Anonymous. Do you address staffing effectiveness 

standards? Hosp Peer Rev. Sep 2003;28(9):122, 127-

128. Comment. 

146. Anonymous. ANA applauds federal legislation to 

mandate safe nurse-to-patient ratios. Ky Nurse. JulSep 2003;51(3):6. News. 

147. Anonymous. Federal safe staffing bill introduced. Am 

Nurse. May-Jun 2003;35(3):1, 5. News. 

148. Anonymous. Tales from the trenches. Patient Care 

Manag. Feb 2003;19(2):10-12. Comment. 

149. Anonymous. 5 resolutions for a happy 2003. Patient 

Care Manag. Jan 2003;19(1):1, 4-6. Comment. 

150. Anonymous. CA: Nurse errs in giving pitocin to stop 

labor: father's suit for emotional distress fails. Nurs 

Law Regan Rep. Oct 2004;45(5):3. Legal cases.

151. Anonymous. Nurse sued when child dies from error 

in interpreting drug dosage. Nurs Law Regan Rep. 

Oct 2004;45(5):1. Legal cases.

152. Anonymous. Study shows 12-hour shifts increase 

errors. Healthcare Benchmarks Qual Improv. Sep 

2004;11(9):105-106. Comment. 

153. Anonymous. Adverse events. Focus on patient safety. 

Can Nurse. Feb 2004;100(2):30. Comment. 

154. Anonymous. Nurses identify barriers to educating 

patients about meds. Hosp Health Netw. Jan 

2004;78(1):64. Comment. 

155. Anonymous. California patient care labor costs rise 

under staffing requirements. Healthc Financ Manage. 

Nov 2004;58(11):118. Comment. 

156. Anonymous. Veteran nurses give patients a quick 

look to avoid waits. Perform Improv Advis. Aug 

2004;8(8):85-87. Comment. 

157. Anonymous. Preliminary report, mandatory overtime 

by RNs in Louisiana 2004 Louisiana Registered 

Nurse Population Survey. Pelican news Mar 

2004;60(1):20. Not peer reviewed.

158. Anonymous. Shifts go up for bid: hospitals see boost 

in patient care, staff morale. Healthcare Benchmarks 

Qual Improv. Oct 2004;11(10):109-112. Comment. 

159. Anonymous. Reducing junior doctors' hours will 

extend opportunities for nurses. Nurs Times. Jul 27-

Aug 2 2004;100(30):15. Comment. 

160. Anonymous. Levels of care: the impact of nursepatient ratios. Prof Nurse. Jul 2004;19(11):6-7. News. 

161. Anonymous. Research shows Michigan safe patient 

care initiatives save lives and money. Mich Nurse. 

Jun-Jul 2004:8. News. 

162. Anonymous. Staffing the ED despite the nursing 

shortage. Rn. Feb 2004;67(2):26hf21-26hf22. 

Comment. 
B-5 

163. Anonymous. Flexible job options help maintain 

quality. Healthcare Benchmarks Qual Improv. Jan 

2004;11(1):8-9. Comment. 

164. Anonymous. JCAHO's 2006 National Patient Safety 

Goals: handoffs are biggest challenge. Hosp Peer 

Rev. Jul 2005;30(7):89-93. Comment. 

165. Anonymous. Nurse terminated for meds. error: 

hospital attempts to deny access to records. Case on 

point: Chapman v. Health & Hospital Corporations, 

2005 WL 697435--NY. Nurs Law Regan Rep. May 

2005;45(12):2. Legal cases. 

166. Anonymous. More than 40% of nurse errors not from 

medication. Healthcare Benchmarks Qual Improv. 

Apr 2005;12(4):41-43. Comment. 

167. Anonymous. Women need flexible schedules and 

challenging assignments. Health Care Strateg 

Manage. Jun 2005;23(6):12. Comment. 

168. Anonymous. AR:12-hour-shift RN falls on trip to 

cafeteria: workers' compensation benefits awarded to 

nurse. Nurs Law Regan Rep. Apr 2005;45(11):3. 

Legal cases. 

169. Anonymous. AACN standards for establishing and 

sustaining healthy work environments: a journey to 

excellence. Am J Crit Care. May 2005;14(3):187-197. 

Review. 

170. Anonymous. Position paper on safe staffing. Tar Heel 

Nurse. Jan-Feb 2005;67(1):20. Review. 

171. Anonymous. An opportunity to shape patient care. 

Nurs Times. Jun 14-20 2005;101(24):69. Not eligible 

target population. 

172. Anonymous. Wright S. Nursing development? Nurs 

Stand. Jun 12-18 1991;5(38):52-53. No association 

tested.

173. Abbott A, Barrow S, Lopresti F, et al. International 

employment in clinical practice: influencing factors 

for the dental hygienist. International Journal of 

Dental Hygiene Feb 2005;3(1):37-44. Not relevant. 

174. Abbott J, Young A, Haxton R, Van Dyke P. 

Collaborative care: a professional model that 

influences job satisfaction. Nurs Econ. May-Jun 

1994;12(3):167-169, 174. Not eligible exposure.

175. Abbott ME. Measuring the effects of a selfscheduling committee. Nurs Manage. Sep 

1995;26(9):64A-64B, 64D, 64G. Not eligible 

outcomes.

176. Ackerman MH, Henry MB, Graham KM, Coffey N. 

Humor won, humor too: a model to incorporate 

humor into the healthcare setting. Nurs Forum. OctDec 1993;28(4):9-16. Not eligible exposure. 

177. Ackley NL. Is a serious nurse shortage coming? Tex 

Nurs. Mar 1999;73(3):10-13. Comment. 

178. Adam S. Plugging the gap--critical care skills are the 

current universal commodity. Nurs Crit Care. Sep-Oct 

2004;9(5):195-198. Editorial. 

179. Adams A, Bond S. Clinical specialty and 

organizational features of acute hospital wards. J Adv 

Nurs. Dec 1997;26(6):1158-1167. Not eligible target 

population.

180. Adams A, Bond S. Staffing in acute hospital wards: 

part 2. Relationships between grade mix, staff 

stability and features of ward organizational 

environment. J Nurs Manag. Sep 2003;11(5):293-298. 

Not eligible target population.

181. Adams A, Bond S. Staffing in acute hospital wards: 

part 1. The relationship between number of nurses 

and ward organizational environment. J Nurs Manag. 

Sep 2003;11(5):287-292. Not eligible target 

population.

182. Adams B. Are we our own jail keepers? Revolution. 

Nov-Dec 2000;1(6):30-31. Comment. 

183. Adams B. Profile: Barry Adams in his own words. 

Revolution. Jan-Feb 2000;1(1):10-11. Interview. 

184. Adams B. Accountable but powerless. Health Aff 

(Millwood). Jan-Feb 2002;21(1):218-223. Comment. 

185. Adams DA. The relationship between use of varying 

proportions of part-time faculty and full-time nursing 

faculty perceptions of workload and collegial support. 

Not relevant. 

186. Adams DA. The relationship between use of varying 

proportions of part-time faculty and full-time nursing 

faculty perceptions of workload and collegial support. 

Not relevant.

187. Adams K, Murphy J. Addressing barriers in headache 

care. Interview by Janis Smy. Nurs Times. May 11-17 

2004;100(19):26-27. Interview. 

188. Adams KS, Zehrer CL, Thomas W. Comparison of a 

needleless system with conventional heparin locks. 

Am J Infect Control. Oct 1993;21(5):263-269. Not 

eligible exposure.

189. Adamsen L, Rasmussen JM. Exploring and 

encouraging through social interaction: a qualitative 

study of nurses' participation in self-help groups for 

cancer patients. Cancer Nurs. Feb 2003;26(1):28-36. 

Not eligible target population.

190. Adamsen L, Tewes M. Discrepancy between patients' 

perspectives, staff's documentation and reflections on 

basic nursing care. Scand J Caring Sci. 

2000;14(2):120-129. Not eligible target population.

191. Adejumo O. Divergent backgrounds, unified goals: 

continuing education program for multinational 

nurses in a hospital in the Middle East. J Contin Educ 

Nurs. Mar-Apr 1999;30(2):79-83. Not eligible target 

population.

192. Adomat R, Hewison A. Assessing patient 

category/dependence systems for determining the 

nurse/patient ratio in ICU and HDU: a review of 

approaches. J Nurs Manag. Sep 2004;12(5):299-308. 

Not eligible target population.

193. Adomat R, Hicks C. Measuring nursing workload in 

intensive care: an observational study using closed 

circuit video cameras. J Adv Nurs. May 

2003;42(4):402-412. Not eligible target population.

194. Agbo M. Up to one's eyes. Nurs Stand. Oct 25-31 

1995;10(5):55. Comment. 

195. Agnew T. Making a difference. Nurs Times. Jun 7-13 

1995;91(23):18. News. 
B-6 

196. Ahmad MM, Alasad JA. Predictors of patients' 

experiences of nursing care in medical-surgical 

wards. Int J Nurs Pract. Oct 2004;10(5):235-241. Not 

eligible target population.

197. Ahmann E. Examining assumptions underlying 

nursing practice with children and families. Pediatr 

Nurs. Sep-Oct 1998;24(5):467-469. No association 

tested. 

198. Ahmed DS, Fecik S. The fatigue factor. When long 

shifts harm patients. Am J Nurs. Sep 1999;99(9):12. 

Case reports.

199. Ahmed DS, Hamrah PM. Right drug, wrong dose. 

Am J Nurs. Jan 1999;99(1 Pt 1):12. Case reports.

200. Ahmed S. Out-patients in vogue. Nurs Stand. May 

18-24 1994;8(34):40. Comment. 

201. Ahrens T, Yancey V, Kollef M. Improving family 

communications at the end of life: implications for 

length of stay in the intensive care unit and resource 

use. Am J Crit Care. Jul 2003;12(4):317-323; 

discussion 324. Not eligible exposure.

202. Aiken LH. More nurses, better patient outcomes: why 

isn't it obvious? Eff Clin Pract. Sep-Oct 

2001;4(5):223-225. Comment. 

203. Aiken LH. Evidence of our instincts: an interview 

with Linda H. Aiken. Interview by Alison P. Smith. 

Nurs Econ. Mar-Apr 2002;20(2):58-61. Not eligible 

target population.

204. Aiken LH, Buchan J, Sochalski J, Nichols B, Powell 

M. Trends in international nurse migration. Health 

Aff (Millwood). May-Jun 2004;23(3):69-77. Not 

eligible exposure. 

205. Aiken LH, Clarke SP, Silber JH, Sloane D. Hospital 

nurse staffing, education, and patient mortality. LDI 

Issue Brief. Oct 2003;9(2):1-4. Comment. 

206. Aiken LH, Clarke SP, Sloane DM. Hospital 

restructuring: does it adversely affect care and 

outcomes? J Nurs Adm. Oct 2000;30(10):457-465.

Published twice.

207. Aiken LH, Clarke SP, Sloane DM. Hospital staffing, 

organization, and quality of care: cross-national 

findings. Int J Qual Health Care. Feb 2002;14(1):5-

13. Not eligible target population. 

208. Aiken LH, Clarke SP, Sloane DM. Hospital staffing, 

organization, and quality of care: Cross-national 

findings. Nurs Outlook. Sep-Oct 2002;50(5):187-194. 

Not eligible target population.

209. Aiken LH, Havens DS, Sloane DM. The Magnet 

Nursing Services Recognition Program. Am J Nurs. 

Mar 2000;100(3):26-35; quiz 35-26. Not eligible 

exposure. 

210. Aiken LH, Havens DS, Sloane DM. Magnet nursing 

services recognition programme. Nurs Stand. Mar 8-

14 2000;14(25):41-47. No association tested. 

211. Aiken LH, Patrician PA. Measuring organizational 

traits of hospitals: the Revised Nursing Work Index. 

Nurs Res. May-Jun 2000;49(3):146-153. Review. 

212. Aiken LH, Sloane DM, Klocinski JL. Hospital nurses' 

occupational exposure to blood: prospective, 

retrospective, and institutional reports. Am J Public 

Health. Jan 1997;87(1):103-107. Not eligible 

outcomes.

213. Aiken LH, Sloane DM, Lake ET. Satisfaction with 

inpatient acquired immunodeficiency syndrome care. 

A national comparison of dedicated and scattered-bed 

units. Med Care. Sep 1997;35(9):948-962. Not 

eligible exposure. 

214. Aiken LH, Sloane DM, Lake ET, Sochalski J, Weber 

AL. Organization and outcomes of inpatient AIDS 

care. LDI Issue Brief. Sep 1999;5(1):1-4. Comment. 

215. Aikens A. Colors of the spectrum. Agency/registry 

nursing. Nurs Spectr (Wash D C). Nov 27 

1995;5(24):16. Comment. 

216. Aitken LM. Critical care nurses' use of decisionmaking strategies. J Clin Nurs. Jul 2003;12(4):476-

483. Not eligible target population. 

217. Akid M. Pay. Nurses threaten to quit bank as rates are 

slashed. Nurs Times. Jul 5-11 2001;97(27):9. News. 

218. Akid M. 800m pounds: the government's incentive to 

end NHS reliance on agency nurses. Nurs Times. Sep 

6-12 2001;97(36):12-13. Not eligible target 

population. 

219. Akid M. The camera never lies. Nurs Times. Mar 29-

Apr 4 2001;97(13):10-11. News. 

220. Albarran J, Scholes J. Blurred, blended or 

disappearing--the image of critical care nursing. Nurs 

Crit Care. Jan-Feb 2005;10(1):1-3. Editorial. 

221. Alberts MJ, Chaturvedi S, Graham G, Hughes RL, 

Jamieson DG, Krakowski F, Raps E, Scott P. Acute 

stroke teams: results of a national survey. National 

Acute Stroke Team Group. Stroke. Nov 

1998;29(11):2318-2320. Not eligible outcomes. 

222. Alcock D, Jacobsen MJ, Sayre C. Competencies 

related to medication administration and monitoring. 

Can J Nurs Adm. Sep 1997;10(3):54-73. Not eligible 

target population. 

223. Alcock D, Lawrence J, Goodman J, Ellis J. Formative 

evaluation: implementation of primary nursing. Can J 

Nurs Res. Fall 1993;25(3):15-28. Not eligible 

outcomes.

224. Alderman C. Nursing overseas: caring in a divided 

community. Nurs Stand. Apr 7-13 1993;7(29):22-23. 

Comment. 

225. Alex J, Rao VP, Cale AR, Griffin SC, Cowen ME, 

Guvendik L. Surgical nurse assistants in cardiac 

surgery: a UK trainee's perspective. Eur J 

Cardiothorac Surg. Jan 2004;25(1):111-115. Not 

eligible target population.

226. Alexander C, Palladino M, Evans B, Harp K, Marable 

K, Whitmer K. Self-scheduling: two success stories. 

The art of the deal. Am J Nurs. Mar 1993;93(3):70-

74. Comment. 

227. Alimoglu MK, Donmez L. Daylight exposure and the 

other predictors of burnout among nurses in a 

University Hospital. Int J Nurs Stud. Jul 

2005;42(5):549-555. Not eligible target population.

228. Allan D, Cornes D. The impact of management of 

change projects on practice: a description of the 

contribution that one educational programme made to 

the quality of health care. J Adv Nurs. Apr 

1998;27(4):865-869. Not eligible target population. 

229. Allanach H. Go with the flow. Nurs Stand. Nov 10-16 

1999;14(8):23. Not eligible target population.
B-7 

230. Allen C, Heffernan C, Pallent S, Weaver L. 

Uniforms: a strange custom? Nurs Times. Sep 2-8 

1992;88(36):51. Comment. 

231. Allen CI, Turner PS. The effect of an intervention 

programme on interactions on a continuing care ward 

for older people. J Adv Nurs. Oct 1991;16(10):1172-

1177. Not eligible target population. 

232. Allen J, Mellor D. Work context, personal control, 

and burnout amongst nurses. West J Nurs Res. Dec 

2002;24(8):905-917. Not eligible target population.

233. Allen SK, Wilder K. Back belts pay off for nurses. 

Occup Health Saf. Jan 1996;65(1):59-62. Not Eligible 

exposure. 

234. Alleyne J, Thomas VJ. The management of sickle cell 

crisis pain as experienced by patients and their carers. 

J Adv Nurs. Apr 1994;19(4):725-732. Not eligible 

target population.

235. Allgood C, O'Rourke K, VanDerslice J, Hardy MA. 

Job satisfaction among nursing staff in a military 

health care facility. Mil Med. Oct 2000;165(10):757-

761. Not eligible target population. 

236. AllisonJones LL. Student and faculty perceptions of 

teaching effectiveness of full-time and part-time 

associate degree nursing faculty. Not relevant. 

237. AllisonJones LL, Hirt JB. Comparing the teaching 

effectiveness of part-time & full-time clinical nurse 

faculty. Nursing Education Perspectives Sep-Oct 

2004;25(5):238-43. Not relevant. 

238. al-Ma'aitah R, Momani M. Assessment of nurses' 

continuing education needs in Jordan. J Contin Educ 

Nurs. Jul-Aug 1999;30(4):176-181. Not eligible 

target population.

239. Almeida SL. Legislating nurse-patient ratios: A 

controversial approach to improving patient care? J 

Emerg Nurs. Oct 2002;28(5):377-378. Editorial. 

240. Alspach G. Nurse staffing and patient outcomes. This 

is news? Crit Care Nurse. Feb 2003;23(1):14-15. 

Editorial. 

241. Alspach G. When your work conditions are sicker 

than your patients. Crit Care Nurse. Jun 

2005;25(3):11-12, 14. Editorial. 

242. Altimier LB, Sanders JM. Cross-training in 3-D. Nurs 

Manage. Nov 1999;30(11):59-62. Comment. 

243. Altman S. Arbitrator upholds RN's refusal to work 

unsafe assignment. Chart. May 1997;94(5):1, 4. Legal 

cases.

244. Alward RR. Study links rotating shift work and 

nurses' risk of coronary heart disease. Am Nurse. Mar 

1996;28(2):12. Comment. 

245. Alward RR, Monk TH. A comparison of rotating-shift 

and permanent night nurses. Int J Nurs Stud. 

1990;27(3):297-302. Not eligible outcomes.

246. Alward RR, Monk TH. A 'round-the-clock' 

profession: coping with the effects of shift work. Nev 

Rnformation. Nov 1995;4(4):18-19. Comment. 

247. Amato M, Perton L, Sullivan B. Buttons, buttons, and 

more buttons: are they professional? J Nurs Adm. Dec 

2001;31(12):559-560. Interview. 

248. Ambrose C. Recruitment problems in intensive care: 

a solution. Nurs Stand. Dec 4-10 2002;17(12):39-40. 

Not eligible target population. 

249. Andersen SE. Implementing a new drug record 

system: a qualitative study of difficulties perceived by 

physicians and nurses. Qual Saf Health Care. Mar 

2002;11(1):19-24. Not eligible target population. 

250. Anderson C. Enteral feeding: a change in practice. J 

Child Health Care. Winter 2000;4(4):160-162. Not 

eligible target population. 

251. Anderson DJ, Webster CS. A systems approach to the 

reduction of medication error on the hospital ward. J 

Adv Nurs. Jul 2001;35(1):34-41. Not eligible target 

population. 

252. Anderson FD, Maloney JP, Beard LW. A descriptive, 

correlational study of patient satisfaction, provider 

satisfaction, and provider workload at an army 

medical center. Mil Med. Feb 1998;163(2):90-94. Not 

eligible target population. 

253. Anderson FD, Maloney JP, Knight CD, Jennings BM. 

Utilization of supplemental agency nurses in an Army 

medical center. Mil Med. Jan 1996;161(1):48-53. Not 

eligible target population. 

254. Anderson LA, Schramm CA. Adapting charting by 

exception to the perianesthesia setting. J Perianesth 

Nurs. Oct 1999;14(5):260-269. Comment. 

255. Anderson MA, Clarke MM, Helms LB, Foreman MD. 

Hospital readmission from home health care before 

and after prospective payment. J Nurs Scholarsh. 

2005;37(1):73-79. Not eligible target population. 

256. Anderson RM. Economic and quality of care issues 

with implications for scopes of practice--physicians 

and nurses. Aspens Advis Nurse Exec. Apr 

1994;9(7):suppl 1. Interview. 

257. Anderson S, Eadie DR, MacKintosh AM, Haw S. 

Management of alcohol misuse in Scotland: the role 

of A&E nurses. Accid Emerg Nurs. Apr 

2001;9(2):92-100. Not eligible target population. 

258. Anderson S, Wittwer W. Using bar-code point-ofcare technology for patient safety. J Healthc Qual. 

Nov-Dec 2004;26(6):5-11. Not eligible exposure. 

259. Anderson TA, Hart GK. Data clarification. Aust Crit 

Care. Feb 2002;15(1):4; author reply 4-5. Comment. 

260. Ando S, Ono Y, Shimaoka M, Hiruta S, Hattori Y, 

Hori F, Takeuchi Y. Associations of self estimated 

workloads with musculoskeletal symptoms among 

hospital nurses. Occup Environ Med. Mar 

2000;57(3):211-216. Not eligible target population. 

261. Ang R, Fong LC. Nursing leadership: the Singapore 

experience. Reflect Nurs Leadersh. 2003;29(1):26-28. 

Not eligible target population. 

262. Angeles-Llerenas A, Alvarez del Rio A, SalazarMartinez E, Kraus-Weissman A, Zamora-Munoz S, 

Hernandez-Avila M, Lazcano-Ponce E. Perceptions 

of nurses with regard to doctor-patient 

communication. Br J Nurs. Dec 11-2004 Jan 7 

2003;12(22):1312-1321. Not eligible target 

population.

263. Angus J, Hodnett E, O'Brien-Pallas L. Implementing 

evidence-based nursing practice: a tale of two 

intrapartum nursing units. Nurs Inq. Dec 

2003;10(4):218-228. Not eligible outcomes. 

264. Anshus JS. The mentality of contraction. Am J Emerg 

Med. Jan 1996;14(1):114. Letter. 
B-8 

265. Anthony MK. The relationship of authority to 

decision-making behavior: implications for redesign. 

Res Nurs Health. Oct 1999;22(5):388-398. Not 

eligible exposure.

266. Anthony MK, Hudson-Barr D. A patient-centered 

model of care for hospital discharge. Clin Nurs Res. 

May 2004;13(2):117-136. Not eligible exposure. 

267. Anton D. Meet the travelers. Danielle Anton. Rn. Jan 

2004;Suppl:22. Interview. 

268. Aquila A. The Vascular Project: using data to 

improve processes and outcomes. J Vasc Nurs. Sep 

2001;19(3):80-86. Not eligible exposure.

269. Arafa MA, Nazel MW, Ibrahim NK, Attia A. 

Predictors of psychological well-being of nurses in 

Alexandria, Egypt. Int J Nurs Pract. Oct 

2003;9(5):313-320. Not eligible target population. 

270. Arbesman MC, Wright C. Mechanical restraints, 

rehabilitation therapies, and staffing adequacy as risk 

factors for falls in an elderly hospitalized population. 

Rehabil Nurs. May-Jun 1999;24(3):122-128. No 

association tested. 

271. Archibald G. A post-modern nursing model. Nurs 

Stand. May 10-16 2000;14(34):40-42. Not eligible 

target population. 

272. Arford PH, Allred CA. Value = quality + cost. J Nurs 

Adm. Sep 1995;25(9):64-69. No association tested.

273. Armstrong M. Staff mix and public safety. Nurs BC. 

Oct 2004;36(4):5-6. Letter. 

274. Armstrong-Stassen M, Cameron SJ, Horsburgh ME. 

Downsizing-initiated job transfer of hospital nurses: 

how do the job transferees fare? J Health Hum Serv 

Adm. Spring 2001;23(4):470-489. Not eligible 

outcomes. 

275. Arndt M. Medication errors. Research in practice: 

how drug mistakes affect self-esteem. Nurs Times. 

Apr 13-19 1994;90(15):27-30. Comment. 

276. Arranz P, Ulla SM, Ramos JL, Del Rincon C, LopezFando T. Evaluation of a counseling training program 

for nursing staff. Patient Educ Couns. Feb 

2005;56(2):233-239. Not eligible target population. 

277. Arsenault S. Staffing is a concern in telemetry. Crit 

Care Nurse. Oct 2000;20(5):14-16. Comment. 

278. Arthur D. The validity and reliability of the 

measurement of the concept 'expressed emotion' in 

the family members and nurses of Hong Kong 

patients with schizophrenia. Int J Ment Health Nurs. 

Sep 2002;11(3):192-198. Not eligible target 

population.

279. Arts SE, Francke AL, Hutten JB. Liaison nursing for 

stroke patients: results of a Dutch evaluation study. J 

Adv Nurs. Aug 2000;32(2):292-300. Not eligible 

target population. 

280. Artz M. Setting nurse-patient ratios: ANA bill calls 

for development of staffing systems in hospitals. Am 

J Nurs. May 2005;105(5):97. News. 

281. Arvanitopulos BL, Camino MK. You're pulling me 

where? Medsurg Nurs. Dec 1998;7(6):371-373. 

Comment. 

282. Asch DA. Use of a coded postcard to maintain 

anonymity in a highly sensitive mail survey: cost, 

response rates, and bias. Epidemiology. Sep 

1996;7(5):550-551. Not eligible exposure.

283. Ashe N, Manzo L. Get customer sensitive. Nurs 

Manage. Jan 2002;33(1):50-51. Comment. 

284. Astelm J. Elizabeth and Alexandra's story. Child Care 

Health Dev. Nov 1995;21(6):369-375. Case reports.

285. Atencio BL, Cohen J, Gorenberg B. Nurse retention: 

is it worth it? Nurs Econ. Nov-Dec 2003;21(6):262-

268, 299, 259. Not eligible outcomes.

286. Atkins PM, Marshall BS, Javalgi RG. Happy 

employees lead to loyal patients. Survey of nurses and 

patients shows a strong link between employee 

satisfaction and patient loyalty. J Health Care Mark. 

Winter 1996;16(4):14-23. Not eligible exposure.

287. Atkinson M. Arbitrator: hospital must tie admissions 

to RN staffing. Revolution. Mar-Apr 2005;6(2):9. 

Comment. 

288. Austin S. Staffing: know your liability. Nurs Manage. 

Jul 2000;31(7):19. Legal cases.

289. Aveyard B. Education and person-centred approaches 

to dementia care. Nurs Older People. Feb 

2001;12(10):17-19. Not eligible target population.

290. Avigne J, McHugh N, Manley M, Sievers L. OR 

roundtable. Managers' advice on OR staffing. OR 

Manager. Jun 1999;15(6):15-17, 19. Interview. 

291. Baarda S. Caring for staff nurses. AWHONN 

Lifelines. Aug-Sep 2001;5(4):10-11. Letter. 

292. Babus V. Tuberculosis morbidity risk in medical 

nurses in specialized institutions for the treatment of 

lung diseases in Zagreb. Int J Tuberc Lung Dis. Jun 

1997;1(3):254-258. Not eligible target population.

293. Badovinac CC, Wilson S, Woodhouse D. The use of 

unlicensed assistive personnel and selected outcome 

indications. Nurs Econ. Jul-Aug 1999;17(4):194-200. 

Not eligible exposure.

294. Baggot DM, Hensinger B, Parry J, Valdes MS, Zaim 

S. The new hire/preceptor experience: cost-benefit 

analysis of one retention strategy. J Nurs Adm. Mar 

2005;35(3):138-145. Not eligible exposure.

295. Bailey BA. How to float safely and effectively. 

Nursing. Feb 1990;20(2):113-116. No association 

tested.

296. Bailey DA, Mion LC. Improving care givers' 

satisfaction with information received during 

hospitalization. J Nurs Adm. Jan 1997;27(1):21-27. 

Not eligible exposure.

297. Bailey F. A day in the life: a night to remember. Nurs 

Stand. Nov 1-6 1995;10(6):38. Case reports.

298. Bailey L. Medical errors--what we can do? One 

informed patient's recommendations. S C Nurse. OctDec 2002;9(4):20. Comment. 

299. Bailey M. Occupational HIV infection risk. Lancet. 

May 5 1990;335(8697):1104-1105. Comment. 

300. Bair B, Toth W, Johnson MA, Rosenberg C, Hurdle 

JF. Interventions for disruptive behaviors. Use and 

success. J Gerontol Nurs. Jan 1999;25(1):13-21. Not 

eligible exposure. 

301. Bair N, Bobek MB, Hoffman-Hogg L, Mion LC, 

Slomka J, Arroliga AC. Introduction of sedative, 

analgesic, and neuromuscular blocking agent 

guidelines in a medical intensive care unit: physician 

and nurse adherence. Crit Care Med. Mar 

2000;28(3):707-713. Not eligible exposure.
B-9 

302. Baker H, Naphthine R. Nurses and medication. Part 6. 

Ritual+workloads = medication error. Aust Nurs J. 

Nov 1994;2(5):34-36. Not eligible target population. 

303. Baker H, Naphthine R. Nurses and medication. Part 5. 

Medication error: the big stick to beat you with. Aust 

Nurs J. Oct 1994;2(4):28-30. Not eligible target 

population. 

304. Baker HM. Rules outside the rules for administration 

of medication: a study in New South Wales, 

Australia. Image J Nurs Sch. 1997;29(2):155-158. Not 

eligible target population.

305. Baker K, Evans CB, Tiburzi T, Nolan MT, Frost GL, 

Kokoski P, Arrington DM. Costing services: 

comparing three i.v. medication systems. Nurs 

Manage. Mar 1993;24(3):56-60. Not eligible 

exposure. 

306. Balas MC, Scott LD, Rogers AE. The prevalence and 

nature of errors and near errors reported by hospital 

staff nurses. Appl Nurs Res. Nov 2004;17(4):224-

230. Not eligible outcomes.

307. Bale S, Tebbie N, Price P. A topical metronidazole 

gel used to treat malodorous wounds. Br J Nurs. Jun 

10 2004;13(11):S4-11. Not eligible target population.

308. Balhorn J. Patient classification used as a tool for 

assessment of staff/patient ratios. Edtna Erca J. JanMar 1998;24(1):13-16. Review. 

309. Ball C, Walker G, Harper P, Sanders D, McElligott 

M. Moving on from 'patient dependency' and 'nursing 

workload' to managing risk in critical care. Intensive 

Crit Care Nurs. Apr 2004;20(2):62-68. Not eligible 

target population. 

310. Balling K, McCubbin M. Hospitalized children with 

chronic illness: parental caregiving needs and valuing 

parental expertise. J Pediatr Nurs. Apr 

2001;16(2):110-119. Not eligible exposure.

311. Ballweg DD. Implementing developmentally 

supportive family-centered care in the newborn 

intensive care unit as a quality improvement 

initiative. J Perinat Neonatal Nurs. Dec 

2001;15(3):58-73. Not eligible exposure. 

312. Bamber M. Reasons for leaving among psychiatric 

nurses: a two-year prospective study. Nurs Pract. 

1991;4(4):9-11. Not eligible exposure.

313. Bania K, Bergmooser G. A tool for improving 

supplemental staffing. Nurs Manage. May 

1997;28(5):78. Comment. 

314. Banks N, Hardy B, Meskimen K. Take the plunge: 

expanding the float pool to "closed" units. Nurs 

Manage. Jan 1999;30(1):51-55. Not eligible 

outcomes. 

315. Barash PG, Rosenbaum SH. Staffing ICUs: the good 

news and the not-so-good news. Chest. Mar 

1998;113(3):569-570. Comment. 

316. Barker P. Psychiatric caring. Nurs Times. Mar 8-14 

2001;97(10):38-39. Not eligible target population.

317. Barnes J. A life in the day of. Nurs Stand. Nov 24-30 

1999;14(10):26-27. Comment. 

318. Barratt E. Investigating shift preferences. Nurs Times. 

May 8-14 1991;87(19):44-45. Comment. 

319. Barrington SF, Kettle AG, O'Doherty MJ, Wells CP, 

Somer EJ, Coakley AJ. Radiation dose rates from 

patients receiving iodine-131 therapy for carcinoma 

of the thyroid. Eur J Nucl Med. Feb 1996;23(2):123-

130. Not eligible target population. 

320. Barta SK, Stacy RD. The effects of a theory-based 

training program on nurses' self-efficacy and behavior 

for smoking cessation counseling. J Contin Educ 

Nurs. May-Jun 2005;36(3):117-123. Not eligible 

exposure. 

321. Barton E. Workwise: a job problem shared. Nurs 

Stand. May 26-Jun 1 1993;7(36):44-45. Comment. 

322. Barton J. Nursing shifts. Is flexible rostering helpful? 

Nurs Times. Feb 15-22 1995;91(7):32-33. Not 

eligible target population. 

323. Barton J, Spelten ER, Smith LR, et al. A classification 

of nursing and midwifery shift systems. International 

journal of nursing studies Feb 1993;30(1):65-80. Not 

relevant.

324. Barton J, Spelten E, Totterdell P, Smith L, Folkard S. 

Is there an optimum number of night shifts? 

Relationship between sleep, health and well-being. 

Work Stress. Apr-Sep 1995;9(2-3):109-123. Not 

eligible target population.

325. Barton J, Spelten ER, Smith LR, Totterdell PA, 

Folkard S. A classification of nursing and midwifery 

shift systems. Int J Nurs Stud. Feb 1993;30(1):65-80. 

Not eligible target population. 

326. Bartram T, Joiner TA, Stanton P. Factors affecting the 

job stress and job satisfaction of Australian nurses: 

implications for recruitment and retention. Contemp 

Nurse. Oct 2004;17(3):293-304. Not eligible target 

population. 

327. Barzoloski-O'Connor B. Have license, will travel. 

Nurs Spectr (Wash D C). Jul 29 1996;6(16):16. 

Comment. 

328. Bassett D, Tsourtos G. Inpatient suicide in a general 

hospital psychiatric unit. A consequence of 

inadequate resources? Gen Hosp Psychiatry. Sep 

1993;15(5):301-306. Not eligible target population. 

329. Batalis NI, Prahlow JA. Accidental insulin overdose. 

J Forensic Sci. Sep 2004;49(5):1117-1120. Case 

reports. 

330. Bates E. Part-time working. Defective agency. Nurs 

Times. Feb 28-Mar 5 1996;92(9):32-33. Comment. 

331. Bates J. One day it could be you. Nurs Stand. Jun 2-8 

2004;18(38):24-25. Comment. 

332. Bauer I. Nurses' perception of the first hour of the 

morning shift (6.00-7.00 a.m.) in a German hospital. J 

Adv Nurs. Jun 1993;18(6):932-937. Not eligible 

target population. 

333. Baulcomb JS. Management of change through force 

field analysis. J Nurs Manag. Jul 2003;11(4):275-280. 

Not eligible target population. 

334. Baxter B. Operating department staffing--a business 

manager's perspective. Br J Theatre Nurs. Oct 

1997;7(7):11, 14-17. Not eligible target population. 

335. Baxter B. Have I been here before? Br J Theatre 

Nurs. Oct 1998;8(7):41-42. Not eligible target 

population.
B-10 

336. Beach SM, Engelsher J, Kinzeler EE. Databits. Hey, 

that's my grandma! Ky Nurse. Oct-Dec 2004;52(4):7. 

Comment. 

337. Beard EL, Jr. Stop floating--the next paradigm shift? 

J Nurs Adm. Mar 1994;24(3):4. Comment. 

338. Beardsley D. Board of Nursing decision puts patients 

at risk. J Nurs Adm. Apr 1999;29(4):4-5. Letter. 

339. Beasley T, Gerbis P, Lyon J. Staffing and critical 

care. Nev Rnformation. Jun 1995;4(2):7. Comment. 

340. Beattie J, Calpin-Davies PJ. Workforce dilemmas: a 

comparison of staffing in a generalist and a specialist 

intensive care unit. Intensive Crit Care Nurs. Feb 

1999;15(1):52-57. Not eligible target population.

341. Bechel DL, Myers WA, Smith DG. Does patientcentered care pay off? Jt Comm J Qual Improv. Jul 

2000;26(7):400-409. Not eligible exposure. 

342. Beck KL, Larrabee JH. Measuring patients' 

perceptions of nursing care. Nurs Manage. Sep 

1996;27(9):32B-D. Not eligible exposure.

343. Becker A, Schulten-Oberborsch G, Beck U, 

Vestweber KH. Stoma care nurses: good value for 

money? World J Surg. Jul 1999;23(7):638-642; 

discussion 642-633. Not eligible target population. 

344. Becker B, Woolard R, Nirenberg TD, Minugh A, 

Longabaugh R, Clifford PR. Alcohol use among 

subcritically injured emergency department patients. 

Acad Emerg Med. Sep 1995;2(9):784-790. Not 

eligible outcomes. 

345. Becker ER, Foster RW. Organizational determinants 

of nurse staffing patterns. Nurs Econ. Mar-Apr 

1988;6(2):71-75. Not eligible year. 

346. Bednar B, McMullen N. A retrospective analysis of 

employee turnover in the health care setting. Nephrol 

News Issues. Feb 1998;12(2):35-39. No association 

tested. 

347. Bednar B, Sinitzky M, Thrall K, Wick G. Staff 

turnover in the dialysis unit. Interview by Diane 

Boudreau. Nephrol News Issues. Sep 1995;9(9):39-

40. No association tested. 

348. Beeman J, Diehl B. A credentialing program for 

nursing staff caring for pediatric patients with an 

ilizarov apparatus. Rehabil Nurs. Sep-Oct 

1995;20(5):278-282. Not eligible exposure. 

349. Beer HL, Duvvi S, Webb CJ, Tandon S. Blood loss 

estimation in epistaxis scenarios. J Laryngol Otol. Jan 

2005;119(1):16-18. Not eligible exposure. 

350. Begley CM. 'Knowing your place': student midwives' 

views of relationships in midwifery in Ireland. 

Midwifery. Sep 2001;17(3):222-233. Not eligible 

target population. 

351. Begley CM. 'Great fleas have little fleas': Irish student 

midwives' views of the hierarchy in midwifery. J Adv 

Nurs. May 2002;38(3):310-317. Not eligible target 

population. 

352. Behrman AJ, Shofer FS, Green-McKenzie J. Trends 

in bloodborne pathogen exposure and follow-up at an 

urban teaching hospital: 1987 to 1997. J Occup 

Environ Med. Apr 2001;43(4):370-376. Not eligible 

exposure. 

353. Beitz JM, Fey J, O'Brien D. Perceived need for 

education vs. actual knowledge of pressure ulcer care 

in a hospital nursing staff. Medsurg Nurs. Oct 

1998;7(5):293-301. Not eligible exposure. 

354. Belcher JV, Munjas B. Psychiatric-mental health head 

nurse management concerns. Arch Psychiatr Nurs. 

Aug 1990;4(4):260-263. No association tested. 

355. Bell M, Warner JA, Cameron AE. Patient flow 

patterns in a recovery room and implications for 

staffing. J R Soc Med. Jan 1985;78(1):35-38. Not 

eligible year. 

356. Beltzhoover M. Self-scheduling: an innovative 

approach. Nurs Manage. Apr 1994;25(4):81-82. No 

association tested. 

357. Ben-Ami S, Shaham J, Rabin S, Melzer A, Ribak J. 

The influence of nurses' knowledge, attitudes, and 

health beliefs on their safe behavior with cytotoxic 

drugs in Israel. Cancer Nurs. Jun 2001;24(3):192-200. 

Not eligible target population. 

358. Benjamin I. Staff allocation and rostering in a 

Queensland public hospital. Qld Nurse. Nov-Dec 

1990;9(6):10-11. No association tested.

359. Benko LB. Oregon passes nurses bill. Hospitals and 

nurses at odds over potential effect on staffing. Mod 

Healthc. Jun 18 2001;31(25):52. News. 

360. Benko LB. Workforce report 2003. Ratio daze in 

California. State staffing law may exacerbate nursing 

shortfall. Mod Healthc. Jun 16 2003;33(24):30-31. 

Comment. 

361. Bennett DS. The blind men and the elephant. A fable 

for health care safety. Crit Care Nurs Clin North Am. 

Dec 2002;14(4):xiii-xvi. Comment. 

362. Bennett DS, Dune L. Everyday thoughts: harnessing 

the thought process toward a practical framework for 

increasing critical thinking and reducing error. Crit 

Care Nurs Clin North Am. Dec 2002;14(4):385-390, 

viii-ix. Review. 

363. Benson RM. A non-specialist's guide to the CCU. Rn. 

Jan 1991;54(1):50-53. Comment. 

364. Berden HJ, Willems FF, Hendrick JM, Pijls NH, 

Knape JT. How frequently should basic 

cardiopulmonary resuscitation training be repeated to 

maintain adequate skills? Bmj. Jun 12 

1993;306(6892):1576-1577. Not eligible target 

population. 

365. Bergbom I, Svensson C, Berggren E, Kamsula M. 

Patients' and relatives' opinions and feelings about 

diaries kept by nurses in an intensive care unit: pilot 

study. Intensive Crit Care Nurs. Aug 1999;15(4):185-

191. Not eligible target population.

366. Berger MC, Seversen A, Chvatal R. Ethical issues in 

nursing. West J Nurs Res. Aug 1991;13(4):514-521. 

Not eligible outcomes.

367. Berglin P. Leadership through shared governance. 

 Colo Nurse. Mar 1995;95(1):19-20. Comment. 

368. Berland A. Controlling workload. Can Nurse. May 

1990;86(5):36-38. No association tested. 

369. Berliner H. US healthcare. United straits. Health Serv 

J. Jun 27 2002;112(5811):32. Comment. 

370. Berman S. Health care: mandatory nurse-to-patient 

staffing ratios in California. J Law Med Ethics. 

Summer 2002;30(2):312-313. Review. 
B-11 

371. Berrios CD, Jacobowitz WH. Therapeutic holding: 

outcomes of a pilot study. J Psychosoc Nurs Ment 

Health Serv. Aug 1998;36(8):14-18. Not eligible 

exposure. 

372. Berry D, Drury J, Prendeville B, Ranganathan P, 

Sumner J. Sexual abuse: giving support to nurses. 

Nurs Stand. Oct 13-19 1993;8(4):25-27. Not eligible 

target population. 

373. Berry DM. An inpatient classification system for 

nursing service staffing decisions. Commun Nurs 

Res. Mar 1977;8:90-100. Not eligible year. 

374. Bertolini G, Rossi C, Brazzi L, Radrizzani D, Rossi 

G, Arrighi E, Simini B. The relationship between 

labour cost per patient and the size of intensive care 

units: a multicentre prospective study. Intensive Care 

Med. Dec 2003;29(12):2307-2311. Not eligible target 

population. 

375. Bertram DA, Thompson MC, Giordano D, Perla J, 

Rosenthal TC. Implementation of an inpatient case 

management program in rural hospitals. J Rural 

Health. Winter 1996;12(1):54-66. Not eligible 

exposure. 

376. Bethel S, Ridder J. Evaluating nursing practice: 

satisfaction at what cost? Nurs Manage. Sep 

1994;25(9):41-43, 46-48. Not eligible outcomes.

377. Bevan J, Linton A. Continuous quality improvement: 

maintaining quality of care with changing staffing 

patterns. J Cannt. Spring 1998;8(2):33-35. No 

association tested. 

378. Beyea SC. Too tired to work safely? Aorn J. Sep 

2004;80(3):559-562. Not eligible exposure. 

379. Beyers M. Ask AONE's experts ... about staffing 

options. Nurs Manage. Jul 1998;29(7):72. Comment. 

380. Beyers M. Ask AONE's experts ... about patientfocused care. Nurs Manage. Aug 1998;29(8):88. 

Comment. 

381. Beyers M. Ask AONE's experts ... about how to 

reduce overtime and use of per diem staff. Nurs 

Manage. Dec 1999;30(12):56. Comment. 

382. Beyers M. Ask AONE's experts ... about counting 

short-stay census. Nurs Manage. May 1999;30(5):72. 

Comment. 

383. Bhatia R, Blackshaw G, Rogers A, Grant A, Kulkarni 

R. Developing a departmental culture for reporting 

adverse incidents. Int J Health Care Qual Assur Inc 

Leadersh Health Serv. 2003;16(2-3):154-156. Not 

eligible target population. 

384. Bhengu BR. Exploring the critical care nurses' 

experiences regarding moonlighting. Curationis. May 

2001;24(2):48-53. Not eligible target population. 

385. Biddle J. 9 tips for success. Nursing. Nov 2002;32(11 

Pt 1):80. Comment. 

386. Bilchik GS. Norma Rae, R.N. Hosp Health Netw. 

Nov 2000;74(11):40-44. Comment. 

387. Biller AM. Implementing nursing case management. 

Rehabil Nurs. May-Jun 1992;17(3):144-146. No 

association tested. 

388. Billinghurst F, Morgan B, Arthur HM. Patient and 

nurse-related implications of remote cardiac 

telemetry. Clin Nurs Res. Nov 2003;12(4):356-370. 

Not eligible exposure. 

389. Binder RL, McNiel DE. Staff gender and risk of 

assault on doctors and nurses. Bull Am Acad 

Psychiatry Law. 1994;22(4):545-550. Not eligible 

exposure. 

390. Bingham R. Leaving nursing. Health Aff (Millwood). 

Jan-Feb 2002;21(1):211-217. Comment. 

391. Binnekade JM, Vroom MB, de Mol BA, de Haan RJ. 

The quality of Intensive Care nursing before, during, 

and after the introduction of nurses without ICUtraining. Heart Lung. May-Jun 2003;32(3):190-196. 

Not eligible target population.

392. Binnie A. Freedom to practise: patient-centred 

nursing. Nurs Times. Jan 27-Feb 2 2000;96(4):39-40. 

Comment. 

393. Birnbaum D. Full-time equivalent (FTE) numbers. 

Infect Control Hosp Epidemiol. Mar 2002;23(3):116-

117. Comment. 

394. Bischof J. Self-scheduling in critical care. Crit Care 

Nurse. Jan 1992;12(1):50-55. No association tested.

395. Bishop S, Panjari M, Astbury J, Bell R. "A survey of 

antenatal clinic staff: some perceived barriers to the 

promotion of smoking cessation in pregnancy". Aust 

Coll Midwives Inc J. Sep 1998;11(3):14-18. Not 

eligible target population. 

396. Bissonnette T. What was said, what we heard. Mich 

Nurse. Jun-Jul 2005;78(5):10. Comment. 

397. Bjork IT. Practical skill development in new nurses. 

Nurs Inq. Mar 1999;6(1):34-47. Not eligible target 

population. 

398. Bjork IT, Kirkevold M. Issues in nurses' practical 

skill development in the clinical setting. J Nurs Care 

Qual. Oct 1999;14(1):72-84. Not eligible target 

population. 

399. Black K. Specialized teams complement nursing. 

Patient satisfaction begins with satisfied professional 

and support teams. Healthc Exec. Mar-Apr 

2004;19(2):50-51. Comment. 

400. Blain S. Attitudes to women undergoing TOP. Nurs 

Stand. Jun 2-8 1993;7(37):30-33. Not eligible 

exposure. 

401. Blair PD. Continuous assessment and regular 

communication foster patient safety. Nurs Manage. 

Aug 2003;34(8):22-23, 60. Comment. 

402. Blanchfield KC, Biordi DL. Power in practice: a 

study of nursing authority and autonomy. Nursing 

administration quarterly Spring 1996;20(3):42-9. Not 

relevant. 

403. Bland P. New grads face changing employment 

picture -- a synopsis of a 1996 survey. Nurse to Nurse 

Jan-Feb 1997;8(1):14-5. Not peer reviewed.

404. Blank AE, Horowitz S, Matza D. Quality with a 

human face? The Samuels Planetree model hospital 

unit. Jt Comm J Qual Improv. Jun 1995;21(6):289-

299. Not eligible exposure. 

405. Blegen MA, Vaughn T, Pepper G, Vojir C, Stratton 

K, Boyd M, Armstrong G. Patient and staff safety: 

voluntary reporting. Am J Med Qual. Mar-Apr 

2004;19(2):67-74. Not eligible exposure. 

406. Blewitt DK, Jones KR. Using elements of the nursing 

minimum data set for determining outcomes. J Nurs 

Adm. Jun 1996;26(6):48-56. Not eligible exposure. 
B-12 

407. Bliss-Holtz J. Discriminating types of medication 

calculation errors in nursing practice. Nurs Res. NovDec 1994;43(6):373-375. Not eligible outcomes. 

408. Bloice C. Slash and burn redux. Hunter Group still 

bottom-line feeding. Revolution. May-Jun 

2002;3(3):6-7. News. 

409. Bloodworth C, Lea A, Lane S, Ginn R. Challenging 

the myth of the 12-hour shift: a pilot evaluation. Nurs 

Stand. Apr 4-10 2001;15(29):33-36. Not eligible 

target population. 

410. Blumenfield M, Milazzo J, Wormser GP, Smith PJ. 

Reluctance to care for patients with AIDS. Gen Hosp 

Psychiatry. Nov 1991;13(6):410. Letter. 

411. Blythe J, Baumann A, Zeytinoglu I, Denton M, 

Higgins A. Full-time or part-time work in nursing: 

preferences, tradeoffs and choices. Healthc Q. 

2005;8(3):69-77, 64. Not eligible outcomes. 

412. Boehm C. PASNAP targets mandatory overtime. 

Revolution. May-Jun 2005;6(3):11. Comment. 

413. Boettger JE. Effects of a pressure-reduction mattress 

and staff education on the incidence of nosocomial 

pressure ulcers. J Wound Ostomy Continence Nurs. 

Jan 1997;24(1):19-25. Not eligible exposure 

414. Bohnen MV, Balantac DD. Basic academic 

preparation of foreign-educated nurses: a base for 

developing continuing education courses. Journal of 

continuing education in nursing Nov-Dec 

1994;25(6):258-62. Not relevant.. 

415. Boling J, Hoffmann L. The nursing shortage and its 

implications for case management. Case Manager. 

Nov-Dec 2001;12(6):53-57. No association tested. 

416. Bolton SC. Who cares? Offering emotion work as a 

'gift' in the nursing labour process. J Adv Nurs. Sep 

2000;32(3):580-586. Not eligible exposure. 

417. Bonadio WA, Carney M, Gustafson D. Efficacy of 

nurses suturing pediatric dermal lacerations in an 

emergency department. Ann Emerg Med. Dec 

1994;24(6):1144-1146. Not eligible exposure. 

418. Bond CA, Raehl CL, Franke T. Medication errors in 

United States hospitals. Pharmacotherapy. Sep 

2001;21(9):1023-1036. Not eligible outcomes. 

419. Bond CA, Raehl CL, Franke T. Interrelationships 

among mortality rates, drug costs, total cost of care, 

and length of stay in United States hospitals: 

summary and recommendations for clinical pharmacy 

services and staffing. Pharmacotherapy. Feb 

2001;21(2):129-141. Not eligible exposure.

420. Bond CA, Raehl CL, Franke T. Clinical pharmacy 

services, hospital pharmacy staffing, and medication 

errors in United States hospitals. Pharmacotherapy. 

Feb 2002;22(2):134-147. Not eligible exposure. 

421. Bond CA, Raehl CL, Pitterle ME. Staffing and the 

cost of clinical and hospital pharmacy services in 

United States hospitals. Pharmacotherapy. Jun 

1999;19(6):767-781. Not eligible exposure. 

422. Bond GE, Fiedler FE. A comparison of leadership vs. 

renovation in changing staff values. Nurs Econ. JanFeb 1999;17(1):37-43. Not eligible exposure. 

423. Bondas TE. Caritative leadership. Ministering to the 

patients. Nurs Adm Q. Jul-Sep 2003;27(3):249-253. 

Review. 

424. Bonner R, Beaumont R, Smith B. Understanding 

rostering. Part 6. Changing rosters--managing roster 

change. Aust Nurs J. Aug 1995;3(2):36-38. Not 

eligible target population. 

425. Bonner R, Beaumont R, Smith B. Understanding 

rostering. Part 4. Products & consequences. Aust 

Nurs J. Jun 1995;2(11):36-38. Not eligible target 

population. 

426. Bonner R, Beaumont R, Smith B. Understanding 

rostering. Part 3. How a roster is developed. Aust 

Nurs J. May 1995;2(10):40-42. Not eligible target 

population. 

427. Bonner R, Beaumont R, Smith B. Understanding 

rostering. Part 1. The rights & wrongs of rostering. 

Aust Nurs J. Mar 1995;2(8):18-20. Not eligible target 

population. 

428. Booker JM, Roseman C. A seasonal pattern of 

hospital medication errors in Alaska. Psychiatry Res. 

Aug 28 1995;57(3):251-257. Not eligible exposure. 

429. Boomer MJ, Rissel C. An evaluation of a smoke free 

environment policy in two Sydney hospitals. Aust 

Health Rev. 2002;25(3):179-184. Not eligible target 

population. 

430. Boosfeld B. Conflict in decision making: do nurses 

have a role? Paediatr Nurs. Sep 1995;7(7):21-23. 

Comment. 

431. Booth B. Management of drug errors. Nurs Times. 

Apr 13-19 1994;90(15):30-31. Comment. 

432. Borg E. Professional liability during the shortage. Can 

Nurse. Sep 2001;97(8):34-35. Comment. 

433. Borg MA. Bed occupancy and overcrowding as 

determinant factors in the incidence of MRSA 

infections within general ward settings. J Hosp Infect. 

Aug 2003;54(4):316-318. Not eligible target 

population. 

434. Borromeo AR, Windle PE, Eagen MK. The 

professional salary model: meeting the bottom lines. 

Nurs Econ. Jul-Aug 1996;14(4):241-244. No 

association tested. 

435. Boscarino JA. Patients' perception of quality hospital 

care and hospital occupancy: are there biases 

associated with assessing quality care based on 

patients' perceptions? Int J Qual Health Care. Oct 

1996;8(5):467-477. Not eligible outcomes. 

436. Bosek MS. Mandatory overtime: professional duty, 

harms, and justice. JONAS Healthc Law Ethics 

Regul. Dec 2001;3(4):99-102. Comment. 

437. Bosman RJ, Rood E, Oudemans-van Straaten HM, 

Van der Spoel JI, Wester JP, Zandstra DF. Intensive 

care information system reduces documentation time 

of the nurses after cardiothoracic surgery. Intensive 

Care Med. Jan 2003;29(1):83-90. Not eligible target 

population. 

438. Bostrom J, Tisnado J, Zimmerman J, Lazar N. The 

impact of continuity of nursing care personnel on 

patient satisfaction. J Nurs Adm. Oct 1994;24(10):64-

68. Not eligible exposure. 

439. Bostrom J, Zimmerman J. Restructuring nursing for a 

competitive health care environment. Nurs Econ. JanFeb 1993;11(1):35-41, 54. Not eligible outcomes. 
B-13 

440. Bostrom JM. Impact of physician practice on nursing 

care. Nurs Econ. Sep-Oct 1994;12(5):250-255, 286. 

Not eligible exposure. 

441. Boudreaux ED, Ary R, Mandry C. Emergency 

department personnel accuracy at estimating patient 

satisfaction. J Emerg Med. Aug 2000;19(2):107-112. 

Not eligible exposure. 

442. Boumans NP, Landeweerd JA, Visser M. 

Differentiated practice, patient-oriented care and 

quality of work in a hospital in the Netherlands. 

Scand J Caring Sci. Mar 2004;18(1):37-48. Not 

eligible target population. 

443. Bourbonnais R, Comeau M, Vezina M. Job strain and 

evolution of mental health among nurses. J Occup 

Health Psychol. Apr 1999;4(2):95-107. Not eligible 

outcomes. 

444. Bourbonnais R, Vinet A, Vezina M, Gingras S. 

Certified sick leave as a non-specific morbidity 

indicator: a case-referent study among nurses. Br J 

Ind Med. Oct 1992;49(10):673-678. Not eligible 

outcomes. 

445. Bourgault AM, Smith S. The development of multilevel critical care competency statements for selfassessment by ICU nurses. Dynamics. Winter 

2004;15(4):15-18. Not eligible exposure. 

446. Bouza E, Munoz P, Lopez-Rodriguez J, Jesus Perez 

M, Rincon C, Martin Rabadan P, Sanchez C, Bastida 

E. A needleless closed system device (CLAVE) 

protects from intravascular catheter tip and hub 

colonization: a prospective randomized study. J Hosp 

Infect. Aug 2003;54(4):279-287. Not eligible 

exposure. 

447. Bowden FJ, Pollett B, Birrell F, Dax EM. 

Occupational exposure to the human 

immunodeficiency virus and other blood-borne 

pathogens. A six-year prospective study. Med J Aust. 

Jun 21 1993;158(12):810-812. Not eligible exposure. 

448. Bowles C, Candela L. First job experiences of recent 

RN graduates: improving the work environment. J 

Nurs Adm. Mar 2005;35(3):130-137. Not eligible 

outcomes. 

449. Bowles KH. Application of the Omaha System in 

acute care. Res Nurs Health. Apr 2000;23(2):93-105. 

Not eligible exposure. 

450. Boyd G. Terminated. Radiol Manage. Jan-Feb 

2004;26(1):54. Review. 

451. Boykin A, Schoenhofer SO, Smith N, St Jean J, 

Aleman D. Transforming practice using a caringbased nursing model. Nurs Adm Q. Jul-Sep 

2003;27(3):223-230. Not eligible exposure. 

452. Boynton D, Rothman L. Stage managing change: 

supporting new patient care models. Nurs Econ. MayJun 1995;13(3):166-173. No association tested.

453. Braddy PK, Washburn TA, Carroll LL. Factors 

influencing nurses to work for agencies. Western 

journal of nursing research Jun 1991;13(3):353-62. 

Not relevant. 

454. Bradley CF, Kozak C. Nursing care and management 

of the elderly hip fractured patient. J Gerontol Nurs. 

Aug 1995;21(8):15-22. Not eligible exposure. 

455. Bradley D. Ask the experts. Crit Care Nurse. Apr 

1998;18(2):98-99. Comment. 

456. Bradley EH, Cherlin E, McCorkle R, Fried TR, Kasl 

SV, Cicchetti DV, Johnson-Hurzeler R, Horwitz SM. 

Nurses' use of palliative care practices in the acute 

care setting. J Prof Nurs. Jan-Feb 2001;17(1):14-22. 

Not eligible outcomes. 

457. Bradley G. Drug errors. Just one slip. Interview by 

Daloni Carlisle. Nurs Times. Apr 3-9 1991;87(14):30-

31. Interview. 

458. Bradley S. Suffer the little children. The influence of 

nurses and parents in the evolution of open visiting in 

children's wards 1940-1970. Int Hist Nurs J. 

2001;6(2):44-51. Not eligible target population. 

459. Brady J. The nursing life. Stolen bases. Am J Nurs. 

Apr 1994;94(4):51. Comment. 

460. Bratt MM, Broome M, Kelber S, Lostocco L. 

Influence of stress and nursing leadership on job 

satisfaction of pediatric intensive care unit nurses. 

Am J Crit Care. Sep 2000;9(5):307-317. Not eligible 

exposure. 

461. Braun BI, Kritchevsky SB, Wong ES, Solomon SL, 

Steele L, Richards CL, Simmons BP. Preventing 

central venous catheter-associated primary 

bloodstream infections: characteristics of practices 

among hospitals participating in the Evaluation of 

Processes and Indicators in Infection Control (EPIC) 

study. Infect Control Hosp Epidemiol. Dec 

2003;24(12):926-935. No association tested. 

462. Bremnes RM. Experience with and attitudes to 

chemotherapy among newly employed nurses in 

oncological and surgical departments: a longitudinal 

study. Support Care Cancer. Jan 1999;7(1):11-16. Not 

eligible target population. 

463. Brennan W, Scully W, Tarbuck P, Young C. Nurses' 

attire in a special hospital: perceptions of patients and 

staff. Nurs Stand. Apr 26-May 2 1995;9(31):35-38. 

Not eligible exposure. 

464. Breslawski S, Hamilton D. Operating room 

scheduling. Choosing the best system. Aorn J. May 

1991;53(5):1229-1237. Not eligible outcomes.

465. Brewer CS, Nauenberg E. Future intentions of 

registered nurses employed in the western New York 

labor market: relationships among demographic, 

economic, and attitudinal factors. Applied Nursing 

Research Aug 2003;16(3):144-55. Not relevant.

466. Brewer CS, Zayas LE, Kahn LS, et al. Nursing 

recruitment and retention in New York State: a 

qualitative workforce needs assessment. Policy, 

Politics, & Nursing Practice Feb 2006;7(1):54-63. Not 

relevant.

467. Brezynskie H, Pendon E, Lindsay P, Adam M. 

Identification of the perceived learning needs of 

balloon angioplasty patients. Can J Cardiovasc Nurs. 

1998;9(2):8-14. Not eligible exposure. 

468. Bridgeman J. How do nurses learn about familycentred care? Paediatr Nurs. May 1999;11(4):26-29. 

Not eligible target population. 

469. Bridger JC. A study of nurses' views about the 

prevention of nosocomial urinary tract infections. 

Journal of clinical nursing Sep 1997;6(5):379-87. Not 

relevant. 

470. Briggs B. Pumped up about i.v. system. Health Data 

Manag. Feb 2004;12(2):106-108, 110. Comment. 
B-14 

471. Brillhart B, Sills F. Analysis of the roles and 

responsibilities of rehabilitation nursing staff. 

Rehabilitation Nursing May-Jun 1994;19(3):145-50, 

90. Not relevant.

472. Brillman JC, Doezema D, Tandberg D, Sklar DP, 

Davis KD, Simms S, Skipper BJ. Triage: limitations 

in predicting need for emergent care and hospital 

admission. Ann Emerg Med. Apr 1996;27(4):493-

500. Not eligible exposure. 

473. Brockopp DY, Franey BN, Sage-Smith D, Romond 

EH, Cannon CC. Patients' knowledge of their 

caregivers' names. A teaching-hospital study. Hosp 

Top. Winter 1992;70(1):25-28. Not eligible exposure.

474. Brockopp DY, Porter M, Kinnaird S, Silberman S. 

Fiscal and clinical evaluation of patient care. A case 

management model for the future. J Nurs Adm. Sep 

1992;22(9):23-27. Not eligible exposure. 

475. Brodell E. Nursing career satisfaction: the effects of 

autonomy, social integration and flexible scheduling. 

Prairie Rose. Sep-Nov 1996;65(3):4-6. No association 

tested. 

476. Broekmans S, Vanderschueren S, Morlion B, Kumar 

A, Evers G. Nurses' attitudes toward pain treatment 

with opioids: a survey in a Belgian university 

hospital. Int J Nurs Stud. Feb 2004;41(2):183-189. 

Not eligible target population. 

477. Brogan G. Off and running! Revolution. Jan-Feb 

2004;5(1):18-21. Not eligible target population. 

478. Brokalaki H, Matziou V, Zyga S, Kapella M, Tsaras 

K, Brokalaki E, Myrianthefs P. Omissions and errors 

during oxygen therapy of hospitalized patients in a 

large city of Greece. Intensive Crit Care Nurs. Dec 

2004;20(6):352-357. Not eligible target population. 

479. Bronder E. A decision that defies logic. Am J Nurs. 

Apr 2001;101(4):57-58. Comment. 

480. Brooks I. The lights are bright? Debating the future of 

the permanent night shift. J Manag Med. 1997;11(2-

3):58-70. Not eligible target population.

481. Broomfield D, Humphris GM, Fisher SE, Vaughan D, 

Brown JS, Lane S. The orofacial cancer patient's 

support from the general practitioner, hospital teams, 

family, and friends. J Cancer Educ. Winter 

1997;12(4):229-232. Not eligible target population. 

482. Brotherton JM, Bartlett MJ, Muscatello DJ, 

Campbell-Lloyd S, Stewart K, McAnulty JM. Do we 

practice what we preach? Health care worker 

screening and vaccination. Am J Infect Control. May 

2003;31(3):144-150. Not eligible target population. 

483. Brous E. How to handle that staffing predicament. 

Rn. May 2002;65(5):67-70. Comment. 

484. Brown B. How to develop a unit personnel budget. 

Nurs Manage. Jun 1999;30(6):34-35. No association 

tested. 

485. Brown B. Formula for an effective acuity system. 

Nurs Manage. Jun 1999;30(6):14. Comment. 

486. Brown C, Arnetz B, Petersson O. Downsizing within 

a hospital: cutting care or just costs? Soc Sci Med. 

Nov 2003;57(9):1539-1546. Not eligible target 

population. 

487. Brown G. Nursing is critically ill: why? What can be 

done to help alleviate the nursing shortage. Minor 

Nurse Newsl. Winter 2003;10(1):2. Comment. 

488. Brown H. Media frenzy follows diary publication. 

Nurs N Z. Aug 1996;2(7):7. News. 

489. Brown H. Nightmare on night shift. Nurs N Z. Jul 

1996;2(6):20. Comment. 

490. Brown PW, Fay MS. Sentinel event review, Part II: A 

new spirit of inquiry. Aspens Advis Nurse Exec. Oct 

1997;13(1):1, 5-6. Comment. 

491. Browne R, Miller E. Leading your leader. Nurs 

Manage. Oct 2003;34(10):58-62. Not eligible 

exposure. 

492. Brownson K, Dowd SB. Floating: a nurse's 

nightmare? Health Care Superv. Mar 1997;15(3):10-

15. No association tested. 

493. Bruce J, Wong I. Parenteral drug administration 

errors by nursing staff on an acute medical 

admissions ward during day duty. Drug Saf. 

2001;24(11):855-862. Not eligible target population. 

494. Bruera E, Willey JS, Ewert-Flannagan PA, Cline MK, 

Kaur G, Shen L, Zhang T, Palmer JL. Pain intensity 

assessment by bedside nurses and palliative care 

consultants: a retrospective study. Support Care 

Cancer. Apr 2005;13(4):228-231. Not eligible 

exposure. 

495. Brumfield VC, Kee CC, Johnson JY. Preoperative 

patient teaching in ambulatory surgery settings. Aorn 

J. Dec 1996;64(6):941-946, 948, 951-942. Not 

eligible exposure. 

496. Bruner DW. Radiation oncology nurses: staffing 

patterns and role development. Oncol Nurs Forum. 

May 1993;20(4):651-655. Review. 

497. Brunt BA. Continuing education evaluation of 

behavior change. J Nurses Staff Dev. Mar-Apr 

2000;16(2):49-54. Not eligible outcomes. 

498. Brusco MJ, Futch J, Showalter MJ. Nurse staff 

planning under conditions of a nursing shortage. J 

Nurs Adm. Jul-Aug 1993;23(7-8):58-64. No 

association tested. 

499. Bryan YE, Hitchings KS, Fuss MA, Fox MA, 

Kinneman MT, Young MJ. Measuring and evaluating 

hospital restructuring efforts. Eighteen-month followup and extension to critical care, Part 1. J Nurs Adm. 

Sep 1998;28(9):21-27. Not eligible exposure. 

500. Bryant C. Role clarification: a quality improvement 

survey of hospital chaplain customers. J Healthc 

Qual. Jul-Aug 1993;15(4):18-20. Not eligible 

exposure. 

501. Bryant CJ, Crean SJ, Hopper C. Maxillofacial surgery 

and the role of the extended day case. Br Dent J. Feb 

22 1997;182(4):134-138. Not eligible target 

population. 

502. Bryden DC, Gwinnutt CL. Tracheal intubation via the 

laryngeal mask airway: a viable alternative to direct 

laryngoscopy for nursing staff during 

cardiopulmonary resuscitation. Resuscitation. Jan 

1998;36(1):19-22. Not eligible exposure. 

503. Buchan J. Shifting patterns of nurses' work. Nurs 

Stand. Jun 16-22 1993;7(39):29. Comment. 

504. Buchan J. Lessons from America? US magnet 

hospitals and their implications for UK nursing. J Adv 

Nurs. Feb 1994;19(2):373-384. Review. 

505. Buchan J. Shifting the patterns of nurses' work. Nurs 

Stand. Aug 2-8 1995;9(45):29. Comment. 
B-15 

506. Buchan J. The shape of time to come. Nurs Stand. 

Mar 22-28 1995;9(26):22-23. Not eligible target 

population. 

507. Buchan J. Working on the bank: why do nurses do it? 

Nurs Stand. Mar 15-21 1995;9(25):33. Not eligible 

target population. 

508. Buchan J. The quality of mercy. Nurs Stand. Jun 11 

1997;11(38):22-23. Not eligible target population. 

509. Buchan J. The cost of understaffing. Nurs Stand. May 

21 1997;11(35):27. Comment. 

510. Buchan J. Workforce planning. Your country needs 

you. Health Serv J. Jul 16 1998;108(5613):22-25. Not 

eligible target population. 

511. Buchan J. Still attractive after all these years? Magnet 

hospitals in a changing health care environment. J 

Adv Nurs. Jul 1999;30(1):100-108. Review. 

512. Buchan J. Rethink the weighting game. Nurs Stand. 

Aug 2-8 2000;14(46):23. Comment. 

513. Buchan J. Recruitment. Happy landings? Health Serv 

J. Aug 24 2000;110(5719):24-27. Not eligible target 

population. 

514. Buchman TG, Ray SE, Wax ML, Cassell J, Rich D, 

Niemczycki MA. Families' perceptions of surgical 

intensive care. J Am Coll Surg. Jun 2003;196(6):977-

983. Review. 

515. Bucknall TK. Critical care nurses' decision-making 

activities in the natural clinical setting. Journal of 

clinical nursing Jan 2000;9(1):25-36. Not relevant.

516. Buerhaus PI, Donelan K, Ulrich BT, Norman L, 

Dittus R. Is the shortage of hospital registered nurses 

getting better or worse? Findings from two recent 

national surveys of RNs. Nurs Econ. Mar-Apr 

2005;23(2):61-71, 96, 55. Not eligible outcomes. 

517. Buerhaus PI, Staiger DO, Auerbach DI. New signs of 

a strengthening U.S. nurse labor market? Health 

affairs Jul-Dec 2004;23(Supplement 2):W4-526-33. 

Not relevant.

518. Buerhaus PI, Staiger DO, Auerbach DI. Implications 

of an Aging Registered Nurse Workforce. JAMA. 

June 14, 2000 2000;283(22):2948-2954. Not eligible 

outcomes. 

519. Buerhaus PI, Staiger DO, Auerbach DI. Is the current 

shortage of hospital nurses ending? Health Aff 

(Millwood). Nov-Dec 2003;22(6):191-198. Not 

eligible exposure. 

520. Buff DD, Shabti R. The night float system of resident 

on call: what do the nurses think? J Gen Intern Med. 

Jul 1995;10(7):400-402. Not eligible exposure.

521. Bull MJ. Patients' and professionals' perceptions of 

quality in discharge planning. J Nurs Care Qual. Jan 

1994;8(2):47-61. Not eligible exposure. 

522. Bupp JE, Dinger M, Lawrence C, Wingate S. 

Placement of cardiac electrodes: written, simulated, 

and actual accuracy. Am J Crit Care. Nov 

1997;6(6):457-462. Not eligible exposure. 

523. Burden B. Privacy or help? The use of curtain 

positioning strategies within the maternity ward 

environment as a means of achieving and maintaining 

privacy, or as a form of signalling to peers and 

professionals in an attempt to seek information or 

support. J Adv Nurs. Jan 1998;27(1):15-23. Not 

eligible target population. 

524. Burek C, Collins NA, Hodlin A. An easy way to 

communicate pathways to patients. Hosp Food Nutr 

Focus. Jun 1996;12(10):4; suppl 1 p. Comment. 

525. Burge J. Meet the travelers. Janis Burge. Rn. Jan 

2004;Suppl:12. Interview. 

526. Burgess L. Mixed-sex wards--the NT survey results. 

Nurs Times. Aug 3-9 1994;90(31):35-38. Not eligible 

exposure. 

527. Burgess L. Mixed-sex wards. Mixed responses. Nurs 

Times. Jan 12-18 1994;90(2):30-34. Not eligible 

exposure. 

528. Burhansstipanov L, Wound DB, Capelouto N, 

Goldfarb F, Harjo L, Hatathlie L, Vigil G, White M. 

Culturally relevant "Navigator" patient support. The 

Native sisters. Cancer Pract. May-Jun 1998;6(3):191-

194. No association tested. 

529. Burke RJ. Surviving hospital restructuring. Next 

steps. J Nurs Adm. Apr 2001;31(4):169-172. Not 

eligible outcomes. 

530. Burke RJ. Work experiences and psychological wellbeing of former hospital-based nurses now employed 

elsewhere. Psychol Rep. Dec 2002;91(3 Pt 2):1059-

1064. Not eligible outcomes. 

531. Burke RJ. Survivors and victims of hospital 

restructuring and downsizing: who are the real 

victims? Int J Nurs Stud. Nov 2003;40(8):903-909. 

Not eligible target population. 

532. Burke RJ. Hospital restructuring stressors: support 

and nursing staff perceptions of unit functioning. 

Health Care Manag (Frederick). Jul-Sep 

2003;22(3):241-248. Not eligible exposure. 

533. Burke RJ. Implementation of hospital restructuring 

and nursing staff perceptions of hospital functioning. 

J Health Organ Manag. 2004;18(4-5):279-289. Not 

eligible outcomes. 

534. Burke RJ. Work status congruence, work outcomes, 

and psychologic well-being. Health Care Manag 

(Frederick). Apr-Jun 2004;23(2):120-127. Not 

eligible outcomes. 

535. Burke RJ. Correlates of nursing staff survivor 

responses to hospital restructuring and downsizing. 

Health Care Manag (Frederick). Apr-Jun 

2005;24(2):141-149. Not eligible exposure. 

536. Burke RJ, Greenglass ER. Work-family congruence 

and work-family concerns among nursing staff. Can J 

Nurs Leadersh. May-Jun 1999;12(2):21-29. Not 

eligible exposure. 

537. Burke RL. When bad things happen to good 

organizations: a focused approach to recovery using 

the essentials of magnetism. Nurs Adm Q. Jul-Sep 

2005;29(3):228-240. Review. 

538. Burkle NL. Using 'weekenders' to staff the OR. Aorn 

J. Sep 1990;52(3):632, 634, 636. No association 

tested. 

539. Burke RJ, Greenglass ER. Juggling act: work 

concerns, family concerns. Canadian Nurse Oct 

2000;96(9):20-3. Inadequate date presentation. 

540. Burman ME. The impact of organizational and 

environmental factors on staffing in home health care. 

Public Health Nurs. Dec 1993;10(4):233-240. Not 

eligible target population. 
B-16 

541. Burnard P. Implications of client-centred counselling 

for nursing practice. Nurs Times. Jun 28-Jul 4 

1995;91(26):35-37. Comment. 

542. Burner OY, Cunningham P, Hattar HS. Managing a 

multicultural nurse staff in a multicultural 

environment. J Nurs Adm. Jun 1990;20(6):30-34. Not 

eligible outcomes. 

543. Burns J. Soviet nurses help alleviate Baltimore 

hospital's shortage. Mod Healthc. Aug 19 

1991;21(33):71, 73. Not eligible outcomes. 

544. Burns JP, Mitchell C, Griffith JL, Truog RD. End-oflife care in the pediatric intensive care unit: attitudes 

and practices of pediatric critical care physicians and 

nurses. Crit Care Med. Mar 2001;29(3):658-664. Not 

eligible outcomes. 

545. Burrows Z, O'Connor S. Let the team decide? 

Evaluation of self-rostering on an acute general 

medical ward. Prof Nurse. Nov 1993;9(2):86-90. Not 

eligible target population. 

546. Busby A, Gilchrist B. The role of the nurse in the 

medical ward round. J Adv Nurs. Mar 

1992;17(3):339-346. Not eligible target population. 

547. Bushy A. Critical access hospitals: rural nursing 

issues. J Nurs Adm. Jun 2001;31(6):301-310. 

Comment. 

548. Butler D, Oswald SL, Turner DE. The effects of 

demographics on determinants of perceived healthcare service quality. The case of users and observers. 

J Manag Med. 1996;10(5):8-20. Not eligible 

exposure. 

549. Butler L. Valuing research in clinical practice: a basis 

for developing a strategic plan for nursing research. 

Can J Nurs Res. Winter 1995;27(4):33-49. Not 

eligible outcomes. 

550. Buttery J, Eades M, Frisch S, Giguere M, Mountjoy 

A. Family response to difficult hospitalizations: the 

phenomenon of 'working through'. J Clin Nurs. Jul 

1999;8(4):459-466. Not eligible exposure. 

551. Byrd ME. Child-focused single home visiting. Public 

Health Nurs. Oct 1997;14(5):313-322. Not eligible 

exposure. 

552. Byrne G, Richardson M, Brunsdon J, Patel A. Patient 

satisfaction with emergency nurse practitioners in A 

& E. J Clin Nurs. Jan 2000;9(1):83-92. Not eligible 

target population. 

553. Cadigan S. Issues of recruitment and retention. Qld 

Nurse. Jan-Feb 1997;16(1):17. Comment. 

554. Cahill J. Patient's perceptions of bedside handovers. J 

Clin Nurs. Jul 1998;7(4):351-359. Not eligible target 

population. 

555. Cain M. Looking for positive changes in nursing. 

Nurs N Z. Aug 2002;8(7):28. Not eligible target 

population. 

556. Calabretta N, Cavanaugh SK. Education for 

inpatients: working with nurses through the clinical 

information system. Med Ref Serv Q. Summer 

2004;23(2):73-79. Not eligible exposure. 

557. Caldwell MF. Incidence of PTSD among staff victims 

of patient violence. Hosp Community Psychiatry. 

Aug 1992;43(8):838-839. Not eligible exposure. 

558. Callery P. Caring for parents of hospitalized children: 

a hidden area of nursing work. J Adv Nurs. Nov 

1997;26(5):992-998. Not eligible target population. 

559. Callery P, Smith L. A study of role negotiation 

between nurses and the parents of hospitalized 

children. J Adv Nurs. Jul 1991;16(7):772-781. Not 

eligible target population. 

560. Calliari D. The relationship between a calculation test 

given in nursing orientation and medication errors. J 

Contin Educ Nurs. Jan-Feb 1995;26(1):11-14. Not 

eligible exposure. 

561. Calliari D. A method to increase attendance at 

mandatory classes. J Nurs Staff Dev. Jul-Aug 

1996;12(4):213-215. Not eligible exposure. 

562. Calligaro KD, Miller P, Dougherty MJ, Raviola CA, 

DeLaurentis DA. Role of nursing personnel in 

implementing clinical pathways and decreasing 

hospital costs for major vascular surgery. J Vasc 

Nurs. Sep 1996;14(3):57-61. Not eligible exposure. 

563. Callister LC. The role of the nurse in childbirth: 

perceptions of the childbearing woman. Clin Nurse 

Spec. Nov 1993;7(6):288-293, 317. Not eligible 

exposure. 

564. Calpin-Davies PJ, Akehurst RL. Doctor-nurse 

substitution: the workforce equation. J Nurs Manag. 

Mar 1999;7(2):71-79. Not eligible target population. 

565. Campbell C. Annualised hours. Br J Perioper Nurs. 

Apr 2001;11(4):170-171. Not eligible target 

population. 

566. Campolo M, Pugh J, Thompson L, Wallace M. 

Pioneering the 12-hour shift in Australia--

implementation and limitations. Aust Crit Care. Dec 

1998;11(4):112-115. Not eligible target population. 

567. Canavan K. ANA study links nurse staffing to 

quality. Am Nurse. May-Jun 1997;29(3):1, 3. News. 

568 Canning S. The Beverly Allitt case. More questions 

than answers. Nurs Stand. Feb 23-Mar 1 

1994;8(22):20. Not eligible target population. 

569. Capitulo KL, Ankner ML, Miller J. Professional 

responsibility versus mandatory overtime. J Nurs 

Adm. Jun 2001;31(6):290-292. Comment. 

570. Caplan CA. Nursing staff and patient perceptions of 

the ward atmosphere in a maximum security forensic 

hospital. Arch Psychiatr Nurs. Feb 1993;7(1):23-29. 

Not eligible exposure. 

571. Capuano T, Bokovoy J, Halkins D, Hitchings K. 

Work flow analysis: eliminating non-value-added 

work. J Nurs Adm. May 2004;34(5):246-256. Not 

eligible exposure. 

572. Capuano T, Bokovoy J, Hitchings K, Houser J. Use of 

a validated model to evaluate the impact of the work 

environment on outcomes at a magnet hospital. 

Health Care Manage Rev. Jul-Sep 2005;30(3):229-

236. Not eligible outcomes. 

573. Caraher M. A sociological approach to health 

promotion for nurses in an institutional setting. J Adv 

Nurs. Sep 1994;20(3):544-551. Not eligible target 

population. 

574. Carey RG, Teeters JL. CQI case study: reducing 

medication errors. Jt Comm J Qual Improv. May 

1995;21(5):232-237. Not eligible exposure. 
B-17 

575. Carlisle D. Paint and perseverance. Nurs Times. Dec 

11-17 1991;87(50):39. Comment. 

576. Carlisle D. Arts in action. A stately pleasure dome. 

Nurs Times. Apr 17-23 1991;87(16):28-29. Comment. 

577. Carlisle D. A nurse in any language. Nurs Times. Sep 

25-Oct 1 1996;92(39):26-27. Comment. 

578. Carlisle D, Hempel S. Conduct unbecoming? Nurs 

Times. Jul 24-30 1991;87(30):18. Comment. 

579. Carlowe J. Don't bank on it. Nurs Stand. Mar 18-24 

1998;12(26):15. News. 

580. Carlowe J. Trial by error. Nurs Times. Jul 23-29 

2002;98(30):22-24. Not eligible target population. 

581. Carr A. GRASPing the nettle, the introduction of a 

workload measurement tool into an accident and 

emergency department. Accid Emerg Nurs. Jan 

1994;2(1):21-26. No association tested.

582. Carr SM. Refocusing health visiting -- sharpening the 

vision and facilitating the process. J Nurs Manag. 

May 2005;13(3):249-256. Not eligible target 

population. 

583. Carr-Hill RA, Jenkins-Clarke S. Measurement 

systems in principle and in practice: the example of 

nursing workload. J Adv Nurs. Aug 1995;22(2):221-

225. Not eligible target population. 

584. Carrick JA. Determining case manager workload: are 

there secrets to success? Nurs Case Manag. May-Jun 

1998;3(3):128-130. Comment. 

585. Carroll-Johnson RM. The good news and the bad 

news. Nurs Diagn. Jan-Mar 2002;13(1):3-4. Editorial.

586. Carter H, MacInnes P. Nursing attitudes to the care of 

elderly patients at risk of continuing hospital care. J 

Adv Nurs. Sep 1996;24(3):448-455. Not eligible 

target population. 

587. Carter M. Betrayal of trust. Nurs Times. Aug 11-17 

1999;95(32):34-35. Case Reports. 

588. Carveth JA. Perceived patient deviance and avoidance 

by nurses. Nurs Res. May-Jun 1995;44(3):173-178. 

Not eligible exposure. 

589. Carzoli RP, Martinez-Cruz M, Cuevas LL, Murphy S, 

Chiu T. Comparison of neonatal nurse practitioners, 

physician assistants, and residents in the neonatal 

intensive care unit. Arch Pediatr Adolesc Med. Dec 

1994;148(12):1271-1276. Not eligible exposure. 

590. Cassard SD, Weisman CS, Gordon DL, Wong R. The 

impact of unit-based self-management by nurses on 

patient outcomes. Health Serv Res. Oct 

1994;29(4):415-433. Not eligible exposure. 

591. Castledine G. Case 22: The incompetent practitioner. 

Serious concerns about a nurse's basic competencies. 

Br J Nurs. Mar 9-22 2000;9(5):259. Not eligible 

target population. 

592. Castledine G. Nurses need to sort out their system of 

care. Br J Nurs. Mar 8-21 2001;10(5):350. Not 

eligible target population. 

593. Castledine G. Nurse in charge who walked out on an 

understaffed ward. Br J Nurs. Oct 24-Nov 13 

2002;11(19):1231. Editorial. 

594. Castledine G. Nurse who covered up for a sister who 

was having problems. Br J Nurs. Jan 23-Feb 12 

2003;12(2):79. Case Reports.

595. Castledine G. Staff nurse who had an alcohol problem 

and made nursing errors. Br J Nurs. Nov 25-Dec 8 

2004;13(21):1288. Not eligible target population. 

596. Castledine G. Senior nurse whose incompetence 

resulted in the death of a patient. Br J Nurs. May 12-

25 2005;14(9):516. Not eligible target population. 

597. Castleforte MR, Fraser L. Yes, primary nursing can 

survive 12-hour shifts. Nurs Manage. Mar 

1995;26(3):64-65. Comment.

598. Catalani C, Biggeri A, Gottard A, Benvenuti M, Frati 

E, Cecchini C. Prevalence of HCV infection among 

health care workers in a hospital in central Italy. Eur J 

Epidemiol. 2004;19(1):73-77. Not eligible target 

population. 

599. Caterinicchio MJ. Redefining nursing according to 

patients' and families' needs: an evolving concept. 

AACN Certification Corporation. AACN Clin Issues. 

Feb 1995;6(1):153-156. Comment. 

600. Cating G. Mandatory OT is the last straw. Revolution. 

Sep-Oct 2000;1(5):4. Letter. 

601. Caty S, Larocque S, Koren I. Family-centered care in 

Ontario general hospitals: the views of pediatric 

nurses. Can J Nurs Leadersh. May-Jun 

2001;14(2):10-18. Not eligible outcomes. 

602. Cavan DA, Hamilton P, Everett J, Kerr D. Reducing 

hospital inpatient length of stay for patients with 

diabetes. Diabet Med. Feb 2001;18(2):162-164. Not 

eligible target population. 

603. Celia B. Age and gender differences in pain 

management following coronary artery bypass 

surgery. J Gerontol Nurs. May 2000;26(5):7-13; quiz 

52-13. Not eligible exposure. 

604. Ceria CD. Nursing absenteeism and its effects on the 

quality of patient care. J Nurs Adm. Dec 

1992;22(12):11, 38. Not eligible outcomes.

605. Cerrai T, Michelassi S, Ierpi C, Toti G, Zignego AL, 

Lombardi M. Universal precautions and dedicated 

machines as cheap and effective measures to control 

HCV spread. Edtna Erca J. Apr-Jun 1998;24(2):43-

45, 48. Not eligible target population. 

606. Chaaya M, Rahal B, Morou G, Kaiss N. 

Implementing patient-centered care in Lebanon. J 

Nurs Adm. Sep 2003;33(9):437-440. Not eligible 

target population. 

607. Chamberlain G, Wraight A, Crowley P. Birth at 

home. Pract Midwife. Jul-Aug 1999;2(7):35-39. Not 

eligible target population. 

608. Chan DS. Validation of the Clinical Learning 

Environment Inventory. West J Nurs Res. Aug 

2003;25(5):519-532. Not eligible target population.

609. Chan FS. An evaluation of the role of the night nurse 

practitioner. Nurs Times. Sep 18-23 1996;92(38):38-

39. Not eligible target population.

610. Chan JC, Chu RW, Young BW, Chan F, Chow CC, 

Pang WC, Chan C, Yeung SH, Chow PK, Lau J, 

Leung PM. Use of an electronic barcode system for 

patient identification during blood transfusion: 3-year 

experience in a regional hospital. Hong Kong Med J. 

Jun 2004;10(3):166-171. Not eligible target 

population. 
B-18 

611. Chan R, Molassiotis A, Chan E, Chan V, Ho B, Lai 

CY, Lam P, Shit F, Yiu I. Nurses' knowledge of and 

compliance with universal precautions in an acute 

care hospital. Int J Nurs Stud. Feb 2002;39(2):157-

163. Not eligible target population. 

612. Chan S, Lam TH. Preventing exposure to secondhand smoke. Semin Oncol Nurs. Nov 

2003;19(4):284-290. Not eligible target population. 

613. Chan SS, Leung GM, Tiwari AF, Salili F, Leung SS, 

Wong DC, Wong AS, Lai AS, Lam TH. The impact 

of work-related risk on nurses during the SARS 

outbreak in Hong Kong. Fam Community Health. JulSep 2005;28(3):274-287. Not eligible target 

population. 

614. Chandler C. Solutions for inadequate staffing. Am J 

Nurs. Oct 2003;103(10):14. Comment. 

615. Chandra A, Willis WK. Importing nurses: combating 

the nursing shortage in America. Hosp Top. Spring 

2005;83(2):33-37. Review. 

616. Chang AM, Lam LW. Evaluation of a health care 

assistant pilot programme. J Nurs Manag. Jul 

1997;5(4):229-236. Not eligible target population. 

617. Chang E, Hancock K, Chenoweth L, Jeon YH, 

Glasson J, Gradidge K, Graham E. The influence of 

demographic variables and ward type on elderly 

patients' perceptions of needs and satisfaction during 

acute hospitalization. Int J Nurs Pract. Jun 

2003;9(3):191-201. Not eligible target population. 

618. Chang SO. The conceptual structure of physical touch 

in caring. J Adv Nurs. Mar 2001;33(6):820-827. Not 

eligible target population. 

619. Charles J. Mandatory overtime: conflicts of 

conscience? JONAS Healthc Law Ethics Regul. Mar 

2002;4(1):10-12. Review. 

620. Chartier K. Fighting the shortage with strong 

retention strategies--University of Michigan Health 

System model. Nephrol News Issues. Jul 

2004;18(8):28, 79. Comment. 

621. Chartier K. National nurse-to-patient ratio proposed. 

Nephrol News Issues. Jul 2004;18(8):23. News. 

622. Chartier K. Staff ratios: California law may spread to 

other states. Nephrol News Issues. Apr 

2004;18(5):22. Comment. 

623. Cheek J. Nurses and the administration of 

medications. Broadening the focus. Clin Nurs Res. 

Aug 1997;6(3):253-274. Not eligible target 

population. 

624. Chen WT, Han M, Holzemer WL. Nurses' 

knowledge, attitudes, and practice related to HIV 

transmission in northeastern China. AIDS Patient 

Care STDS. Jul 2004;18(7):417-422. Not eligible 

target population. 

625. Chesanow N. A medical crisis: who'll care for your 

patients? Med Econ. May 7 2001;78(9):67-68, 72, 74. 

Comment.

626. Chevron V, Menard JF, Richard JC, Girault C, Leroy 

J, Bonmarchand G. Unplanned extubation: risk 

factors of development and predictive criteria for 

reintubation. Crit Care Med. Jun 1998;26(6):1049-

1053. Not eligible target population. 

627. Chewitt MD, Fallis WM, Suski MC. The surgical 

hotline. Bridging the gap between hospital and home. 

J Nurs Adm. Dec 1997;27(12):42-49. Not eligible 

exposure. 

628. Ching TY, Seto WH. Evaluating the efficacy of the 

infection control liaison nurse in the hospital. J Adv 

Nurs. Oct 1990;15(10):1128-1131. Not eligible target 

population. 

629. Cho SH. Nurse staffing and adverse patient outcomes: 

a systems approach. Nurs Outlook. Mar-Apr 

2001;49(2):78-85. Review. 

630. Cho SH. Using multilevel analysis in patient and 

organizational outcomes research. Nurs Res. Jan-Feb 

2003;52(1):61-65. Review. 

631. Choi E, Song M. Physical restraint use in a Korean 

ICU. J Clin Nurs. Sep 2003;12(5):651-659. Not 

eligible target population. 

632. Choi J, Bakken S, Larson E, Du Y, Stone PW. 

Perceived nursing work environment of critical care 

nurses. Nurs Res. Nov-Dec 2004;53(6):370-378. Not 

eligible exposure. 

633. Choi T, Jameson H, Brekke ML, Podratz RO, 

Mundahl H. Effects on nurse retention. An 

experiment with scheduling. Med Care. Nov 

1986;24(11):1029-1043. Not eligible year. 

634. Choi-Kwon S, Lee SK, Park HA, Kwon SU, Ahn JS, 

Kim JS. What stroke patients want to know and what 

medical professionals think they should know about 

stroke: Korean perspectives. Patient Educ Couns. Jan 

2005;56(1):85-92. Not eligible target population. 

635. Chokbunyasit N, Potacharoen O, Sirisanthana T. 

Prevalence of HBV infection in nurses and manual 

workers in Maharaj Nakorn Chiang Mai Hospital. J 

Med Assoc Thai. Jul 1995;78 Suppl 1:S19-25. Not 

eligible target population. 

636. Chong J, Marshall BJ, Barkin JS, McCallum RW, 

Reiner DK, Hoffman SR, O'Phelan C. Occupational 

exposure to Helicobacter pylori for the endoscopy 

professional: a sera epidemiological study. Am J 

Gastroenterol. Nov 1994;89(11):1987-1992. Not 

eligible exposure. 

637. Chou KR, Lu RB, Mao WC. Factors relevant to 

patient assaultive behavior and assault in acute 

inpatient psychiatric units in Taiwan. Arch Psychiatr 

Nurs. Aug 2002;16(4):187-195. Not eligible target 

population. 

638. Christensen P. RNs--hands-on care and more. Nurs 

Spectr (Wash D C). Jan 13 1997;7(1):3. Editorial. 

639. Christmas AB, Reynolds J, Hodges S, Franklin GA, 

Miller FB, Richardson JD, Rodriguez JL. Physician 

extenders impact trauma systems. J Trauma. May 

2005;58(5):917-920. Not eligible exposure. 

640. Christmas D. Meet the travelers. Diane Christmas. 

Rn. Jan 2004;Suppl:30. Interview. 

641. Chung K, Choi YB, Moon S. Toward efficient 

medication error reduction: error-reducing 

information management systems. J Med Syst. Dec 

2003;27(6):553-560. Review.

642. Chung LH, Chong S, French P. The efficiency of 

fluid balance charting: an evidence-based 

management project. J Nurs Manag. Mar 

2002;10(2):103-113. Not eligible target population. 
B-19 

643. Cimino MA, Kirschbaum MS, Brodsky L, Shaha SH. 

Assessing medication prescribing errors in pediatric 

intensive care units. Pediatr Crit Care Med. Mar 

2004;5(2):124-132. Not eligible exposure. 

644. Cimiotti JP, Wu F, Della-Latta P, Nesin M, Larson E. 

Emergence of resistant staphylococci on the hands of 

new graduate nurses. Infect Control Hosp Epidemiol. 

May 2004;25(5):431-435. Not eligible outcomes. 

645. Cina J, Baroletti S, Churchill W, Hayes J, Messinger 

C, Mogan-McCarthy P, Harmuth Y. Interdisciplinary 

education program for nurses and pharmacists. Am J 

Health Syst Pharm. Nov 1 2004;61(21):2294-2296. 

Not eligible exposure.

646. Cirone N. Taking orders by phone? Nursing. Aug 

1998;28(8):56-57. Comment.

647. Clark AP. Nurse staffing levels and prevention of 

adverse events. Clin Nurse Spec. Sep 2002;16(5):237-

238. Review. 

648. Clark BA, Rutledge C, Bush S, Knaub G, Beeken JE, 

Larsen PD. An experience with "research by 

committee". J Nurses Staff Dev. Sep-Oct 

1998;14(5):244-249. Not eligible exposure. 

649. Clark JS. An aging population with chronic disease 

compels new delivery systems focused on new 

structures and practices. Nurs Adm Q. Apr-Jun 

2004;28(2):105-115. Not eligible exposure. 

650. Clark K, Normile LB. Delays in implementing 

admission orders for critical care patients associated 

with length of stay in emergency departments in six 

mid-Atlantic states. J Emerg Nurs. Dec 

2002;28(6):489-495. Not eligible exposure. 

651. Clark MF. Traveling nurses. One solution to 

supplementing your OR staff. Aorn J. May 

1992;55(5):1249-1253. No association tested. 

652. Clark N, Kiyimba F, Bowers L, Jarrett M, McFarlane 

L. Absconding: nurses views and reactions. J 

Psychiatr Ment Health Nurs. Jun 1999;6(3):219-224. 

Not eligible target population.

653. Clarke A, Hadfield-Law L, Neal K. I've been told I 

have to move to another part of the unit, but I don't 

want to go. What doI do? Nurs Times. May 4-10 

2000;96(18):30. Comment. 

654. Clarke M. Speaking up. Nurs Times. Jan 13-19 

1993;89(2):42-44. Comment. 

655. Clarke SP. Balancing staffing and safety. Nurs 

Manage. Jun 2003;34(6):44-48. Review. 

656. Clarke SP. The policy implications of staffingoutcomes research. J Nurs Adm. Jan 2005;35(1):17-

19. Review. 

657. Clarke SP, Aiken LH. Failure to rescue. Am J Nurs. 

Jan 2003;103(1):42-47. Review. 

658. Clarke SP, Sloane DM, Aiken LH. Effects of hospital 

staffing and organizational climate on needlestick 

injuries to nurses. Am J Public Health. Jul 

2002;92(7):1115-1119. Not eligible outcomes. 

659. Clarke T, Abbenbroek B, Hardy L. The impact of a 

high dependency unit continuing education program 

on nursing practice and patient outcomes. Aust Crit 

Care. Dec 1996;9(4):138-147, 149. Not eligible target 

population. 

660. Clay ML. An opinion: staff nurses at risk; increasing 

use of practical nurses. Pa Nurse. Mar 1997;52(3):7. 

Comment. 

661. Cleary M, Edwards C. 'Something always comes up': 

nurse-patient interaction in an acute psychiatric 

setting. J Psychiatr Ment Health Nurs. Dec 

1999;6(6):469-477. Not eligible target population. 

662. Cleary PD. A hospitalization from hell: a patient's 

perspective on quality. Ann Intern Med. Jan 7 

2003;138(1):33-39. Case Reports. 

663. Clement J. "Change is inevitable and desirable": an 

interview with Ontario's Minister of Health and LongTerm Care. Interview by Peggy Leatt. Hosp Q. Fall 

2001;5(1):56-59. Interview. 

664. Clifton B. The end is night. Nurs Stand. Oct 20-26 

1993;8(5):45. Comment. 

665. Cline D, Reilly C, Moore JF. What's behind RN 

turnover? Nurs Manage. Oct 2003;34(10):50-53. 

Comment.

666. Clissold G, Smith P, Acutt B. The impact of unwaged 

domestic work on the duration and timing of sleep of 

female nurses working full-time on rotating 3-shift 

rosters. J Hum Ergol (Tokyo). Dec 2001;30(1-2):345-

349. Not eligible target population. 

667. Coates M, Heilmann S. Self-scheduling: a practical 

application of shared governance. Aspens Advis 

Nurse Exec. Aug 1993;8(11):6-7. Comment. 

668. Cobb MD. Dealing fairly with medication errors. 

Nursing. Mar 1990;20(3):42-43. Comment. 

669. Cody WK. Affirming reflection. Nurs Sci Q. Jan 

1999;12(1):4-6. Comment.

670. Cohen H, Mandrack MM. Application of the 80/20 

rule in safeguarding the use of high-alert medications. 

Crit Care Nurs Clin North Am. Dec 2002;14(4):369-

374. Not eligible exposure. 

671. Cohen LM, McCue JD, Green GM. Do clinical and 

formal assessments of the capacity of patients in the 

intensive care unit to make decisions agree? Arch 

Intern Med. Nov 8 1993;153(21):2481-2485. Not 

eligible exposure. 

672. Cohen MR. Special care units need all pharmacy 

services. Nursing. Sep 1990;20(9):12. Comment. 

673. Cohen MR. Don't let doctors intimidate you. Nursing. 

Jan 1992;22(1):18. Case Reports. 

674. Cohen MR, Davis NM. Comments on ASHP 

guidelines for preventing medication errors. Am J 

Hosp Pharm. May 1993;50(5):913. Comment. 

675. Cohen MZ, Hausner J, Johnson M. Knowledge and 

presence: accountability as described by nurses and 

surgical patients. J Prof Nurs. May-Jun 

1994;10(3):177-185. Not eligible exposure. 

676. Cohen-Katz J, Wiley S, Capuano T, Baker DM, 

Deitrick L, Shapiro S. The effects of mindfulnessbased stress reduction on nurse stress and burnout: a 

qualitative and quantitative study, part III. Holist Nurs 

Pract. Mar-Apr 2005;19(2):78-86. Not eligible 

exposure. 

677. Cohran J, Larson E, Roach H, Blane C, Pierce P. 

Effect of intravascular surveillance and education 

program on rates of nosocomial bloodstream 

infections. Heart Lung. Mar-Apr 1996;25(2):161-164. 

Not eligible exposure. 
B-20 

678. Coile RC, Jr. Nursing workforce shortages: "code 

blue" for RN staffing across America. Russ Coiles 

Health Trends. Nov 2001;14(1):1, 4-7. Comment.

679. Cole A. Shifting shifts. Nurs Times. May 15-21 

1991;87(20):21. Comment. 

680. Cole A. Satisfied customers. Nurs Times. Mar 6-12 

1996;92(10):20-21. News. 

681. Coleman JC, Paul GL. Relationship between staffing 

ratios and effectiveness of inpatient psychiatric units. 

Psychiatr Serv. Oct 2001;52(10):1374-1379. Not 

eligible outcomes. 

682. Coleman S, Dracup K, Moser DK. Comparing 

methods of cardiopulmonary resuscitation instruction 

on learning and retention. J Nurs Staff Dev. Mar-Apr 

1991;7(2):82-87. Not eligible exposure. 

683. Colen HB, Neef C, Schuring RW. Identification and 

verification of critical performance dimensions. Phase 

1 of the systematic process redesign of drug 

distribution. Pharm World Sci. Jun 2003;25(3):118-

125. Not eligible target population.

684. Collier V, Fraser J, Evans C. Change from the bottom 

up. Nurs Times. Feb 4-10 1998;94(5):68-69. 

Comment. 

685. Collins SE. Nurse attorney notes. Fla Nurse. Feb-Mar 

1996;44(3):13. Legal Cases.

686. Colodny A. Spinal cord injury nurses in action: 

partners in practice. SCI Nurs. Sep 1997;14(3):79-82. 

No association tested. 

687. Comack M, Smith SD, Bowman A, Gillow K, Hunt 

M, Snell L, Thomsen F, Turner D. Planning change in 

scheduling practices: a theoretical perspective. Can J 

Nurs Adm. Mar-Apr 1991;4(1):17-21. No association 

tested. 

688. Condliffe B. Witness for the prosecution. Nurs Times. 

Jul 19-25 2001;97(29):26-27. Not eligible target 

population. 

689. Conklin D, MacFarland V, Kinnie-Steeves A, 

Chenger P. Medication errors by nurses: contributing 

factors. AARN News Lett. Jan 1990;46(1):8-9. No 

association tested. 

690. Connell J, Bradley S. Visiting children in hospital: a 

vision from the past. Paediatr Nurs. Apr 

2000;12(3):32-35. Not eligible target population. 

691. Conners AM. Patient classification system in a rural 

emergency department. Accid Emerg Nurs. Jan 

1994;2(1):7-20. No association tested. 

692. Connor D. Family-centred care in practice. Nurs N Z. 

May 1998;4(4):18-19. Not eligible target population. 

693. Considine J, Ung L, Thomas S. Triage nurses' 

decisions using the National Triage Scale for 

Australian emergency departments. Accid Emerg 

Nurs. Oct 2000;8(4):201-209. Not eligible target 

population. 

694. Conway R. The mysteries of the Milton Tank! Nurs 

Prax N Z. Nov 1996;11(3):27-31. Not eligible target 

population. 

695. Cook AF, Hoas H, Guttmannova K, Joyner JC. An 

error by any other name. Am J Nurs. Jun 

2004;104(6):32-43; quiz 44. Not eligible outcomes.

696. Cook DJ, Guyatt GH, Jaeschke R, Reeve J, Spanier 

A, King D, Molloy DW, Willan A, Streiner DL. 

Determinants in Canadian health care workers of the 

decision to withdraw life support from the critically 

ill. Canadian Critical Care Trials Group. Jama. Mar 1 

1995;273(9):703-708. Not eligible exposure.

697. Cook R. Day in the life: Back to school nurses. Nurs 

Stand. Aug 12-18 1992;6(47):45. Comment. 

698. Cooke P. One-to-one midwifery: Part 6. Mod 

Midwife. Sep 1996;6(9):23-25. Comment. 

699. Cookson ST, Ihrig M, O'Mara EM, Denny M, Volk 

H, Banerjee SN, Hartstein AI, Jarvis WR. Increased 

bloodstream infection rates in surgical patients 

associated with variation from recommended use and 

care following implementation of a needleless device. 

Infect Control Hosp Epidemiol. Jan 1998;19(1):23-

27. Not eligible exposure. 

700. Coombs M. The challenge facing critical care nurses 

in the UK: a personal perspective. Nurs Crit Care. 

Mar-Apr 1999;4(2):81-84. Not eligible target 

population. 

701. Cooper C, Connor T. Easing winter pressure: 

commissioning and evaluating a medical day case 

unit. Nurs Stand. Jun 30-Jul 6 1999;13(41):32-34. Not 

eligible target population. 

702. Cooper J, Spencer D. The challenges and benefits of 

job sharing in palliative care education. Br J Nurs. 

Oct 9-22 1997;6(18):1071-1075. Not eligible target 

population. 

703. Cooper JE, Tate R, Yassi A. Work hardening in an 

early return to work program for nurses with back 

injury. WORK: A Journal of Prevention, Assessment 

& Rehabilitation Mar 1997;8(2):149-56. Not relevant. 

704. Cooper MC. Can a zero defects philosophy be applied 

to drug errors? J Adv Nurs. Mar 1995;21(3):487-491. 

Not eligible target population. 

705. Cooper PG. Nurse-patient ratios revisited. Nurs 

Forum. Apr-Jun 2004;39(2):3-4. Editorial. 

706. Copeland-Fields L, Griffin T, Jenkins T, Buckley M, 

Wise LC. Comparison of outcome predictions made 

by physicians, by nurses, and by using the Mortality 

Prediction Model. Am J Crit Care. Sep 

2001;10(5):313-319. Not eligible exposure.

707. Corby S. Opportunity 2000 in the National Health 

Service: a missed opportunity for women. J Manag 

Med. 1997;11(5-6):279-293. Not eligible target 

population. 

708. Corder L. Part-time working. Level the playing field. 

Nurs Times. Feb 28-Mar 5 1996;92(9):30-32. Not 

eligible target population. 

709. Corley MC, Huff S, Sayles L, Short L. Patient and 

nurse criteria for heart transplant candidacy. Medsurg 

Nurs. Jun 1995;4(3):211-215. Not eligible exposure. 

710. Cormack K. Audit of consent forms. Br J Theatre 

Nurs. Dec 1998;8(9):14-16. Not eligible target 

population. 

711. Corona GG. We turned med/surg staff into telemetry 

experts. Rn. Oct 1992;55(10):21-22, 24. No 

association tested. 

712. Costello A, Tsushima ST. Agency nursing: one 

hospital's experience. Nurs Manage. Feb 

1996;27(2):63, 65, 67. Comment. 
B-21 

713 Costello A, Tsushima ST. Notes from the field. 

Agency nursing: one hospital's experience. Nursing 

management Feb 1996;27(2):63, 5, 7. Inadequate 

data presentation.

714. Costello K. Managed competition vs. single payer: 

what's best for patients and RNs? Calif Nurse. Jun 

1994;90(6):6. Comment. 

715. Coston B. Fighting through an appeals process. Rn. 

Feb 1995;58(2):57-59. Comment. 

716. Coughlin C. Care centered organizations, Part 2. The 

changing role of the nurse executives. J Nurs Adm. 

Mar 2001;31(3):113-120. No association tested. 

717. Cowin L. The effects of nurses' job satisfaction on 

retention: an Australian perspective. J Nurs Adm. 

May 2002;32(5):283-291. Not eligible target 

population. 

718. Cox C. Should we be getting danger money? Nurs 

Times. Jul 19-25 2001;97(29):23. Comment.

719. Coyle GA, Heinen M. Evolution of BCMA within the 

Department of Veterans Affairs. Nurs Adm Q. JanMar 2005;29(1):32-38. Not eligible exposure. 

720. Coyle J, Williams B. Valuing people as individuals: 

development of an instrument through a survey of 

person-centredness in secondary care. J Adv Nurs. 

Nov 2001;36(3):450-459. Not eligible target 

population. 

721. Craig EA, Hanna IT, McGilvray S, Docherty P, 

Donlevy S. Nurse or doctor: biometry for intraocular 

lens power calculation, who should measure? Health 

Bull (Edinb). Mar 1995;53(2):105-109. Not eligible 

target population. 

722. Cramer LD, McCorkle R, Cherlin E, JohnsonHurzeler R, Bradley EH. Nurses' attitudes and 

practice related to hospice care. J Nurs Scholarsh. 

2003;35(3):249-255. Not eligible target population.

723. Crandall M. Nurse-to-patient ratios. Addressing 

concerns in legislation. AWHONN Lifelines. AprMay 2000;4(2):21. News.

724. Crellin DJ, Johnston L. Poor agreement in application 

of the Australasian Triage Scale to paediatric 

emergency department presentations. Contemp Nurse. 

Aug 2003;15(1-2):48-60. Not eligible target 

population. 

725. Crimlisk JT, McNulty MJ, Francione DA. New 

graduate RNs in a float pool. An inner-city hospital 

experience. J Nurs Adm. Apr 2002;32(4):211-217. 

Not eligible exposure. 

726. Crispin C, Daffurn K. Nurses' responses to acute 

severe illness. Aust Crit Care. Dec 1998;11(4):131-

133. Not eligible target population. 

727. Crome P, McDaniel C, Rotunna S, Tachibana C. 

Staffing solutions: an in-house agency. Nurs Manage. 

Aug 1993;24(8):64A-64B, 64D, 64F. Not eligible 

outcomes. 

728. Cronin-Stubbs D, Swanson B, Dean-Baar S, Sheldon 

JA, Duchene P. The effects of a training program on 

nurses' functional performance assessments. Appl 

Nurs Res. Feb 1992;5(1):38-43. Not eligible 

exposure. 

729. Crouch D. 'I'm delighted the new role is making a 

difference'. Nurs Times. Nov 25-Dec 1 

2003;99(47):26-27. Comment.

730. Crout LA, Chang E, Cioffi J. Why do registered 

nurses work when ill? J Nurs Adm. Jan 

2005;35(1):23-28. Not eligible target population. 

731. Crow D. Foreign nurse recruitment. Healthtexas. Aug 

1991;47(2):10-11. Comment. 

732. Crownover AJ. The other foot: who is an agency 

nurse? Tenn Nurse. Spring 1993;56(1):15, 20. 

Comment. 

733. Cruickshank JF, MacKay RC, Matsuno K, Williams 

AM. Appraisal of the clinical competence of 

registered nurses in relation to their designated levels 

in the Western Australian nursing career structure. Int 

J Nurs Stud. Jun 1994;31(3):217-230. Not eligible 

target population. 

734. Cullen L, Greiner J, Bombei C, Comried L. 

Excellence in evidence-based practice: organizational 

and unit exemplars. Crit Care Nurs Clin North Am. 

Jun 2005;17(2):127-142. Not eligible exposure.

735. Cumbie SA, Conley VM, Burman ME. Advanced 

practice nursing model for comprehensive care with 

chronic illness: model for promoting process 

engagement. ANS Adv Nurs Sci. Jan-Mar 

2004;27(1):70-80. Not eligible exposure. 

736. Cupitt JM, Vinayagam S, McConachie I. Radiation 

exposure of nurses on an intensive care unit. 

Anaesthesia. Feb 2001;56(2):183. Letter.

737. Curley MA. Caring for parents of critically ill 

children. Crit Care Med. Sep 1993;21(9 Suppl):S386-

387. No association tested. 

738. Curry L, Porter M, Michalski M, Gruman C. 

Individualized care: perceptions of certified nurse's 

aides. J Gerontol Nurs. Jul 2000;26(7):45-51; quiz 52-

43. Not eligible target population.

739. Curtin L. Policies hinder nursing staff. J Emerg Nurs. 

Dec 2000;26(6):539. Letter. 

740. Curtin LL. Lean, mean and stupid! Nurs Manage. 

May 1997;28(5):7-8. Editorial. 

741. Curtin LL. An integrated analysis of nurse staffing 

and related variables: effects on patient outcomes. 

Online J Issues Nurs. 2003;8(3):5. Review. 

742. Czaplinski C, Diers D. The effect of staff nursing on 

length of stay and mortality. Med Care. Dec 

1998;36(12):1626-1638. Not eligible exposure. 

743. Czurylo K, Gattuso M, Epsom R, Ryan C, Stark B. 

Continuing education outcomes related to pain 

management practice. J Contin Educ Nurs. Mar-Apr 

1999;30(2):84-87. Not eligible exposure.

744. D'Addario V, Curley A. How case management can 

improve the quality of patient care. Int J Qual Health 

Care. Dec 1994;6(4):339-345. Not eligible outcomes. 

745. D'Agata EM, Wise S, Stewart A, Lefkowitz LB, Jr. 

Nosocomial transmission of Mycobacterium 

tuberculosis from an extrapulmonary site. Infect 

Control Hosp Epidemiol. Jan 2001;22(1):10-12. Not 

eligible exposure. 

746. Daghistani D, Horn M, Rodriguez Z, Schoenike S, 

Toledano S. Prevention of indwelling central venous 

catheter sepsis. Med Pediatr Oncol. Jun 

1996;26(6):405-408. Not eligible exposure.
B-22 

747. Dahlman GB, Dykes AK, Elander G. Patients' 

evaluation of pain and nurses' management of 

analgesics after surgery. The effect of a study day on 

the subject of pain for nurses working at the thorax 

surgery department. J Adv Nurs. Oct 1999;30(4):866-

874. Not eligible target population. 

748. Dalayon AP. Components of preoperative patient 

teaching in Kuwait. J Adv Nurs. Mar 1994;19(3):537-

542. Not eligible target population. 

749. Dale C, Lynch J. Blueprint for healthcare. Nurs 

Manag (Harrow). Oct 1996;3(6):22-24. Not eligible 

target population. 

750. Dale J, Williams S, Wellesley A, Glucksman E. 

Training and supervision needs and experience: a 

longitudinal, cross-sectional survey of accident and 

emergency department senior house officers. Postgrad 

Med J. Feb 1999;75(880):86-89. Not eligible target 

population. 

751. Daly BJ, Phelps C, Rudy EB. A nurse-managed 

special care unit. J Nurs Adm. Jul-Aug 1991;21(7-

8):31-38. Comment.

752. Daly BJ, Thomas D, Dyer MA. Procedures used in 

withdrawal of mechanical ventilation. Am J Crit Care. 

Sep 1996;5(5):331-338. Not eligible Exposure. 

753. Danchaivijitr S, Suthisanon L, Jitreecheue L, 

Tantiwatanapaibool Y. Effects of education on the 

prevention of pressure sores. J Med Assoc Thai. Jul 

1995;78 Suppl 1:S1-6. Not eligible target population. 

754. Dandrinos-Smith S, Garman DA, Baranowski SL, 

Davol LH, Person CD. The making of a supermodel. 

Nurs Manage. Oct 2000;31(10):33-36. Comment. 

755. Daniel M, Banerjee AR. Is a doctor needed in the 

adult ENT pre-admission clinic? J Laryngol Otol. Oct 

2004;118(10):796-798. Not eligible target population.

756. Dann D, Miller B, Hobbs M, Gentzsch P, Pierson C. 

Successful interviewing and selection strategies for 

patient-centered care delivery. Semin Nurse Manag. 

Mar 1995;3(1):27-35. Comment. 

757. Darby DN, Daniel K. Factors that influence nurses' 

customer orientation. J Nurs Manag. Sep 

1999;7(5):271-280. Not eligible target population. 

758. Darby M. Optimal staffing for hospitals: in search of 

solutions. Qual Lett Healthc Lead. Jun 1999;11(6):2-

10. Review. 

759. Darling H. Satisfying a hunger ... a personal journey 

of self discovery through further nursing education. 

Nurs Prax N Z. Mar 1995;10(1):12-21. Not eligible 

target population. 

760. Darmer MR, Ankersen L, Nielsen BG, Landberger G, 

Lippert E, Egerod I. The effect of a VIPS 

implementation programme on nurses' knowledge and 

attitudes towards documentation. Scand J Caring Sci. 

Sep 2004;18(3):325-332. Not eligible target 

population. 

761. Darvas JA, Hawkins LG. What makes a good 

intensive care unit: a nursing perspective. Aust Crit 

Care. May 2002;15(2):77-82. Not eligible target 

population. 

762. Das HS, Sawant P, Shirhatti RG, Vyas K, Vispute S, 

Dhadphale S, Patrawalla V, Desai N. Efficacy of low 

dose intradermal hepatitis B vaccine: results of a 

randomized trial among health care workers. Trop 

Gastroenterol. Jul-Sep 2002;23(3):120-121. Not 

eligible exposure. 

763. Daubener J. A look at travel nursing: two sides to the 

coin. J Emerg Nurs. Oct 2001;27(5):507-510. 

Comment. 

764. Daugherty J. "Premium shifts": a solution to an 

expensive option. Nurs Manage. Apr 1992;23(4):88. 

Comment.

765. Davidhizar R. Preparing a nursing department for 

downshifting. Todays OR Nurse. Jul-Aug 

1993;15(4):51-53. Comment.

766. Davidhizar R, Poole V, Giger JN. Power nap 

rejuvenates body, mind. Pa Nurse. Mar 1996;51(3):6-

7. Comment.

767. Davidson H, Folcarelli PH, Crawford S, Duprat LJ, 

Clifford JC. The effects of health care reforms on job 

satisfaction and voluntary turnover among hospitalbased nurses. Med Care. Jun 1997;35(6):634-645. Not 

eligible exposure. 

768. Davidson J. Golden slumbers. Br J Perioper Nurs. Feb 

2000;10(2):74-75. Comment.

769. Davidson SB, Scott R, Minarik P. Thinking critically 

about delegation. Am J Nurs. Jun 1999;99(6):61-62. 

Comment.

770. Davies H. Client-centred midwifery. No easy option. 

Pract Midwife. Jun 2001;4(6):26-28. Not eligible 

target population. 

771. D'Avirro J, Dotson T, LaPierre B, Marshall W, 

Mishler MB, Tanger JL. An interdisciplinary clinical 

advancement program within a patient-centered care 

model. Rehabil Nurs. May-Jun 1996;21(3):132-138. 

Not eligible exposure. 

772. Davis D. Partnering with nurses to handle personnel 

shortages. Am J Health Syst Pharm. Oct 1 

2002;59(19):1824-1826. Comment. 

773. Davis E. Autonomy at work: woman-centered birth 

and midwifery. Midwifery Today Childbirth Educ. 

Summer 1997(42):23-25. Comment. 

774. Davis JE. Nursing resources in accident and 

emergency departments. J Nurs Manag. Jan 

1995;3(1):11-18. Not eligible target population.

775. Davis LA. A phenomenological study of patient 

expectations concerning nursing care. Holist Nurs 

Pract. May-Jun 2005;19(3):126-133. Not eligible 

exposure. 

776. Davis NM. Always read medication labels. Am J 

Nurs. Nov 1993;93(11):14. Comment. 

777. Davis NM. Combating confirmation bias. Am J Nurs. 

Jul 1994;94(7):17. Comment.

778. Davis NM. Teaching patients to prevent errors. Am J 

Nurs. May 1994;94(5):17. Comment. 

779. Davis NM. Concentrating on interruptions. Am J 

Nurs. Mar 1994;94(3):14. Comment.

780. Davis R. The quick fix? Am J Nurs. Apr 

1991;91(4):56. Comment.
B-23 

781. Dawson C, Barrett V, Ross J. A case of a financial 

approach to manpower planning in the NHS. Health 

Manpow Manage. 1991;17(1):15-23. Not eligible 

target population. 

782. Dawson D. Development of a new eye care guideline 

for critically ill patients. Intensive Crit Care Nurs. 

Apr 2005;21(2):119-122. Not eligible target 

population 

783. Day GR. Is there a relationship between 12-hour 

shifts and job satisfaction in nurses? Alabama Nurse 

Jun-Aug 2004;31(2):11-2. Not peer reviewed. 

784. Day T, Wainwright SP, Wilson-Barnett J. An 

evaluation of a teaching intervention to improve the 

practice of endotracheal suctioning in intensive care 

units. J Clin Nurs. Sep 2001;10(5):682-696. Not 

eligible target population. 

785. Daynard D, Yassi A, Cooper JE, Tate R, Norman R, 

Wells R. Biomechanical analysis of peak and 

cumulative spinal loads during simulated patienthandling activities: a substudy of a randomized 

controlled trial to prevent lift and transfer injury of 

health care workers. Appl Ergon. Jun 2001;32(3):199-

214. Not eligible exposure. 

786. De Groot HA, Burke LJ, George VM. Implementing 

the differentiated pay structure model. Process and 

outcomes. J Nurs Adm. May 1998;28(5):28-38. Not 

eligible exposure. 

787. de Keizer NF, Bonsel GJ, Al MJ, Gemke RJ. The 

relation between TISS and real paediatric ICU costs: 

a case study with generalizable methodology. 

Intensive Care Med. Oct 1998;24(10):1062-1069. Not 

eligible target population. 

788. De La Cour J. Suicide in the ward setting. Nurs 

Times. Oct 5-11 2000;96(40):39-40. Not eligible 

target population. 

789. de Lima RA, Rocha SM, Scochi CG, Callery P. 

Involvement and fragmentation: a study of parental 

care of hospitalized children in Brazil. Pediatr Nurs. 

Nov-Dec 2001;27(6):559-564, 580. Not eligible 

target population. 

790. de Lusignan S, Wells S, Russell C. A model for 

patient-centred nurse consulting in primary care. Br J 

Nurs. Jan 23-Feb 12 2003;12(2):85-90. Not eligible 

target population. 

791. de Lusignan S, Wells SE, Russell C, Bevington WP, 

Arrowsmith P. Development of an assessment tool to 

measure the influence of clinical software on the 

delivery of high quality consultations. A study 

comparing two computerized medical record systems 

in a nurse run heart clinic in a general practice setting. 

Med Inform Internet Med. Dec 2002;27(4):267-280. 

Not eligible target population. 

792. de Rond M, de Wit R, van Dam F. The 

implementation of a Pain Monitoring Programme for 

nurses in daily clinical practice: results of a follow-up 

study in five hospitals. J Adv Nurs. Aug 

2001;35(4):590-598. Not eligible target population.

793. de Rond ME, de Wit R, van Dam FS, Muller MJ. A 

Pain Monitoring Program for nurses: effect on the 

administration of analgesics. Pain. Dec 15 

2000;89(1):25-38. Not eligible target population. 

794. de Ruyter A. Casual work in nursing and other 

clinical professions: evidence from Australia. J Nurs 

Manag. Jan 2004;12(1):62-68. Not eligible target 

population. 

795. de Vries K, Sque M, Bryan K, Abu-Saad H. Variant 

Creutzfeldt-Jakob disease: need for mental health and 

palliative care team collaboration. Int J Palliat Nurs. 

Dec 2003;9(12):512-520. Not eligible target 

population. 

796. Dean KA. Negligent patient abandonment. Fla Nurse. 

Sep 2003;51(3):15. Legal Cases. 

797. Dearholt SL, Feathers CA. Self-scheduling can work. 

Nurs Manage. Aug 1997;28(8):47-48. No association 

tested. 

798. Dechairo-Marino AE, Jordan-Marsh M, Traiger G, 

Saulo M. Nurse/physician collaboration: action 

research and the lessons learned. J Nurs Adm. May 

2001;31(5):223-232. Not eligible outcomes. 

799. Dechant GM. Self-scheduling for nursing staff. 

AARN News Lett. May 1990;46(5):4-8. No 

association tested. 

800. Decter MB. Canadian hospitals in transformation. 

Med Care. Oct 1997;35(10 Suppl):OS70-75. Not 

eligible target population 

801. Deitzer D, Wessell J, Myles K, et al. Agency nurses: 

the right solution to staffing problems? Journal of 

Long-Term Care Administration Fall 1992;20(3):29-

33. Nursing home. 

802. DeMoro D. Market value & real values: industry's 

choice in implementing ratios. Revolution. Jan-Feb 

2004;5(1):27-29. Comment. 

803. DeMoss C, McGrail M, Jr., Haus E, Crain AL, Asche 

SE. Health and performance factors in health care 

shift workers. J Occup Environ Med. Dec 

2004;46(12):1278-1281. Not eligible outcomes.

804. Dennis S. The Tredgold model of nursing. J Adv 

Nurs. Apr 1998;27(4):825-828. Not eligible target 

population. 

805. Denyes MJ, Neuman BM, Villarruel AM. Nursing 

actions to prevent and alleviate pain in hospitalized 

children. Issues Compr Pediatr Nurs. Jan-Mar 

1991;14(1):31-48. Not eligible outcomes. 

806. Devadas D. Short-changed? Nurs Times. Sep 13-19 

2001;97(37):27. Comment. 

807. Devanney JJ. Testing the limits: shift rotation and the 

ADA. Nurs Manage. Mar 1999;30(3):35-37. Legal 

Cases. 

808. Devine J. Opportunity afforded by junior doctors' 

hours being reduced. Nurs Stand. Jul 10-16 

1991;5(42):43. Not eligible target population. 

809. Devins GM, Paul LC, Barre PE, Mandin H, Taub K, 

Binik YM. Convergence of health ratings across 

nephrologists, nurses, and patients with end-stage 

renal disease. J Clin Epidemiol. Apr 2003;56(4):326-

331. Not eligible exposure. 

810. Dewsall J, King K. Children's nurse and service 

manager in acute paediatrics. Interview by Loretta 

Loach. Nurs Times. Nov 26-Dec 2 1997;93(48):40-

41. Interview.
B-24 

811. Dexter F, Epstein RH, Marcon E, de Matta R. 

Strategies to reduce delays in admission into a 

postanesthesia care unit from operating rooms. J 

Perianesth Nurs. Apr 2005;20(2):92-102. Review. 

812. Dexter F, Rittenmeyer H. Quantification of phase I 

postanesthesia nursing activities in the phase II 

postanesthesia care unit. Nurs Outlook. Mar-Apr 

1997;45(2):86-88. Not eligible exposure.

813. Diba VC, Chowdhury MM, Adisesh A, Statham BN. 

Occupational allergic contact dermatitis in hospital 

workers caused by methyldibromo glutaronitrile in a 

work soap. Contact Dermatitis. Feb 2003;48(2):118-

119. Not eligible target population. 

814. Dickens GL, Stubbs JH, Haw CM. Smoking and 

mental health nurses: a survey of clinical staff in a 

psychiatric hospital. J Psychiatr Ment Health Nurs. 

Aug 2004;11(4):445-451. Not eligible target 

population. 

815. Dickenson-Hazard N. Every nurse is a leader. 

Nursing. Nov 2000;30(11):8. Editorial.

816. Dickie H, Vedio A, Dundas R, Treacher DF, Leach 

RM. Relationship between TISS and ICU cost. 

Intensive Care Med. Oct 1998;24(10):1009-1017. Not 

eligible target population. 

817. Dickson J. Casualisation crisis. Nurs N Z. Jul 

1993;1(4):12-14. Not eligible target population

818. Dickson M, King MC. The effect of child care 

proximity on maternal reports of separation anxiety in 

employed nurses. Pediatric nursing Jan-Feb 

1992;18(1):64-6. Not relevant. 

819. Didovich K. Working year. Nurs Stand. Feb 26 

1997;11(23):28. Not eligible target population. 

820. Diehl-Oplinger L, Kaminski MF. Need critical care 

nurses? Inquire within. Nurs Manage. Mar 

2000;31(3):44, 46. Comment.

821. DiFrancesco M, Andrews T. Alamance Regional 

Medical Center improves patient safety with CPOE. J 

Healthc Inf Manag. Winter 2004;18(1):18-23. Not 

eligible exposure. 

822. DiIorio C, Manteuffel B. Preferences concerning 

epilepsy education: opinions of nurses, physicians, 

and persons with epilepsy. J Neurosci Nurs. Feb 

1995;27(1):29-34. Not eligible exposure.

823. Dijkers M, Paradise T. PCS: one system for both 

staffing and costing. Nurs Manage. Jan 

1986;17(1):25-34. Not eligible year.

824. DiMeglio K, Padula C, Piatek C, Korber S, Barrett A, 

Ducharme M, Lucas S, Piermont N, Joyal E, 

DeNicola V, Corry K. Group cohesion and nurse 

satisfaction: examination of a team-building 

approach. J Nurs Adm. Mar 2005;35(3):110-120. Not 

eligible outcomes. 

825. Dimond B. Dilemma. Linda was a nurse working on 

night duty and concerned about staffing levels. Accid 

Emerg Nurs. Jul 1998;6(3):172-174. Not eligible 

target population. 

826. Dimond B. Confidentiality. 9: The law relating to 

whistle blowing. Br J Nurs. Oct 28-Nov 10 

1999;8(19):1322-1323. Not eligible target population. 

827. Dingley J. A computer-aided comparative study of 

progressive alertness changes in nurses working two 

different night-shift rotas. J Adv Nurs. Jun 

1996;23(6):1247-1253. Not eligible target population. 

828. Dingman SK, Williams M, Fosbinder D, Warnick M. 

Implementing a caring model to improve patient 

satisfaction. J Nurs Adm. Dec 1999;29(12):30-37. Not 

eligible exposure.

829. Dinsdale P. Post haste. Nurs Times. Mar 11-17 

1998;94(10):14. Not eligible target population. 

830. Dinsdale P. The more, the better. Nurs Stand. Jul 7-13 

2004;18(43):12-13. Not eligible target population. 

831. Discher CL, Klein D, Pierce L, Levine AB, Levine 

TB. Heart failure disease management: impact on 

hospital care, length of stay, and reimbursement. 

Congest Heart Fail. Mar-Apr 2003;9(2):77-83. Not 

eligible exposure. 

832. Disomma C, Wilkerson S. Staff roles. All of the 

people most of the time. Health Serv J. Jul 13 

1995;105(5461):28-29. Not eligible target population.

833. Dixon L. Pre-admission clinic in an ENT unit. Nurs 

Stand. Mar 23-29 1994;8(26):23-26. Comment.

834. Dodd-McCue D, Tartaglia A, Myer K, Kuthy S, 

Faulkner K. Unintended consequences: the impact of 

protocol change on critical care nurses' perceptions of 

stress. Prog Transplant. Mar 2004;14(1):61-67. Not 

eligible exposure. 

835. Dodd-McCue D, Tartaglia A, Veazey KW, Streetman 

PS. The impact of protocol on nurses' role stress: a 

longitudinal perspective. J Nurs Adm. Apr 

2005;35(4):205-216. Not eligible exposure. 

836. Dodge JA. Patient-centred cystic fibrosis services. J R 

Soc Med. 2005;98 Suppl 45:2-6. Not eligible target 

population. 

837. Dogan O, Ertekin S, Dogan S. Sleep quality in 

hospitalized patients. J Clin Nurs. Jan 

2005;14(1):107-113. Not eligible target population.

838. Doman M, Prowse M, Webb C. Exploring nurses' 

experiences of providing high dependency care in 

children's wards. J Child Health Care. Sep 

2004;8(3):180-197. Not eligible target population.

839. Donadio G. Improving healthcare delivery with the 

transformational whole person care model. Holist 

Nurs Pract. Mar-Apr 2005;19(2):74-77. Not eligible 

exposure. 

840. Donlevy JA, Pietruch BL. The connection delivery 

model: care across the continuum. Nurs Manage. May 

1996;27(5):34, 36. No association tested. 

841. Donoghue J, Decker V, Mitten-Lewis S, Blay N. 

Critical care dependency tool: monitoring the 

changes. Aust Crit Care. May 2001;14(2):56-63. Not 

eligible target population. 

842. Donovan JL, Peters TJ, Noble S, Powell P, Gillatt D, 

Oliver SE, Lane JA, Neal DE, Hamdy FC. Who can 

best recruit to randomized trials? Randomized trial 

comparing surgeons and nurses recruiting patients to 

a trial of treatments for localized prostate cancer (the 

ProtecT study). J Clin Epidemiol. Jul 2003;56(7):605-

609. Not eligible target population. 
B-25 

843. Doreen F, Robinson C. "Magnet" status as markers of 

healthy work environments. Interview by Joanne 

Disch. Creat Nurs. 2002;8(2):4-6. Interview.

844. Dorsey G, Borneo HT, Sun SJ, Wells J, Steele L, 

Howland K, Perdreau-Remington F, Bangsberg DR. 

A heterogeneous outbreak of Enterobacter cloacae 

and Serratia marcescens infections in a surgical 

intensive care unit. Infect Control Hosp Epidemiol. 

Jul 2000;21(7):465-469. Not eligible exposure. 

845. Doucette JN. Serving up uncommon service. Nurs 

Manage. Nov 2003;34(11):26-30. Review. 

846. Dougan M, Lanigan C, Szalapski J. Meeting 

supplemental staffing needs: an in-house approach. 

Nurs Econ. Mar-Apr 1991;9(2):128-130, 132. Not 

eligible outcomes. 

847. Douglas DA, Mayewski J. Census variation staffing. 

Nurs Manage. Feb 1996;27(2):32-33, 36. Not eligible 

outcomes. 

848. Dowding D. Examining the effects that manipulating 

information given in the change of shift report has on 

nurses' care planning ability. J Adv Nurs. Mar 

2001;33(6):836-846. Not eligible target population. 

849. Doyle KA, Maslin-Prothero S. Promoting children's 

rights: the role of the children's nurse. Paediatr Nurs. 

Oct 1999;11(8):23-25. Not eligible target population. 

850. Dracup K, Bryan-Brown CW. One solution to poor 

staffing ratios. Am J Crit Care. Mar 2001;10(2):71-

73. Editorial.

851. Drennan V. The more things change. Nurs Times. Sep 

27-Oct 3 2001;97(39):25. Not eligible target 

population. 

852. Drew JA. If you don't know where you're going, 

anywhere you end up is OK. GHA Today. Jul 

2001;45(7):2. Comment.

853. Driedger L. The other side of the bed. Can Nurse. Feb 

2000;96(2):49-50. Case Reports. 

854. Duchene P. Deliver empowered care. Nurs Manage. 

Nov 2002;33(11):11. Comment. 

855. Duchene P. Staff ratios: just about numbers? Nurs 

Manage. Jul 2002;33(7):10. Comment.

856. Duckett R. Night nursing. Thirst for knowledge. Nurs 

Times. Sep 1-7 1993;89(35):29-31. Comment. 

857. Duffin C. US survey finds link between patient 

recovery and nurse numbers. Nurs Manag (Harrow). 

Jun 2000;7(3):4. News. 

858. Duffin C. Waiting in vain. Nurs Stand. Jan 10-16 

2001;15(17):12. Comment. 

859. Duffy D. Out of the shadows: a study of the special 

observation of suicidal psychiatric in-patients. J Adv 

Nurs. May 1995;21(5):944-950. Not eligible target 

population. 

860. Dugger B. Introducing products to prevent 

needlesticks. Nurs Manage. Oct 1992;23(10):62-66. 

Not eligible exposure.

861. Dumais MM. Use error: a nurse's perspective. 

Biomed Instrum Technol. Jul-Aug 2004;38(4):313-

315. Comment.

862. Dummett S. Avoiding drug administration errors: the 

way forward. Nurs Times. Jul 29-Aug 4 

1998;94(30):58-60. Not eligible target population. 

863. Dumont M, Montplaisir J, InfanteRivard C. Sleep 

quality of former night-shift workers... XIIth 

International Symposium on Night and Shiftwork. 

Foxwoods symposium series, June 1995. International 

Journal of Occupational and Environmental Health 

Jul-Sep 1997;3(3): Suppl):S10-4. Conference 

abstract.

864. Dumont R, van der Loo R, van Merode F, Tange H. 

User needs and demands of a computer-based patient 

record. Medinfo. 1998;9 Pt 1:64-69. Not eligible 

target population. 

865. Duncan K, Pozehl B. Effects of performance 

feedback on patient pain outcomes. Clin Nurs Res. 

Nov 2000;9(4):379-397; discussion 398-401. Not 

eligible outcomes. 

866. Duncan SM, Hyndman K, Estabrooks CA, et al. 

Nurses' experience of violence in Alberta and British 

Columbia hospitals. Canadian Journal of Nursing 

Research Mar 2001;32(4):57-78. Not relevant 

867. Dunn L. Job sharing--the way forward? Nurs Stand. 

Sep 5-11 1990;4(50):32-36. Not eligible target 

population. 

868. Dunton N, Gajewski B, Taunton RL, et al. Nurse 

staffing and patient falls on acute care hospital units. 

Nursing outlook Jan-Feb 2004;52(1):53-9. Not 

relevant. 

869. Durham S. The phone call that changed my life. 

Interview by Mary Hampshire. Nurs Stand. May 17-

23 2000;14(35):18-19. Interview. 

870. Duxbury J. Avoiding disturbed sleep in hospitals. 

Nurs Stand. Nov 30-Dec 6 1994;9(10):31-34. Not 

eligible outcomes. 

871. Duxbury J. Night nurses: why are they undervalued? 

Nurs Stand. Dec 7-13 1994;9(11):33-36. No 

association tested. 

872. Duxbury M, Brown C, Lambert A. Surgical gloves. 

How do you change yours? Br J Perioper Nurs. Jan 

2003;13(1):17-20. Not eligible exposure. 

873. Dykes F. A critical ethnographic study of encounters 

between midwives and breast-feeding women in 

postnatal wards in England. Midwifery. Sep 

2005;21(3):241-252. Not eligible target population. 

874. Dzendrowskyj P, Shaw G, Johnston L. Effects of 

nursing industrial action on relatives of Intensive Care 

Unit patients: a 16-month follow-up. N Z Med J. Nov 

5 2004;117(1205):U1150. Not eligible target 

population. 

875. Eagle DJ, Salama S, Whitman D, Evans LA, Ho E, 

Olde J. Comparison of three instruments in predicting 

accidental falls in selected inpatients in a general 

teaching hospital. J Gerontol Nurs. Jul 1999;25(7):40-

45. Not eligible exposure. 

876. Eastaugh SR. Hospital nursing technical efficiency: 

nurse extenders and enhanced productivity. Hosp 

Health Serv Adm. Winter 1990;35(4):561-573. Not 

eligible outcomes. 

877. Eastaugh SR. Hospital nurse productivity. J Health 

Care Finance. Fall 2002;29(1):14-22. Not eligible 

outcomes. 

878. Eastman M. Staff mix and public safety. Nurs BC. 

Oct 2004;36(4):5. Letter.
B-26 

880. Edel EM. A perioperative patient acuity system: 

planning and design. Nurs Manage. May 

1995;26(5):48N, 48P. Comment. 

881. Edvardsson JD, Sandman PO, Rasmussen BH. 

Meanings of giving touch in the care of older patients: 

becoming a valuable person and professional. J Clin 

Nurs. Jul 2003;12(4):601-609. Not eligible target 

population. 

882. Edwards DF. The Synergy Model: linking patient 

needs to nurse competencies. Crit Care Nurse. Feb 

1999;19(1):88-90, 97-89. Case Reports. 

883. Edwards N. The implications of day surgery for inpatient hospital wards. Nurs Times. Sep 11-17 

1996;92(37):32-34. Not eligible exposure.

884. Edwards SD. Are nursing's 'extraordinary' moral 

standards realistic? Nurs Times. Oct 23-29 

1996;92(43):34-35. Comment. 

885. Efraimsson E, Sandman PO, Hyden LC, Rasmussen 

BH. Discharge planning: "fooling ourselves?"--

patient participation in conferences. J Clin Nurs. Jul 

2004;13(5):562-570. Not eligible target population. 

886. Eischens MJ, Elliott BA, Elliott TE. Two hospice 

quality of life surveys: a comparison. Am J Hosp 

Palliat Care. May-Jun 1998;15(3):143-148. Not 

eligible target population. 

887. Elder R, Neal C, Davis BA, Almes E, Whitledge L, 

Littlepage N. Patient satisfaction with triage nursing 

in a rural hospital emergency department. J Nurs Care 

Qual. Jul-Sep 2004;19(3):263-268. Not eligible 

exposure. 

888. Ellefsen B, Kim HS. Nurses' construction of clinical 

situations: a study conducted in an acute-care setting 

in Norway. Can J Nurs Res. Jun 2004;36(2):114-131. 

Not eligible target population.

889. Ellett ML, Lou Q, Chong SK. Prevalence of 

immunoglobulin G to Helicobacter pylori among 

endoscopy nurses/technicians. Gastroenterol Nurs. 

Jan-Feb 1999;22(1):3-6. Not eligible outcomes. 

890. Ellila H, Sourander A, Valimaki M, Piha J. 

Characteristics and staff resources of child and 

adolescent psychiatric hospital wards in Finland. J 

Psychiatr Ment Health Nurs. Apr 2005;12(2):209-

214. Not eligible target population.

891. Ellis J. Overtime and fatigue. To stay or not to stay. 

Nurs BC. Jun 2001;33(3):32-33. Comment.

892. Ellis J, Etheridge G, Buckley J. Improving the ward 

environment through observation of care. Nurs 

Times. Nov 16-22 2004;100(46):36-38. Not eligible 

target population. 

893. Ellis JM. Barriers to effective screening for domestic 

violence by registered nurses in the emergency 

department. Crit Care Nurs Q. May 1999;22(1):27-41. 

Not eligible exposure.

894. Ellis S. The patient-centred care model: 

holistic/multiprofessional/reflective. Br J Nurs. Mar 

11-24 1999;8(5):296-301. Not eligible target 

population. 

895. Ellis S. More on mandatory overtime and wearing 

blue ribbons. J Emerg Nurs. Feb 2001;27(1):9-10. 

Letter.

896. Endacott R, Chellel A. Nursing dependency scoring: 

measuring the total workload. Nurs Stand. Jun 5 

1996;10(37):39-42. Not eligible target population. 

897. Endacott R, Dawson D. Clinical decisions made by 

nurses in intensive care--results of a telephone survey. 

Nurs Crit Care. Jul-Aug 1997;2(4):191-196. Not 

eligible target population. 

898. Engler AJ, Cusson RM, Brockett RT, CannonHeinrich C, Goldberg MA, West MG, Petow W. 

Neonatal staff and advanced practice nurses' 

perceptions of bereavement/end-of-life care of 

families of critically ill and/or dying infants. Am J 

Crit Care. Nov 2004;13(6):489-498. Not eligible 

exposure. 

899. Enmon P, Demetropoulos S. Bringing talk to the 

table. Nurs Manage. Mar 2004;35(3):50-52. Not 

eligible exposure. 

900. Erickson JI, Hamilton GA, Jones DE, Ditomassi M. 

The value of collaborative governance/staff 

empowerment. J Nurs Adm. Feb 2003;33(2):96-104. 

Not eligible exposure.

901. Erickson ST. Mother's Hours: "extra" RNs balance 

the workload. Nurs Manage. Sep 1991;22(9):45-46, 

48. No association tested. 

902. Erlen JA, Sereika SM. Critical care nurses, ethical 

decision-making and stress. J Adv Nurs. Nov 

1997;26(5):953-961. Not eligible exposure. 

903. Ermer GR, McEleney BJ, West IJ. An oral history of 

the "joint" nursing experience at Landstuhl Regional 

Medical Center. Mil Med. Feb 2000;165(2):131-134. 

Not eligible target population. 

904. Eschiti VS. Planting seeds at Esalen: collaborative 

relationships in holistic healthcare. Beginnings. 

Summer 2005;25(3):3, 17. Comment.

905. Escriba-Aguir V. Nurses' attitudes towards shiftwork 

and quality of life. Scand J Soc Med. Jun 

1992;20(2):115-118. Not eligible target population. 

906. Esposito L. Blizzard forces nursing home evacuation. 

Nurs Spectr (Wash D C). Jan 16 1996;6(2):6. Not 

eligible target population. 

907. Estabrooks CA, Tourangeau AE, Humphrey CK, 

Hesketh KL, Giovannetti P, Thomson D, Wong J, 

Acorn S, Clarke H, Shamian J. Measuring the hospital 

practice environment: a Canadian context. Res Nurs 

Health. Aug 2002;25(4):256-268. Not eligible 

outcomes. 

908. Estryn-Behar M, Vinck L, Caillard JF. Work 

schedules in health care in France: very few changes 

between 1991 and 1998, according to national data. J 

Hum Ergol (Tokyo). Dec 2001;30(1-2):327-332. Not 

eligible target population. 

909. Eubanks P. New act may limit recruitment of foreign 

nurses. Hospitals. Feb 5 1990;64(3):67. Comment. 

910. Evans J, Doswell N. Cross currents. Interview by 

Dina Leifer. Nurs Stand. Aug 15-21 2001;15(48):16. 

Interview. 

911. Evans M. Putting a price on care. Low nurse-topatient ratios save lives but are costly: study. Mod 

Healthc. Aug 8 2005;35(32):14. News.

912. Evans M. Will work for visa. Bill would boost visas 

for skilled workers. Mod Healthc. Jan 10 

2005;35(2):16. News.
B-27 

913. Evans ML, Martin ML, Winslow EH. Nursing care 

and patient satisfaction. Am J Nurs. Dec 

1998;98(12):57-59. No association tested.

914. Evans SK, Laundon T, Yamamoto WG. Projecting 

staffing requirements for intensive care units. J Nurs 

Adm. Jul 1980;10(7):34-42. Not eligible year.

915. Eve M. Low staffing levels leave little time for care. 

Crit Care Nurse. Aug 2001;21(4):20. Comment. 

916. Ewens A, Richards J. Concepts of health: 

implications for public health work. Br J Community 

Nurs. Aug 2000;5(8):404-408. Not eligible target 

population. 

917. Facchinetti NJ, Campbell GM, Jones DP. Evaluating 

dispensing error detection rates in a hospital 

pharmacy. Med Care. Jan 1999;37(1):39-43. Not 

eligible exposure. 

918. Fagerstrom L, Engberg IB, Eriksson K. A comparison 

between patients' experiences of how their caring 

needs have been met and the nurses' patient 

classification--an explorative study. J Nurs Manag. 

Nov 1998;6(6):369-377. Not eligible target 

population. 

919. Fahs MC, Fulop G, Strain J, Sacks HS, Muller C, 

Cleary PD, Schmeidler J, Turner B. The inpatient 

AIDS unit: a preliminary empirical investigation of 

access, economic, and outcome issues. Am J Public 

Health. Apr 1992;82(4):576-578. Not eligible 

exposure. 

920. Fairburn K. Nurses' attitudes to visiting in coronary 

care units. Intensive Crit Care Nurs. Sep 

1994;10(3):224-233. Not eligible outcomes. 

921. Falk-Rafael AR. Empowerment as a process of 

evolving consciousness: a model of empowered 

caring. ANS Adv Nurs Sci. Sep 2001;24(1):1-16. Not 

eligible exposure. 

922. Fanello S, Jousset N, Roquelaure Y, Chotard-Frampas 

V, Delbos V. Evaluation of a training program for the 

prevention of lower back pain among hospital 

employees. Nurs Health Sci. Mar-Jun 2002;4(1-2):51-

54. Not eligible outcomes. 

923. Fargen J, Richards T, Kirchhoff K, et al. Mandatory 

overtime: a survey of registered nurses. Stat Bulletin 

Nov 2001;70(11):4-5. Not peer reviewed. 

924. Farnham JA, Maez-Rauzi V, Conway K. Balancing 

assignments: a PCS for a step-down unit. Nurs 

Manage. Mar 1992;23(3):49-50, 52. Not eligible 

exposure. 

925. Farr BM. Understaffing: a risk factor for infection in 

the era of downsizing? Infect Control Hosp 

Epidemiol. Mar 1996;17(3):147-149. Comment. 

926. Farrell C, Heaven C, Beaver K, Maguire P. 

Identifying the concerns of women undergoing 

chemotherapy. Patient Educ Couns. Jan 

2005;56(1):72-77. Not eligible target population. 

927. Farrell GA. How accurately do nurses perceive 

patients' needs? A comparison of general and 

psychiatric settings. J Adv Nurs. Sep 

1991;16(9):1062-1070. Not eligible target population. 

928. Farrington M, Trundle C, Redpath C, Anderson L. 

Effects on nursing workload of different methicillinresistant Staphylococcus aureus (MRSA) control 

strategies. J Hosp Infect. Oct 2000;46(2):118-122. 

Not eligible target population. 

929. Farwell B. Health care in America: an intimate 

glimpse. Ann Intern Med. Dec 15 

1996;125(12):1005-1006. Comment.

930. Feddersen E, Lockwood DH. An inpatient diabetes 

educator's impact on length of hospital stay. Diabetes 

Educ. Mar-Apr 1994;20(2):125-128. Not eligible 

exposure. 

931. Feldberg C. Labor law: no minimum wage for nurses' 

off-premises, on-call hours. J Law Med Ethics. FallWinter 2001;29(3-4):413-414. Legal Cases.

932. Feldstein MA, Gemma PB. Oncology nurses and 

chronic compounded grief. Cancer Nurs. Jun 

1995;18(3):228-236. Not eligible outcomes.

933. Feng JY, Wu YW. Nurses' intention to report child 

abuse in Taiwan: a test of the theory of planned 

behavior. Res Nurs Health. Aug 2005;28(4):337-347. 

Not eligible target population. 

934. Ferguson TB, Jr. Continuous quality improvement in 

medicine: validation of a potential role for medical 

specialty societies. Am Heart Hosp J. Fall 

2003;1(4):264-272. Not eligible exposure.

935. Fermin P, Mjolsness E, McLeay J, Chisholm L. An 

innovative approach to maintaining critical skills. 

Nurs Manage. Jan 1991;22(1):64A-64C. No 

association tested. 

936. Ferns T. The nature and causes of violent incidents in 

intensive-care settings. Prof Nurse. Dec 

2002;18(4):207-210. Not eligible target population.

937. Fernsebner B, Beyea S. Survey provides a snapshot of 

staffing challenges in the OR. OR Manager. Jun 

2001;17(6):1, 10-13. Not eligible outcomes. 

938. Ferrante A. The nursing shortage crisis in Quebec's 

McGill University affiliated teaching hospitals: 

strategies that can work. Can J Nurs Adm. Sep-Oct 

1993;6(3):26-31. No association tested.

939. Fetzer SJ. Seeing with new eyes. J Perianesth Nurs. 

Dec 2003;18(6):377-379. Editorial.

940. Feutz SA. How to cope with under staffing. Nursing. 

Aug 1991;21(8):54-55. Comment. 

941. Field PA, Renfrew M. Teaching and support: nursing 

input in the postpartum period. Int J Nurs Stud. 

1991;28(2):131-144. Not eligible outcomes. 

942. Fiesseler F, Szucs P, Kec R, Richman PB. Can nurses 

appropriately interpret the Ottawa Ankle Rule? Am J 

Emerg Med. May 2004;22(3):145-148. Not eligible 

exposure. 

943. Fiesta J. The nursing shortage: whose liability 

problem? Part II. Nurs Manage. Feb 1990;21(2):22-

23. Comment.

944. Fiesta J. Staffing implications: a legal update. Nurs 

Manage. Jun 1994;25(6):34-35. Comment. 

945. Filipovich CC. Teach nurses effective ways to deal 

with inadequate staffing. Nurs Manage. Dec 

1999;30(12):38. Comment.

946. Findlay J. Shifting time. Nurs Times. Jan 12-18 

1994;90(2):42-44. Comment.
B-28 

947. Findlay J, Stewart L, Kettles A. Flexible working. 

Good timing. Health Serv J. Jul 13 

1995;105(5461):30. Not eligible target population.

948. Fine JM, Fine MJ, Galusha D, Petrillo M, Meehan 

TP. Patient and hospital characteristics associated 

with recommended processes of care for elderly 

patients hospitalized with pneumonia: results from the 

medicare quality indicator system pneumonia module. 

Arch Intern Med. Apr 8 2002;162(7):827-833. Not 

eligible outcomes. 

949. Fine MJ, Orloff JJ, Rihs JD, Vickers RM, Kominos S, 

Kapoor WN, Arena VC, Yu VL. Evaluation of 

housestaff physicians' preparation and interpretation 

of sputum Gram stains for community-acquired 

pneumonia. J Gen Intern Med. May-Jun 

1991;6(3):189-198. Not eligible exposure. 

950. Fink JL. Emma & the med error. J Christ Nurs. 

Spring 2000;17(2):26-27, 29. Comment. 

951. Fink R, Thompson CJ, Bonnes D. Overcoming 

barriers and promoting the use of research in practice. 

J Nurs Adm. Mar 2005;35(3):121-129. Not eligible 

exposure. 

952. Finn T, King J, Thorburn J. The educational needs of 

part time clinical facilitators. Contemporary Nurse 

Jun 2000;9(2):132-9. Not relevant. 

953. Finnema EJ, Louwerens JW, Slooff CJ, van den 

Bosch RJ. Expressed emotion on long-stay wards. J 

Adv Nurs. Sep 1996;24(3):473-478. Not eligible 

target population. 

954. Firn S. No sex, please. Nurs Times. Apr 6-12 

1994;90(14):57. Comment.

955. Fischer JE, Calame A, Dettling AC, Zeier H, Fanconi 

S. Objectifying psychomental stress in the workplace-

-an example. Int Arch Occup Environ Health. Jun 

2000;73 Suppl:S46-52. Not eligible target population. 

956. Fisher ML, Hinson N, Deets C. Selected predictors of 

registered nurses' intent to stay. J Adv Nurs. Nov 

1994;20(5):950-957. Not eligible exposure. 

957. Fisk J, Arcona S. Tympanic membrane vs. pulmonary 

artery thermometry. Nurs Manage. Jun 

2001;32(6):42, 45-48. Not eligible exposure.

958. Fitch JA, Munro CL, Glass CA, Pellegrini JM. Oral 

care in the adult intensive care unit. Am J Crit Care. 

Sep 1999;8(5):314-318. Not eligible exposure.

959. FitzGerald EL. The possible dream. Revolution. JanFeb 2000;1(1):22-27. Comment.

960. Fitzpatrick F, Murphy OM, Brady A, Prout S, 

Fenelon LE. A purpose built MRSA cohort unit. J 

Hosp Infect. Dec 2000;46(4):271-279. Not eligible 

target population. 

961. Fitzpatrick JJ, Salinas TK, O'Connor LJ, Stier L, 

Callahan B, Smith T, White MT. Nursing care quality 

initiative for care of hospitalized elders and their 

families. J Nurs Care Qual. Apr-Jun 2004;19(2):156-

161. Not eligible exposure.

971. Fitzpatrick JJ, Stier L, Eichorn A, Dlugacz YD, 

O'Connor LJ, Salinas TK, Smith T, White MT. 

Hospitalized elders: changes in functional and mental 

status. Outcomes Manag. Jan-Mar 2004;8(1):52-56. 

Not eligible outcomes.

981. Fitzpatrick JM, While AE, Roberts JD. Shift work 

and its impact upon nurse performance: current 

knowledge and research issues. J Adv Nurs. Jan 

1999;29(1):18-27. Not eligible target population. 

982. Fitzpatrick MA. The numbers game, again? Nurs 

Manage. Apr 2002;33(4):6. Editorial.

983. Flaherty MJ. Insubordination--patient load. NLN 

Publ. Jun 1990(20-2294):318-326. Not eligible 

exposure. 

984. Flannelly LT, Flannelly KJ, Cox. Evaluating 

improvements in nursing staff at a state psychiatric 

hospital. Issues in Mental Health Nursing Sep 

2001;22(6):621-32. Not relevant. 

985. Fletcher CE. Failure mode and effects analysis. An 

interdisciplinary way to analyze and reduce 

medication errors. J Nurs Adm. Dec 1997;27(12):19-

26. Not eligible exposure. 

986. Fletcher CE. Hospital RNs' job satisfactions and 

dissatisfactions. J Nurs Adm. Jun 2001;31(6):324-

331. No association tested. 

987. Fletcher E, Stevenson C. Launching the Tidal Model 

in an adult mental health programme. Nurs Stand. 

Aug 22-28 2001;15(49):33-36. Not eligible target 

population. 

988. Fletcher M. Inquest produces change. Can Nurse. 

Nov 2001;97(10):20. Comment. 

989. Flood D. An Afghan hospital in wartime. Nurses, 

physicians, and wounded fighters--a photo essay. Am 

J Nurs. Feb 2002;102(2):42-45. Not eligible target 

population. 

990. Flook DJ, Crumplin MK. The efficiency of 

management of emergency surgery in a district 

general hospital--a prospective study. Ann R Coll 

Surg Engl. Jan 1990;72(1):27-31. Not eligible target 

population. 

991. Flucker CJ, Hart E, Weisz M, Griffiths R, Ruth M. 

The 50-millilitre syringe as an inexpensive training 

aid in the application of cricoid pressure. Eur J 

Anaesthesiol. Jul 2000;17(7):443-447. Not eligible 

target population. 

992. Flynn EA, Barker KN, Pepper GA, Bates DW, 

Mikeal RL. Comparison of methods for detecting 

medication errors in 36 hospitals and skilled-nursing 

facilities. Am J Health Syst Pharm. Mar 1 

2002;59(5):436-446. Not eligible exposure. 

993. Flynn ER, Wolf ZR, McGoldrick TB, Jablonski RA, 

Dean LM, McKee EP. Effect of three teaching 

methods on a nursing staff's knowledge of medication 

error risk reduction strategies. J Nurs Staff Dev. JanFeb 1996;12(1):19-26. Not eligible exposure. 

994. Flynn K. Nursing in Saudi Arabia. Interview by 

Margaret Atkin. Qld Nurse. Jul-Aug 1990;9(4):10. 

Interview. 

995. Flynn L. Agency characteristics most valued by home 

care nurses: findings of a nationwide study. Home 

Healthc Nurse. Dec 2003;21(12):812-817. Not 

eligible target population. 

996. Flynn L, Aiken LH. Does international nurse 

recruitment influence practice values in U.S. 

hospitals? J Nurs Scholarsh. 2002;34(1):67-73. Not 

eligible exposure. 
B-29 

997. Flynn L, Deatrick JA. Home care nurses' descriptions 

of important agency attributes. J Nurs Scholarsh. 

2003;35(4):385-390. Not eligible target population. 

998. Flynn S. Multiple sclerosis: the Treetops model of 

residential care. Br J Nurs. May 9-22 2002;11(9):635-

642. Not eligible target population. 

999. Fochsen G, Sjogren K, Josephson M, Lagerstrom M. 

Factors contributing to the decision to leave nursing 

care: a study among Swedish nursing personnel. J 

Nurs Manag. Jul 2005;13(4):338-344. Not eligible 

target population. 

1000. Fogle M. One solution to poor staffing ratios. Am J 

Crit Care. Jul 2001;10(4):294. Comment. 

1001. Foley BJ, Kee CC, Minick P, Harvey SS, Jennings 

BM. Characteristics of nurses and hospital work 

environments that foster satisfaction and clinical 

expertise. J Nurs Adm. May 2002;32(5):273-282. Not 

eligible target population. 

1002. Foley DR. Baltimore hospital bucks RN staff 

reduction trend. Revolution. Spring 1997;7(1):51-53. 

Comment.

1003. Foley M. Staffing: the ANA's primary concern. Am J 

Nurs. Jan 2001;101(1):88. Comment.

1004. Fondiller SH. Midwest jobfocus. Transplant care: 

giving patients a new lease on life. Am J Nurs. Mar 

1991;91(3):73, 75-76, 78 passim. News.

1005. Fontaine K, Rositani R. Cost, quality, and satisfaction 

with hospice after-hours care. Hosp J. 2000;15(1):1-

13. Not eligible target population.

1006. Forbes MA. The practice of professional nurse case 

management. Nurs Case Manag. Jan-Feb 

1999;4(1):28-33. Not eligible outcomes. 

1007. Forchuk C, Gibson D, Best H. Strike contingency 

planning. Can Nurse. Jan 1999;95(1):33-37. 

Comment.

1008. Forchuk C, Westwell J, Martin ML, Azzapardi WB, 

Kosterewa-Tolman D, Hux M. Factors influencing 

movement of chronic psychiatric patients from the 

orientation to the working phase of the nurse-client 

relationship on an inpatient unit. Perspect Psychiatr 

Care. Jan-Mar 1998;34(1):36-44. Not eligible 

exposure. 

1009. Ford K, Turner D. Stories seldom told: paediatric 

nurses' experiences of caring for hospitalized children 

with special needs and their families. J Adv Nurs. Feb 

2001;33(3):288-295. Not eligible target population.

1010. Forrester DA. AIDS-related risk factors, medical 

diagnosis, do-not-resuscitate orders and 

aggressiveness of nursing care. Nurs Res. Nov-Dec 

1990;39(6):350-354. Not eligible exposure.

1011. Forrester DA, McCabe-Bender J, Tiedeken K. Fall 

risk assessment of hospitalized adults and follow-up 

study. J Nurses Staff Dev. Nov-Dec 1999;15(6):251-

258; discussion 258-259. Not eligible exposure. 

1012. Forrester DA, McCabe-Bender J, Walsh N, BellBowe J. Physical restraint management of 

hospitalized adults and follow-up study. J Nurses 

Staff Dev. Nov-Dec 2000;16(6):267-276. Not eligible 

exposure. 

1013. Forrester DA, Murphy PA. Nurses' attitudes toward 

patients with AIDS and AIDS-related risk factors. J 

Adv Nurs. Oct 1992;17(10):1260-1266. Not eligible 

exposure. 

1014. Fox M. Primary nursing in long-term geriatric units. 

Can Nurse. Nov 1992;88(10):29, 32. Comment. 

1015. Fox ML, Dwyer DJ. An investigation of the effects of 

time and involvement in the relationship between 

stressors and work-family conflict. J Occup Health 

Psychol. Apr 1999;4(2):164-174. Not eligible 

exposure. 

1016. Foxall MJ, Zimmerman L, Standley R, Bene B. A 

comparison of frequency and sources of nursing job 

stress perceived by intensive care, hospice and 

medical-surgical nurses. J Adv Nurs. May 

1990;15(5):577-584. Not eligible exposure. 

1017. Fraenkel DJ, Cowie M, Daley P. Quality benefits of 

an intensive care clinical information system. Crit 

Care Med. Jan 2003;31(1):120-125. Not eligible 

target population. 

1018. France DJ, Miles P, Cartwright J, Patel N, Ford C, 

Edens C, Whitlock JA. A chemotherapy incident 

reporting and improvement system. Jt Comm J Qual 

Saf. Apr 2003;29(4):171-180. Not eligible exposure.

1019. Francke AL, Garssen B, Luiken JB, De Schepper 

AM, Grypdonck M, Abu-Saad HH. Effects of a 

nursing pain programme on patient outcomes. 

Psychooncology. Dec 1997;6(4):302-310. Not eligible 

exposure. 

1020. Francke AL, Luiken JB, Garssen B, Abu-Saad HH, 

Grypdonck M. Effects of a pain programme on 

nurses' psychosocial, physical and relaxation 

interventions. Patient Educ Couns. Jul 

1996;28(2):221-230. Not eligible exposure.

1021. Frank IC. ED crowding and diversion: strategies and 

concerns from across the United States. J Emerg 

Nurs. Dec 2001;27(6):559-565. Review. 

1022. Freeman BA, Coronado JR. The nursing shortage: 

dynamics and solutions. A supportive clinical practice 

model. Nurs Clin North Am. Sep 1990;25(3):551-

560. No association tested.

1023. French E. Pediatric and neonatal nurses get "one more 

hand". Crit Care Nurse. Oct 1999;19(5):96. Comment. 

1024. Frick S, Uehlinger DE, Zuercher Zenklusen RM. 

Medical futility: predicting outcome of intensive care 

unit patients by nurses and doctors--a prospective 

comparative study. Crit Care Med. Feb 

2003;31(2):456-461. Not eligible target population.

1025. Frid I, Bergbom-Engberg I, Haljamae H. Brain death 

in ICUs and associated nursing care challenges 

concerning patients and families. Intensive Crit Care 

Nurs. Feb 1998;14(1):21-29. Not eligible target 

population. 

1026. Friend B. Trapped in Iraq. Nurs Times. Nov 14-20 

1990;86(46):16-17. News.

1027. Fryklund B, Tullus K, Berglund B, Burman LG. 

Importance of the environment and the faecal flora of 

infants, nursing staff and parents as sources of gramnegative bacteria colonizing newborns in three 

neonatal wards. Infection. Sep-Oct 1992;20(5):253-

257. Not eligible target population. 
B-30 

1028. Fuchs BC, Pass CM. Smoking practices of hospital 

employed nurses. South Carolina Nurse Summer 

1990;5(2):36-7. Not relevant. 

1029. Fudge L. Team-based self-rostering. Br J Perioper 

Nurs. Jul 2001;11(7):310-316. Not eligible target 

population. 

1030. Fujino M, Nojima Y. Effects of ward rotation on 

subsequent transition processes of Japanese clinical 

nurses. Nurs Health Sci. Mar 2005;7(1):37-44. Not 

eligible target population. 

1031. Fuortes LJ, Shi Y, Zhang M, Zwerling C, Schootman 

M. Epidemiology of back injury in university hospital 

nurses from review of workers' compensation records 

and a case-control survey. J Occup Med. Sep 

1994;36(9):1022-1026. Not eligible outcomes. 

1032. Furillo J. Behind (and between) the lines. Revolution. 

Sep-Oct 2000;1(5):25-27. Comment.

1033. Furillo J. Ensuring safe nurse-to-patient ratios: Safe 

Staffing Bill mandates ratios based on patients' needs 

rather than budgets. West J Med. Apr 

2001;174(4):233-234. News. 

1034. Furillo J, Kercher L. Should nurse-to-patient staffing 

ratios be mandated by legislation? MCN Am J Matern 

Child Nurs. Jul-Aug 2001;26(4):176-177. Comment. 

1035. Furlong S, Ward M. Assessing patient dependency 

and staff skill mix. Nurs Stand. Mar 12 

1997;11(25):33-38. Not eligible target population. 

1036. Gabrielson A. Patient-centered care in the OR: is this 

possible? Can Oper Room Nurs J. Mar-Apr 

1997;15(1):8-10. Comment.

1037. Gadbois C. Different job demands of nightshifts in 

hospitals. J Hum Ergol (Tokyo). Dec 2001;30(1-

2):295-300. Not eligible target population.

1038. Gagnon AJ, Waghorn K, Jones MA, Yang H. 

Indicators nurses employ in deciding to test for 

hyperbilirubinemia. J Obstet Gynecol Neonatal Nurs. 

Nov-Dec 2001;30(6):626-633. Not eligible Exposure. 

1039. Gagnon J, Bouchard F, Landry M, Belles-Isles M, 

Fortier M, Fillion L. Implementing a hospital-based 

animal therapy program for children with cancer: a 

descriptive study. Can Oncol Nurs J. Fall 

2004;14(4):210-222. Not eligible exposure. 

1040. Gajewska K, Schroeder M, De Marre F, Vincent JL. 

Analysis of terminal events in 109 successive deaths 

in a Belgian intensive care unit. Intensive Care Med. 

Jun 2004;30(6):1224-1227. Not eligible target 

population. 

1041. Gale J, FothergillBourbonnais F, Chamberlain M. 

Measuring nursing support during childbirth. MCN: 

The American Journal of Maternal/Child Nursing 

Sep-Oct 2001;26(5):264-71. Not relevant. 

1042. Gallagher RM, Kany KA, Rowell PA, Peterson C. 

ANA's nurse staffing principles. Am J Nurs. Apr 

1999;99(4):50, 52-53. Review.

1043. Gamble DA. Filipino nurse recruitment as a staffing 

strategy. J Nurs Adm. Apr 2002;32(4):175-177. Not 

eligible target population. 

1044. Ganapathy S, Zwemer FL, Jr. Coping with a crowded 

ED: an expanded unique role for midlevel providers. 

Am J Emerg Med. Mar 2003;21(2):125-128. Not 

eligible exposure. 

1045. Ganong LH, Coleman M. Effects of family structure 

information on nurses' impression formation and 

verbal responses. Res Nurs Health. Apr 

1997;20(2):139-151. Not eligible exposure. 

1046. Ganz DA, Simmons SF, Schnelle JF. Costeffectiveness of recommended nurse staffing levels 

for short-stay skilled nursing facility patients. BMC 

Health Serv Res. May 10 2005;5(1):35. Not eligible 

target population. 

1047. Garbett R. Part-time working: speaking out. Nurs 

Times. Sep 4-10 1996;92(36):52-53. Not eligible 

target population. 

1048. Garcia de Lucio L, Garcia Lopez FJ, Marin Lopez 

MT, Mas Hesse B, Caamano Vaz MD. Training 

programme in techniques of self-control and 

communication skills to improve nurses' relationships 

with relatives of seriously ill patients: a randomized 

controlled study. J Adv Nurs. Aug 2000;32(2):425-

431. Not eligible target population. 

1049. Gardner KG, Tilbury M. A longitudinal cost analysis 

of primary and team nursing. Nursing Economics 

Mar-Apr 1991;9(2):97-104. Not relevant. 

1050. Gardiner WC. Documenting JCAHO standards in 

assigning nursing staff. J Healthc Qual. Jul-Aug 

1992;14(4):50-53. No association tested. 

1051. Gardner DL. Career commitment in nursing. J Prof 

Nurs. May-Jun 1992;8(3):155-160. Not eligible 

exposure. 

1052. Gardner J. Help, with strings. Hospitals may find 

Congress will attach some controls to funding for new 

nurses. Mod Healthc. Aug 6 2001;31(32):24. Not 

eligible exposure. 

1053. Gardulf A, Soderstrom IL, Orton ML, Eriksson LE, 

Arnetz B, Nordstrom G. Why do nurses at a 

university hospital want to quit their jobs? J Nurs 

Manag. Jul 2005;13(4):329-337. Not eligible target 

population. 

1054. Garfield M, Jeffrey R, Ridley S. An assessment of the 

staffing level required for a high-dependency unit. 

Anaesthesia. Feb 2000;55(2):137-143. Not eligible 

target population. 

1055. Garretson S. Nurse to patient ratios in American 

health care. Nurs Stand. Dec 15-2005 Jan 4 

2004;19(14-16):33-37. Review.

1056. Garrett DK, McDaniel AM. A new look at nurse 

burnout: the effects of environmental uncertainty and 

social climate. J Nurs Adm. Feb 2001;31(2):91-96. 

Not eligible exposure. 

1057. Garvey A. Counting the costs. Nurs Stand. Jul 30-

Aug 5 2003;17(46):12. News. 

1058. Gary R, Marrone S, Boyles C. The use of gaming 

strategies in a transcultural setting. J Contin Educ 

Nurs. Sep-Oct 1998;29(5):221-227. Review.

1059. Gaston TA, Blankenship J. The shortage of full-time 

nurses working at the bedside is becoming a national 

concern. J Nurses Staff Dev. May-Jun 

2004;20(3):150-151; author reply 151. Comment. 

1060. Gates D. "Patient-focused care" and other 

incantations. Mo Nurse. Mar-Apr 1995;64(2):14-15. 

Comment. 
B-31 

1061. Gaudine AP. What do nurses mean by workload and 

work overload? Can J Nurs Leadersh. May-Jun 

2000;13(2):22-27. Not eligible target population.

1062. Gaze H. Starved of attention. Nurs Times. Jan 17-23 

1990;86(3):20. Comment.

1063. Georges CA, Bolton LB, Bennett C. Quality of care 

in African-American communities and the nursing 

shortage. J Natl Black Nurses Assoc. Dec 

2003;14(2):16-24. No association tested. 

1064. Gerace LM, Hughes TL, Spunt J. Improving nurses' 

responses toward substance-misusing patients: a 

clinical evaluation project. Arch Psychiatr Nurs. Oct 

1995;9(5):286-294. Not eligible exposure. 

1065. Geraci EB, Geraci TA. An observational study of the 

emergency triage nursing role in a managed care 

facility. Journal of Emergency Nursing Jun 

1994;20(3):189-94. Not relevant. 

1066. Gerberich SG, Church TR, McGovern PM, Hansen 

HE, Nachreiner NM, Geisser MS, Ryan AD, Mongin 

SJ, Watt GD. An epidemiological study of the 

magnitude and consequences of work related 

violence: the Minnesota Nurses' Study. Occup 

Environ Med. Jun 2004;61(6):495-503. Not eligible 

exposure. 

1067. Gerrish K, Griffith V. Integration of overseas 

Registered Nurses: evaluation of an adaptation 

programme. J Adv Nurs. Mar 2004;45(6):579-587. 

Not eligible target population. 

1068. Geschwinder RF. Anticoagulation therapy a success 

with patient-focused model. Nurse Pract. Aug 

2004;29(8):46-47. Not eligible exposure.

1069. Gestes JL. Oncology outcomes among supplemental 

staff. Okla Nurse. Sep-Nov 2002;47(3):24-25. 

Comment. 

1070. Geyer S. Workforce. Nursing arithmetic. Trustee. Jun 

2003;56(6):31-32. Comment. 

1071. Ghosh B, Cruz G. Nurse requirement planning: a 

computer-based model. J Nurs Manag. Jul 

2005;13(4):363-371. Not eligible target population.

1072. Gibbs G, Harrison C. Recruitment. Dare to be 

different. Nurs Times. Aug 18-24 1999;95(33):36-38. 

Not eligible target population. 

1073. Gill KP, Ursic P. The impact of continuing education 

on patient outcomes in the elderly hip fracture 

population. J Contin Educ Nurs. Jul-Aug 

1994;25(4):181-185. Not eligible exposure.

1074. Gill SL. The little things: perceptions of breastfeeding 

support. J Obstet Gynecol Neonatal Nurs. Jul-Aug 

2001;30(4):401-409. Not eligible exposure. 

1075. Gillan J. Night nursing. Reflex action. Nurs Times. 

Sep 1-7 1993;89(35):26-28. Case Reports. 

1076. Gillespie BM, Kermode S. How do perioperative 

nurses cope with stress? Contemp Nurse. Dec-2004 

Feb 2003;16(1-2):20-29. Review. 

1077. Gilliland M. Workforce reductions: low morale, 

reduced quality care. Nurs Econ. Nov-Dec 

1997;15(6):320-322. Review. 

1078. Gillis AJ. Nurses' knowledge of growth and 

development principles in meeting psychosocial 

needs of hospitalized children. J Pediatr Nurs. Apr 

1990;5(2):78-87. Not eligible exposure. 

1079. Gilman JA. A quality improvement project for better 

glycemic control in hospitalized patients with 

diabetes. Diabetes Educ. Jul-Aug 2001;27(4):541-

546. Not eligible exposure.

1080. Ginsburg L, Norton PG, Casebeer A, Lewis S. An 

educational intervention to enhance nurse leaders' 

perceptions of patient safety culture. Health Serv Res. 

Aug 2005;40(4):997-1020. Not eligible outcomes.

1081. Giovannetti P, Johnson JM. A new generation patient 

classification system. J Nurs Adm. May 

1990;20(5):33-40. No association tested. 

1082. Giraud T, Dhainaut JF, Vaxelaire JF, Joseph T, 

Journois D, Bleichner G, Sollet JP, Chevret S, 

Monsallier JF. Iatrogenic complications in adult 

intensive care units: a prospective two-center study. 

Crit Care Med. Jan 1993;21(1):40-51. Not eligible 

target population. 

1083. Girou E, Chai SH, Oppein F, Legrand P, Ducellier D, 

Cizeau F, Brun-Buisson C. Misuse of gloves: the 

foundation for poor compliance with hand hygiene 

and potential for microbial transmission? J Hosp 

Infect. Jun 2004;57(2):162-169. Not eligible target 

population. 

1084. Gladstone J. Drug administration errors: a study into 

the factors underlying the occurrence and reporting of 

drug errors in a district general hospital. J Adv Nurs. 

Oct 1995;22(4):628-637. Not eligible target 

population. 

1085. Glassford B. Putting patient safety first. Am J Nurs. 

Nov 2004;104(11):81. Comment.

1086. Glover D. Look before you leap. Nurs Times. Mar 3-

9 1999;95(9):31. Comment. 

1087. Gobbi M. Nursing practice as bricoleur activity: a 

concept explored. Nurs Inq. Jun 2005;12(2):117-125. 

Not eligible target population.

1088. Gobis L. The perils of floating. Am J Nurs. Sep 

2001;101(9):78. Legal Cases. 

1089. Godin M. A patient classification system for the 

hemodialysis setting. Nurs Manage. Nov 

1995;26(11):66-67. Comment.

1090. Gold DR, Rogacz S, Bock N, Tosteson TD, Baum 

TM, Speizer FE, Czeisler CA. Rotating shift work, 

sleep, and accidents related to sleepiness in hospital 

nurses. Am J Public Health. Jul 1992;82(7):1011-

1014. Not eligible outcomes. 

1091. Golder DJ. Long night's journey into day. Am J Nurs. 

May 1994;94(5):88. Comment. 

1092. Goldman BD. Nontraditional staffing models in longterm care. J Gerontol Nurs. Sep 1998;24(9):29-34. 

Not eligible target population.

1093. Goldman HG. Role expansion in intensive care: 

survey of nurses' views. Intensive Crit Care Nurs. Dec 

1999;15(6):313-323. Not eligible target population. 

1094. Goldman RL, Bates DP, 3rd, Bradbury M, Breaux 

DK, Caron M, Gerardo C, Copoulos S, Hansen LL, 

Oien SM, Semones C, et al. Marketing alternatives 

for hospitals to the nursing crisis. J Hosp Mark. 

1990;4(1):71-95. No association tested. 
B-32 

1095. Goldstein MJ, Kim E, Widmann WD, Hardy MA. A 

360 degrees evaluation of a night-float system for 

general surgery: a response to mandated work-hours 

reduction. Curr Surg. Sep-Oct 2004;61(5):445-451. 

Not eligible exposure.

1096. Golightly C, Wright LK, Pogue L. A model to 

facilitate interactive planning. J Nurs Adm. Sep 

1990;20(9):16-19. No association tested.

1097. Gomez CR, Malkoff MD, Sauer CM, Tulyapronchote 

R, Burch CM, Banet GA. Code stroke. An attempt to 

shorten inhospital therapeutic delays. Stroke. Oct 

1994;25(10):1920-1923. Not eligible exposure. 

1098. Goncalves MB, Fischer FM, Lombardi Junior M, 

Ferreira RM. Work activities of practical nurses and 

risk factors for the development of musculoskeletal 

disorders. J Hum Ergol (Tokyo). Dec 2001;30(1-

2):369-374. Not eligible target population. 

1099. Gonzalez JC, Routh DK, Armstrong FD. Differential 

medication of child versus adult postoperative 

patients: the effect of nurses' assumptions. Child 

Health Care. Winter 1993;22(1):47-59. Not eligible 

exposure. 

1100. Gonzalez-Torre PL, Adenso-Diaz B, Sanchez-Molero 

O. Capacity planning in hospital nursing: a model for 

minimum staff calculation. Nurs Econ. Jan-Feb 

2002;20(1):28-36. Not eligible target population. 

1101. Goodacre SW, Gillett M, Harris RD, Houlihan KP. 

Consistency of retrospective triage decisions as a 

standardised instrument for audit. J Accid Emerg 

Med. Sep 1999;16(5):322-324. Not eligible target 

population. 

1102. Goodare L. All right on the nights. Nurs Times. Oct 

21-27 2003;99(42):38-39. Comment.

1103. Goode CJ. Impact of a CareMap and case 

management on patient satisfaction and staff 

satisfaction, collaboration, and autonomy. Nurs Econ. 

Nov-Dec 1995;13(6):337-348, 361. Not eligible 

exposure. 

1104. Goode CJ. What variables should I consider when 

making staffing decisions? Nurs Manage. Jun 

2001;32(6):13-14. Review. 

1105. Goode CJ, Krugman ME, Smith K, Diaz J, Edmonds 

S, Mulder J. The pull of magnetism: a look at the 

standards and the experience of a western academic 

medical center hospital in achieving and sustaining 

Magnet status. Nurs Adm Q. Jul-Sep 2005;29(3):202-

213. Not eligible exposure. 

1106. Gooding L. A hard day's night. Nurs Manag 

(Harrow). Sep 2004;11(5):23-26. Not eligible target 

population. 

1107. Goossen WT, Epping PJ, Van den Heuvel WJ, Feuth 

T, Frederiks CM, Hasman A. Development of the 

Nursing Minimum Data Set for the Netherlands 

(NMDSN): identification of categories and items. J 

Adv Nurs. Mar 2000;31(3):536-547. Not eligible 

target population. 

1108.Gordon S. The impact of managed care on female 

caregivers in the hospital and home. J Am Med 

Womens Assoc. Spring 1997;52(2):75-77, 80. Not 

eligible outcomes. 

1109. Gordon S, Buresh B. Sounding the alarm. Am J Nurs. 

Jun 1996;96(6):21-22. Comment. 

1110. Gosztyla J, Fowler S. Survival skills in the acute care 

workplace: a "float" pool perspective. N J Nurse. JunJul 1998;28(6):14. Comment. 

1111. Gosztyla J, Fowler S. Staff nurse column. Survival 

skills in the acute care workplace: a "float" pool 

perspective. New Jersey nurse Jun-Jul 1998;28(6):14. 

Not peer reviewed. 

1112. Gottvall K, Waldenstrom U. Does birth center care 

during a woman's first pregnancy have any impact on 

her future reproduction? Birth. Sep 2002;29(3):177-

181. Not eligible target population.

1113. Gould D. Systematic observation of hand 

decontamination. Nurs Stand. Aug 4-10 

2004;18(47):39-44. Not eligible target population.

1114. Gould D, Chamberlain A. The use of a ward-based 

educational teaching package to enhance nurses' 

compliance with infection control procedures. J Clin 

Nurs. Jan 1997;6(1):55-67. Not eligible exposure.

1115. Gould J, Charlton S. The impact of change on violent 

patients. Nurs Stand. Feb 2-8 1994;8(19):38-40. Not 

eligible exposure. 

1116. Grady C, Jacob J, Romano C. Confidentiality: a 

survey in a research hospital. J Clin Ethics. Spring 

1991;2(1):25-30; discussion 30-24. Not eligible 

exposure. 

1117. Grady C, Griffith CA. A modified simulation 

program addressing a staff nurse educational need 

identified by a student clinical nurse specialist across 

three shifts in a cardiac step-down unit. Clinical 

Nurse Specialist Mar-Apr 2006;20(2):90. Not 

relevant. 

1118. Grady G. Temporary assignments can open many 

doors. Crit Care Nurse. Feb 2000;Suppl:18. 

Comment. 

1119. Grady MA, Bloom KC. Pregnancy outcomes of 

adolescents enrolled in a CenteringPregnancy 

program. J Midwifery Womens Health. Sep-Oct 

2004;49(5):412-420. Not eligible exposure. 

1120. Graf E. Pulling from Peter to save Paul: is "floating" 

administratively or professionally sound? Revolution. 

Fall 1994;4(3):47-49. Comment.

1121. Graf E. Pulling from Peter to save Paul: is "floating" 

administratively or professionally sound? Revolution. 

Fall-Winter 1998;8(3-4):80-83. Comment. 

1122. Graff LG, Radford MJ. Formula for emergency 

physician staffing. Am J Emerg Med. May 

1990;8(3):194-199. Not eligible exposure. 

1123. Graham IW. Reflective narrative and dementia care. J 

Clin Nurs. Nov 1999;8(6):675-683. Not eligible 

target population. 

1124. Graham IW. Reflective practice and its role in mental 

health nurses' practice development: a year-long 

study. J Psychiatr Ment Health Nurs. Apr 

2000;7(2):109-117. Not eligible target population.

1125. Graham MV. A day-to-day decision support tool. 

Nurs Manage. Mar 1995;26(3):48I, 48L. Comment.

1126. Granberg A, Engberg IB, Lundberg D. Acute 

confusion and unreal experiences in intensive care 

patients in relation to the ICU syndrome. Part II. 

Intensive Crit Care Nurs. Feb 1999;15(1):19-33. Not 

eligible target population. 
B-33 

1127. Grandell-Niemi H, Hupli M, Leino-Kilpi H, Puukka 

P. Medication calculation skills of nurses in Finland. J 

Clin Nurs. Jul 2003;12(4):519-528. Not eligible target 

population. 

1128. Grant AM, Grinspun D, Hernandez CA. The revision 

of a workload measurement tool to reflect the nursing 

needs of patients with traumatic brain injury. Rehabil 

Nurs. Nov-Dec 1995;20(6):306-309, 313. No 

association tested. 

1129. Grant LA, Potthoff SJ, Ryden M, Kane RA. Staff 

ratios, training, and assignment in Alzheimer's special 

care units. J Gerontol Nurs. Jan 1998;24(1):9-16; quiz 

59. Not eligible target population. 

1130. Grant M, Ferrell BR, Rivera LM, Lee J. Unscheduled 

readmissions for uncontrolled symptoms. A health 

care challenge for nurses. Nurs Clin North Am. Dec 

1995;30(4):673-682. Not eligible exposure.

1131. Granum V. Nursing students' perceptions of nursing 

as a subject and a function. J Nurs Educ. Jul 

2004;43(7):297-304. Not eligible target population. 

1132. Grassman D. Development of inpatient oncology 

educational and support programs. Oncol Nurs 

Forum. May 1993;20(4):669-676. No association 

tested. 

1133. Gray J, Cass J, Harper DW, O'Hara PA. A controlled 

evaluation of a lifts and transfer educational program 

for nurses. Geriatr Nurs. Mar-Apr 1996;17(2):81-85. 

Review. 

1134. Gray JE, Safran C, Davis RB, Pompilio-Weitzner G, 

Stewart JE, Zaccagnini L, Pursley D. Baby CareLink: 

using the internet and telemedicine to improve care 

for high-risk infants. Pediatrics. Dec 

2000;106(6):1318-1324. Not eligible exposure.

1135. Greaves C. Patients' perceptions of bedside handover. 

Nurs Stand. Dec 8-14 1999;14(12):32-35. Not eligible 

target population. 

1136. Green A, Beeney J, Johnson N, Carlson B. Action 

STAT! The crisis nurse. Nurs Manage. Oct 

1998;29(10):41-42. Comment. 

1137. Green JM, Kitzinger JV, Coupland VA. Stereotypes 

of childbearing women: a look at some evidence. 

Midwifery. Sep 1990;6(3):125-132. Not eligible 

target population. 

1138. Greenberg M. Hailing one of health care's priceless 

resources--nurses commentary. S C Nurse. Apr-Jun 

2002;9(2):31. Comment. 

1139. Greene J. From whodunit to what happened. Hosp 

Health Netw. Apr 1999;73(4):50-52, 54. Comment. 

1140. Greene J. Medical staff. Hitting the visa limit. Hosp 

Health Netw. Jan 2004;78(1):16. News.

1141. Greene J, Nordhaus-Bike AM. Nurse shortage. Where 

have all the RNs gone? Hosp Health Netw. Aug 5-20 

1998;72(15-16):78, 80. Comment. 

1142. Greene SA, Powell CW. Expansion of clinical 

pharmacy services through staff development. Am J 

Hosp Pharm. Aug 1991;48(8):1704-1708. Not eligible 

target population. 

1143. Greeneich D. Developing a consumer-focused unit 

culture. Aspens Advis Nurse Exec. Apr 1994;9(7):1-

4. Comment.

1144. Greenglass ER, Burke RJ. Stress and the effects of 

hospital restructuring in nurses. Can J Nurs Res. Sep 

2001;33(2):93-108. Not eligible exposure. 

1145. Greengold NL, Shane R, Schneider P, Flynn E, 

Elashoff J, Hoying CL, Barker K, Bolton LB. The 

impact of dedicated medication nurses on the 

medication administration error rate: a randomized 

controlled trial. Arch Intern Med. Oct 27 

2003;163(19):2359-2367. Not eligible outcomes. 

1146. Gregoire MB. Quality of patient meal service in 

hospitals: delivery of meals by dietary employees vs 

delivery by nursing employees. J Am Diet Assoc. Oct 

1994;94(10):1129-1134. Not eligible exposure. 

1147. Gregoire MB. Who should serve patient meals? Hosp 

Food Nutr Focus. Jul 1995;11(11):6-7. Not eligible 

exposure. 

1148. Gresk KD. Twelve-hour shifts on a new telemetry 

unit. Nurs Manage. Feb 1991;22(2):40-42. No 

association tested. 

1149. Grewal PS, Sawant NH, Deaney CN, Gibson KM, 

Gupta AM, Haverty PF, Panditaratne HG, 

Samarasinghe SR, Sharma A, Singh S, Turner SA, 

Wilkinson SL, Wood SP, Glickman S. Pressure sore 

prevention in hospital patients: a clinical audit. J 

Wound Care. Mar 1999;8(3):129-131. Not eligible 

target population. 

1150. Grice AS, Picton P, Deakin CD. Study examining 

attitudes of staff, patients and relatives to witnessed 

resuscitation in adult intensive care units. Br J 

Anaesth. Dec 2003;91(6):820-824. Not eligible target 

population. 

1151. Griesmer H. Self-scheduling turned us into a winning 

team. Rn. Dec 1993;56(12):21-23. No association 

tested. 

1152. Griffith DE, Hardeman JL, Zhang Y, Wallace RJ, 

Mazurek GH. Tuberculosis outbreak among 

healthcare workers in a community hospital. Am J 

Respir Crit Care Med. Aug 1995;152(2):808-811. 

Case Reports. 

1153. Griffiths H. Responding to Esther's voice: improving 

the care of acutely ill older adults. Nurs BC. Dec 

2004;36(5):8-11. Comment.

1154. Griffiths P. Clinical outcomes for nurse-led in-patient 

care. Nurs Times. Feb 28-Mar 5 1996;92(9):40-43. 

Not eligible target population. 

1155. Griffiths P, Riddington L. Nurses' use of computer 

databases to identify evidence for practice--a crosssectional questionnaire survey in a UK hospital. 

Health Info Libr J. Mar 2001;18(1):2-9. Not eligible 

target population. 

1156. Grindel CG, Patsdaughter CA, Medici G, Babington 

LM. Adult-health/medical-surgical nurses' 

perceptions of students' contributions to clinical 

agencies. Medsurg Nurs. Apr 2003;12(2):117-123. 

Not eligible exposure. 

1157. Grindel CG, Peterson K, Kinneman M, Turner TL. 

The Practice Environment Project. A process for 

outcome evaluation. J Nurs Adm. May 

1996;26(5):43-51. No association tested. 

1158. Grinspun D. Putting patients first: the role of nursing 

caring. Hosp Q. Summer 2000;3(4):22-24. Comment. 
B-34 

1159. Gropper EI, Boily CA. Breathing life into customer 

satisfaction. Nurs Manage. Nov 1999;30(11):64-68. 

No association tested. 

1160. Gropper RG. Spotlight on. Redesigning faculty roles 

to enhance program outcomes: a case study. Nurse 

educator Jul-Aug 1995;20(4):5-7. Not relevant. 

1161. Grossman I, Weiss LM, Simon D, Tanowitz HB, 

Wittner M. Blastocystis hominis in hospital 

employees. Am J Gastroenterol. Jun 1992;87(6):729-

732. Not eligible exposure. 

1162. Grossman RJ. The staffing crisis. Health Forum J. 

May-Jun 2002;45(3):10-15. Review. 

1163. Grossman S, Wheeler K, Lippman D. Role-modeling 

experience improves nursing students' attitudes 

toward people living with AIDS. Nursingconnections. 

Spring 1998;11(1):41-49. Not eligible exposure.

1164. Grouse A, Bishop R. Non-medical technicians reduce 

emergency department waiting times. Emerg Med 

(Fremantle). Mar 2001;13(1):66-69. Not eligible 

target population. 

1165. Grumbach K, Ash M, Seago JA, Spetz J, Coffman J. 

Measuring shortages of hospital nurses: how do you 

know a hospital with a nursing shortage when you see 

one? Med Care Res Rev. Dec 2001;58(4):387-403. 

Not eligible exposure. 

1166. Grzybowski M, Ownby DR, Peyser PA, Johnson CC, 

Schork MA. The prevalence of anti-latex IgE 

antibodies among registered nurses. J Allergy Clin 

Immunol. Sep 1996;98(3):535-544. Not eligible 

exposure. 

1167. Guidez C. [How can a nursing team participate in a 

clinical trial? Zoladex, flutamide trial]. Soins. Sep 

1990(540):53. Not eligible target population. 

1168. Gullick J. A study into safe and efficient use of 

defibrillators by nurses. Nurs Times. Nov 2-8 

2004;100(44):42-44. Not eligible target population. 

1169. Gullick J, Shepherd M, Ronald T. The effect of an 

organisational model on the standard of care. Nurs 

Times. Mar 9-15 2004;100(10):36-39. Not eligible 

target population. 

1170. Gundogmus UN, Ozkara E, Mete S. Nursing and 

midwifery malpractice in Turkey based on the Higher 

Health Council records. Nurs Ethics. Sep 

2004;11(5):489-499. Not eligible target population. 

1171. Gunning CS. Looking to the future: health 

professions education in Texas. Tex Nurs. Apr 

2000;74(4):11-12. Comment. 

1172. Gupta A, Della-Latta P, Todd B, San Gabriel P, Haas 

J, Wu F, Rubenstein D, Saiman L. Outbreak of 

extended-spectrum beta-lactamase-producing 

Klebsiella pneumoniae in a neonatal intensive care 

unit linked to artificial nails. Infect Control Hosp 

Epidemiol. Mar 2004;25(3):210-215. Not eligible 

exposure. 

1173. Gupta S, Pati AK. Desynchronization of circadian 

rhythms in a group of shift working nurses: effects of 

pattern of shift rotation. J Hum Ergol (Tokyo). Dec 

1994;23(2):121-131. Not eligible target population. 

1174. Guy J, Persaud J, Davies E, Harvey D. Drug errors: 

what role do nurses and pharmacists have in 

minimizing the risk? J Child Health Care. Dec 

2003;7(4):277-290. Not eligible target population. 

1175. Hackel R, Butt L, Banister G. How nurses perceive 

medication errors. Nurs Manage. Jan 1996;27(1):31, 

33-34. No association tested. 

1176. Hackenschmidt A. Living with nurse staffing ratios: 

early experiences. J Emerg Nurs. Aug 

2004;30(4):377-379. Review. 

1177. Haddad A. Ethics in action. A float nurse from the 

newborn nursery who has scant critical care 

experience. Rn. Jul 1995;58(7):21-22, 24. Comment. 

1178. Haddad A. Ethics in action. "Fess up" to patients? Rn. 

Sep 2003;66(9):27-30. Not eligible exposure. 

1179. Hader R, Claudio T. Seven methods to effectively 

manage patient care labor resources. J Nurs Adm. Feb 

2002;32(2):66-68. Review. 

1180. Hafsteinsdottir TB, Grypdonck MH. NDT 

competence of nurses caring for patients with stroke. 

J Neurosci Nurs. Oct 2004;36(5):289-294. Not 

eligible target population. 

1181. Hagenow NR. Why not person-centered care? The 

challenges of implementation. Nurs Adm Q. Jul-Sep 

2003;27(3):203-207. Case reports. 

1182. Hagenstad R, Weis C, Brophy K. Strike a balance 

with decentralized housekeeping. Nurs Manage. Jun 

2000;31(6):39-43. Not eligible exposure. 

1183. Hageseth KL. Flexible scheduling and part-time 

work. Focus Crit Care. Aug 1991;18(4):273. 

Comment.

1184. Haggart R, Rushforth H. 'A child's eye view': the 

development and evaluation of a teaching video. 

Paediatr Nurs. Dec-2000 Jan 1999;11(10):27-30. Not 

eligible exposure. 

1185. Haigh C, Neild A, Duncan F. Balance of power--do 

patients use researchers to survive hospital? Nurse 

Res. 2005;12(4):71-81. Not eligible target population.

1186. Hainsworth DS. The effect of death education on 

attitudes of hospital nurses toward care of the dying. 

Oncol Nurs Forum. Jul 1996;23(6):963-967. Not 

eligible exposure. 

1187. Haisfield ME, McGuire DB, Krumm S, Shore AD, 

Zabora J, Rubin HR. Patients' and healthcare 

providers' opinions regarding advance directives. 

Oncol Nurs Forum. Aug 1994;21(7):1179-1187. Not 

eligible exposure. 

1188. Hale C. Evaluating a change to primary nursing: some 

methodological issues. Nurs Pract. 1991;4(4):12-16. 

No association tested. 

1189. Hale PC, Houghton A, Taylor PR, Mason RC, Owen 

WJ, Bonell C, McColl L. Crossover trial of partial 

shift working and a one in six rota system for house 

surgeons in two teaching hospitals. J R Coll Surg 

Edinb. Feb 1995;40(1):55-58. Not eligible target 

population. 

1190. Haley RW, Cushion NB, Tenover FC, Bannerman 

TL, Dryer D, Ross J, Sanchez PJ, Siegel JD. 

Eradication of endemic methicillin-resistant 

Staphylococcus aureus infections from a neonatal 

intensive care unit. J Infect Dis. Mar 

1995;171(3):614-624. No association tested. 

1191. Hall DS. Work-related stress of registered nurses in a 

hospital setting. J Nurses Staff Dev. Jan-Feb 

2004;20(1):6-14; quiz 15-16. Not eligible exposure.
B-35 

1193. Hall EO. A double concern: Danish grandfathers' 

experiences when a small grandchild is critically ill. 

Intensive Crit Care Nurs. Feb 2004;20(1):14-21. Not 

eligible target population. 

1194. Hall LM, Doran D. Nurse staffing, care delivery 

model, and patient care quality. J Nurs Care Qual. 

Jan-Mar 2004;19(1):27-33. Not eligible association 

presentation. 

1195. Hall LM, Doran D, Laschinger HS, Mallette C, 

Pedersen C, O'Brien-Pallas LL. A balanced scorecard 

approach for nursing report card development. 

Outcomes Manag. Jan-Mar 2003;7(1):17-22. Review. 

1196. Hall LMPRN. Nursing staff mix models and 

outcomes. Journal of Advanced Nursing October. 

2003;44(2):217-226. Not eligible outcomes.

1197. Hall M. My sham trial. Nurs Stand. Oct 15-21 

1997;12(4):18-19. Comment.

1198. Hallberg IR, Norberg A. Strain among nurses and 

their emotional reactions during 1 year of systematic 

clinical supervision combined with the 

implementation of individualized care in dementia 

nursing. J Adv Nurs. Dec 1993;18(12):1860-1875. 

Not eligible target population.

1199. Haller E, McNiel DE, Binder RL. Impact of a 

smoking ban on a locked psychiatric unit. J Clin 

Psychiatry. Aug 1996;57(8):329-332. Not eligible 

exposure. 

1200. Halloran EJ. RN staffing: more care--less cost. Nurs 

Manage. Sep 1983;14(9):18-22. Not eligible year. 

1201. Halpern JS. Leah L. Curtin discusses the nursing 

shortage. Int J Trauma Nurs. Jul-Sep 2000;6(3):85-87. 

Interview. 

1202. Hamer G. A patient rates nurses: the good, the bad 

and the loving. J Christ Nurs. Summer 1990;7(3):28-

31. No association tested. 

1203. Hamilton D, Strawn N. Keeping your eye on the ball: 

an open letter to nurse executives. Aspens Advis 

Nurse Exec. Jun 1998;13(9):9-11. Comment. 

1204. Hamilton J. Ten tips for telling people what they don't 

want to hear. Aspens Advis Nurse Exec. May 

1993;8(8):1-2. Comment. 

1205. Hamilton J, Edgar L. A survey examining nurses' 

knowledge of pain control. J Pain Symptom Manage. 

Jan 1992;7(1):18-26. Not eligible outcomes.

1206. Hamilton M. Combining utilization management and 

discharge planning. J Healthc Qual. Jul-Aug 

1995;17(4):7-10, 17; quiz 17, 44. Not eligible 

exposure. 

1207. Hampton S. Can electric beds aid pressure sore 

prevention in hospitals? Br J Nurs. Sep 24-Oct 7 

1998;7(17):1010-1017. Not eligible exposure. 

1208. Han Y, Huh SJ, Ju SG, Ahn YC, Lim do H, Lee JE, 

Park W. Impact of an electronic chart on the staff 

workload in a radiation oncology department. Jpn J 

Clin Oncol. Aug 2005;35(8):470-474. Not eligible 

target population. 

1209. Hancock MR. A pointless system? Am J Nurs. Aug 

1992;92(8):18. Comment. 

1210. Hand D. NHS cuts: shifting attitudes. Nurs Stand. 

Dec 5-11 1990;5(11):20. Not eligible target 

population. 

1211. Handelman E. Short-staffed but safe. Am J Nurs. Nov 

2003;103(11):120. News.

1212. Hansen HE, Biros MH, Delaney NM, Schug VL. 

Research utilization and interdisciplinary 

collaboration in emergency care. Acad Emerg Med. 

Apr 1999;6(4):271-279. Not eligible exposure. 

1213. Hanson RH, Balk JA. A replication study of staff 

injuries in a state hospital. Hosp Community 

Psychiatry. Aug 1992;43(8):836-837. Comment. 

1214. Hansten R. Streamline change-of-shift report. Nurs 

Manage. Aug 2003;34(8):58-59. Comment. 

1215. Hansten R, Washburn MJ. Professional practice: facts 

& impact. Am J Nurs. Mar 1998;98(3):42-45. 

Comment. 

1216. Harber P, Pena L, Hsu P, Billet E, Greer D, Kim K. 

Personal history, training, and worksite as predictors 

of back pain of nurses. Am J Ind Med. Apr 

1994;25(4):519-526. Not eligible outcomes.

1217. Hardin S, Hussey L. AACN Synergy model for 

patient care. Case study of a CHF patient. Crit Care 

Nurse. Feb 2003;23(1):73-76. Case Reports.

1218. Harding LK, Harding NJ, Warren H, Mills A, 

Thomson WH. The radiation dose to accompanying 

nurses, relatives and other patients in a nuclear 

medicine department waiting room. Nucl Med 

Commun. Jan 1990;11(1):17-22. Not eligible target 

population. 

1219. Harding R. Reflections on family-centred care. 

Paediatr Nurs. Nov 1997;9(9):19-21. Not eligible 

target population. 

1220. Hardy LK. Nursing work and the implications of "the 

second shift". Can J Nurs Adm. Nov-Dec 

1990;3(4):23-26. Not eligible exposure. 

1221. Hardy M, Barrett C. Interpretation of trauma 

radiographs by radiographers and nurses in the UK: a 

comparative study. Br J Radiol. Aug 

2004;77(920):657-661. Not eligible target population.

1222 Hardy ML, Barrett C. Requesting and interpreting 

trauma radiographs: a role extension for accident & 

emergency nurses. Accid Emerg Nurs. Oct 

2003;11(4):202-213. Not eligible target population. 

1223. Harloe LJ, Greenway MN, O'Connor S, Fowle T, 

Hayes K, Pendall D, Stewart C, Squires L, Bond M, 

White K. Generating ideas for research: an Australian 

research experience. Gastroenterol Nurs. Jul-Aug 

1995;18(4):138-141. Not eligible target population. 

1224. Harmond K. Time out. Nurs Stand. May 30-Jun 5 

1990;4(36):47. Not eligible target population. 

1225. Harmond K. Caring for sick buildings. Nurs Stand. 

Jun 19-25 1991;5(39):44. Not eligible target 

population. 

1226. Harrahill M, Eastes L. Trauma nurse practitioner: the 

perfect job? J Emerg Nurs. Aug 1999;25(4):337-338. 

Comment. 

1227. Harrington SS, Walker BL. Is computer-based 

instruction an effective way to present fire safety 

training to long-term care staff? J Nurses Staff Dev. 

May-Jun 2003;19(3):147-154. Not eligible exposure. 

1228. Harris M, Gavel P, Conn W. Planning Australia's 

hospital workforce. Aust Health Rev. 2002;25(5):61-

77. Not eligible target population.
B-36 

1229. Harrison JP, Nolin J, Suero E. The Effect of Case 

Management on U.S. Hospitals. Nursing Economics. 

March-April 2004 2004;22(2):64-70. Not eligible 

outcomes. 

1230. Harrison S, Hutton L, Nowak M. An investigation of 

professional advice advocating therapeutic sun 

exposure. Aust N Z J Public Health. Apr 

2002;26(2):108-115. Not eligible exposure. 

1231. Hart A, Lockey R. Inequalities in health care 

provision: the relationship between contemporary 

policy and contemporary practice in maternity 

services in England. J Adv Nurs. Mar 

2002;37(5):485-493. Not eligible target population. 

1232. Hart J, Neiman V, Chaimoff C, Wolloch Y, Djaldetti 

M. Patient satisfaction in two departments of surgery 

in a community hospital. Isr J Med Sci. Dec 

1996;32(12):1338-1343. Not eligible target 

population. 

1233. Hart SE. Hospital ethical climates and registered 

nurses' turnover intentions. J Nurs Scholarsh. 

2005;37(2):173-177. Not eligible exposure.

1234. Hartley J. Reduced doctors' hours. Nurs Times. Jul 

27-Aug 2 2004;100(30):20-23. Not eligible target 

population. 

1235. Hartley J. Nurses face a lottery over choice of shifts. 

Nurs Times. Jul 5-11 2005;101(27):10-11. News.

1236. Harty-Golder B. How should a lab design a fail-safe 

system for point-of-care testing? MLO Med Lab Obs. 

Dec 2001;33(12):22-23. Comment. 

1237. Hasan-Stein L. Two hospitals report: the pros and 

cons of 12-hour shifts. Nurs N Z. Mar 1998;4(2):14-

15. Not eligible target population. 

1238. Hastings C, Waltz C. Assessing the outcomes of 

professional practice redesign. Impact on staff nurse 

perceptions. J Nurs Adm. Mar 1995;25(3):34-42. Not 

eligible exposure. 

1239. Hatcher I, Sullivan M, Hutchinson J, Thurman S, 

Gaffney FA. An intravenous medication safety 

system: preventing high-risk medication errors at the 

point of care. J Nurs Adm. Oct 2004;34(10):437-439. 

Not eligible exposure.

1240. Havens DS, Vasey J. Measuring staff nurse decisional 

involvement: the Decisional Involvement Scale. J 

Nurs Adm. Jun 2003;33(6):331-336. Not eligible 

outcomes. 

1241. Havlovic SJ, Lau DC, Pinfield LT. Repercussions of 

work schedule congruence among full-time, parttime, and contingent nurses. Health Care Manage 

Rev. Fall 2002;27(4):30-41. Not eligible exposure.

1242. Hawkins CA, O'Connor L, Potter S. 'The ones that got 

away': implementing an exit policy for nurses in a 

public hospital. Contemp Nurse. Aug 2003;15(1-

2):29-36. Not eligible target population.

1243. Hawkins T, Sutton K. Self-scheduling in a CVICU 

(cardiovascular intensive care unit). Nurs Manage. 

Nov 1991;22(11):64A, 64D, 64F passim. Not eligible 

outcomes. 

1244. Hay E, Bekerman L, Rosenberg G, Peled R. Quality 

assurance of nurse triage: consistency of results over 

three years. Am J Emerg Med. Mar 2001;19(2):113-

117. Not eligible target population. 

1245. Hayes J. Non-nursing duties are eroding our status. 

Aust Nurs J. Dec-2000 Jan 1999;7(6):3. Not eligible 

target population. 

1246. Hayes J. Time to change. Nurs Stand. Feb 23-Mar 1 

2005;19(24):78. Comment. 

1247. Haynes G, Lewer H, Woolford P. Night nurse 

practitioners are not 'mini-doctors'. Br J Nurs. Nov 

26-Dec 9 1992;1(14):722-725. Comment.

1248. Healy AN. Teaming up for more with less. Provider. 

Apr 2004;30(4):41-42. Comment. 

1249. Heatlie JM. Reducing insulin medication errors: 

evaluation of a quality improvement initiative. J 

Nurses Staff Dev. Mar-Apr 2003;19(2):92-98. Not 

eligible exposure. 

1250. Hecht WA, Landstrom G, Nisbet MM, Ratcliffe CJ, 

Tyler JL. Meeting the nursing shortage head on. A 

round table discussion. Healthc Financ Manage. Mar 

2003;57(3):52-58, 60. Comment. 

1251. Heckert DA, Fottler MD, Swartz BW, Mercer AA. 

The impact of the changing healthcare environment 

on the attitudes of nursing staff: a longitudinal case 

study. Health Serv Manage Res. Aug 1993;6(3):191-

202. Not eligible exposure.

1252. Hedstrom M, Skolin I, von Essen L. Distressing and 

positive experiences and important aspects of care for 

adolescents treated for cancer. Adolescent and nurse 

perceptions. Eur J Oncol Nurs. Mar 2004;8(1):6-17; 

discussion 18-19. Not eligible target population. 

1253. Heinz D. Hospital nurse staffing and patient 

outcomes: a review of current literature. Dimens Crit 

Care Nurs. Jan-Feb 2004;23(1):44-50. Review. 

1254. Heller A. Nurses rightfully are tired. Mich Nurse. Feb 

2001;74(2):4-5. Comment. 

1255. Hemmings P. Shift systems: staying power. Nurs 

Stand. Aug 10-16 1994;8(46):42. Comment. 

1256. Hendel T, Fish M, Aboudi S. Strategies used by 

hospital nurses to cope with a national crisis: a 

manager's perspective. Int Nurs Rev. Dec 

2000;47(4):224-231. Not eligible target population. 

1257. Hendel T, Fish M, Galon V. Leadership style and 

choice of strategy in conflict management among 

Israeli nurse managers in general hospitals. J Nurs 

Manag. Mar 2005;13(2):137-146. Not eligible target 

population. 

1258. Hendler I, Nahtomi O, Segal E, Perel A, Wiener M, 

Meyerovitch J. The effect of full protective gear on 

intubation performance by hospital medical 

personnel. Mil Med. Apr 2000;165(4):272-274. Not 

eligible target population. 

1259. Hendy R. Auditing PICC line management. Nurs 

Times. Sep 20-26 2001;97(38):32-33. Not eligible 

target population. 

1260. Henneman EA, Gawlinski A. A "near-miss" model 

for describing the nurse's role in the recovery of 

medical errors. J Prof Nurs. May-Jun 2004;20(3):196-

201. Not eligible exposure. 

1261. Henninger DE, Nolan MT. A comparative evaluation 

of two educational strategies to promote publication 

by nurses. J Contin Educ Nurs. Mar-Apr 

1998;29(2):79-84. Not eligible exposure. 
B-37 

1262. Hensing G, Alexanderson K. The association between 

sex segregation, working conditions, and sickness 

absence among employed women. Occup Environ 

Med. Feb 2004;61(2):e7. Not eligible target 

population. 

1263. Hensinger B, Harkins D, Bruce T. Self-scheduling: 

two success stories. No more short staffing. Am J 

Nurs. Mar 1993;93(3):66-69. Comment. 

1264. Herman CJ, Speroff T, Cebul RD. Improving 

compliance with immunization in the older adult: 

results of a randomized cohort study. J Am Geriatr 

Soc. Nov 1994;42(11):1154-1159. Not eligible 

exposure. 

1265. Herrmann J. Canadian nurses head South. Health Syst 

Rev. May-Jun 1992;25(3):33-35. News. 

1266. Herrmann LL, Zabramski JM. Tandem practice 

model: a model for physician-nurse practitioner 

collaboration in a specialty practice, neurosurgery. J 

Am Acad Nurse Pract. Jun 2005;17(6):213-218. 

Review.

1267. Hertting A, Nilsson K, Theorell T, Larsson US. 

Downsizing and reorganization: demands, challenges 

and ambiguity for registered nurses. J Adv Nurs. Jan 

2004;45(2):145-154. Not eligible target population.

1268. Hess RG, Jr. Wrinkles in time. Nurs Spectr (Wash D 

C). May 5 1997;7(9):3. Editorial. 

1269. Hesterly SC, Schaffner A, Lounsbery K. Milestone 

Action Plans. Empowering nurses to manage care. J 

Nurs Adm. Nov 1992;22(11):53-56. No association 

tested. 

1270. Hewitt BE. The challenge of providing family-centred 

care during air transport: an example of reflection on 

action in nursing practice. Contemp Nurse. Aug 

2003;15(1-2):118-124. Not eligible exposure.

1271. Hewlett PO. Conceptualizing nursing work-force 

redevelopment. J Nurs Adm. Oct 1999;29(10):8-10, 

29. No association tested. 

1272. Heyman EN, Lombardo BA. Managing costs: the 

confused, agitated, or suicidal patient. Nurs Econ. 

Mar-Apr 1995;13(2):107-111, 118. Not eligible 

exposure. 

1273. Hibbs PJ. Skill mix in hospital. Sr Nurse. Sep-Oct 

1992;12(5):14-17. No association tested. 

1274. Higgins J, Wiles R. Private patients' perceptions of 

nursing practice in the National Health Service. Nurs 

Pract. 1992;5(3):20-22. Not eligible target 

population. 

1275. Higgins LW. Nurses' perceptions of collaborative 

nurse-physician transfer decision making as a 

predictor of patient outcomes in a medical intensive 

care unit. J Adv Nurs. Jun 1999;29(6):1434-1443. Not 

eligible outcomes. 

1276. Higgins R, Hurst K, Wistow G. Nursing acute 

psychiatric patients: a quantitative and qualitative 

study. J Adv Nurs. Jan 1999;29(1):52-63. Not eligible 

target population. 

1277. Higuchi KA, Dulberg C, Duff V. Factors associated 

with nursing diagnosis utilization in Canada. Nurs 

Diagn. Oct-Dec 1999;10(4):137-147. Not eligible 

exposure. 

1278.Hill A, Burge A, Skinner C. Tuberculosis in National 

Health Service hospital staff in the west Midlands 

region of England, 1992-5. Thorax. Nov 

1997;52(11):994-997. Not eligible target population.

1279.Hilton J. A care pathway for home parenteral 

nutrition. Nurs Times. May 4-10 2000;96(18):38-39. 

Not eligible exposure. 

1280.Hilton P, Goddard M. Taken to task. Nurs Times. Apr 

17-23 1996;92(16):44-45. Not eligible target 

population. 

1281.Himali U. An unsafe equation: fewer RNs = more 

workplace injuries. Am Nurse. Jul-Aug 

1995;27(5):19. Comment.

1282. Himali U. ANA sounds alarm about unsafe staffing 

levels: PR campaing sheds light on RN replacement 

trends. Am Nurse. Mar 1995;27(2):1, 7. Comment. 

1283. Hinds PS, Hockenberry-Eaton M, Gilger E, Kline N, 

Burleson C, Bottomley S, Quargnenti A. Comparing 

patient, parent, and staff descriptions of fatigue in 

pediatric oncology patients. Cancer Nurs. Aug 

1999;22(4):277-288; quiz 288-279. Not eligible 

exposure. 

1284. Hines J. Communication problems of hearingimpaired patients. Nurs Stand. Jan 26-Feb 1 

2000;14(19):33-37. Not eligible exposure. 

1285. Hinshaw AS, Scofield R, Atwood JR. Staff, patient, 

and cost outcomes of all-registered nurse staffing. J 

Nurs Adm. Nov-Dec 1981;11(11-12):30-36. Not 

eligible year. 

1286. Hirter J, Van Nest RL. Vigilance: a concept and a 

reality. Crna. May 1995;6(2):96-98. Comment.

1287. Hiscott RD. Changes in employment status: the 

experiences of Ontario registered nurses. Canadian 

Journal of Nursing Research Summer 1994;26(2):43-

60. Not relevant. 

1288. Hiscott RD. Changes in the school-to-work transition 

for Canadian nursing program graduates. Canadian 

Journal of Nursing Research Winter 1995;27(4):151-

63. Not relevant. 

1289. Hiscott RD, Connop PJ. Job turnover among nursing 

professionals: impact of shift length and kinship 

responsibilities. Sociology and Social Research Oct 

1990;75(1):32-7. Not relevant.

1290. Hiscott RD, Sharratt MT, Stewart TO, et al. Research 

examines nurse mobility. Registered Nurse Oct-Nov 

1993;5(5):38-40. Not peer reviewed. 

1291. Hitchings KS. Job sharing: a viable option. Nurs Staff 

Dev Insid. May-Jun 1992;1(3):3, 8. No association 

tested. 

1292. Hodby D. Dollars and sense: the economics and 

outcomes of patients undergoing carotid 

endarterectomy at Royal Adelaide Hospital. J Vasc 

Nurs. Mar 2002;20(1):6-11; quiz 12-13. Not eligible 

target population. 

1293. Hodge MB. The effect of 12 hour shifts on cognition, 

fatigue, and mood in acute care nurses... 34th Annual 

Communicating Nursing Research Conference/15th 

Annual WIN Assembly, "Health Care Challenges 

Beyond 2001: Mapping the Journey for Research and 

Practice," held April 19-21, 2001 in Seattle, 

Washington. Communicating nursing research Spring 

2001;34:296. Conference abstract. 
B-38 

1294. Hodge MB, Asch SM, Olson VA, Kravitz RL, Sauve 

MJ. Developing indicators of nursing quality to 

evaluate nurse staffing ratios. J Nurs Adm. Jun 

2002;32(6):338-345. Not eligible outcomes. 

1295. Hodgson J. Nursing must look after its young. Nurs 

Stand. Oct 18-24 1995;10(4):47. Comment. 

1296. Hodnett ED, Lowe NK, Hannah ME, Willan AR, 

Stevens B, Weston JA, Ohlsson A, Gafni A, Muir 

HA, Myhr TL, Stremler R. Effectiveness of nurses as 

providers of birth labor support in North American 

hospitals: a randomized controlled trial. Jama. Sep 18 

2002;288(11):1373-1381. Not eligible outcomes. 

1297. Hoffart N, Willdermood S. Self-scheduling in five 

med/surg units. A comparison. Nurs Manage. Apr 

1997;28(4):42-45; quiz 426. No association tested. 

1298. Hoffman AJ, Scott LD. Role stress and career 

satisfaction among registered nurses by work shift 

patterns. J Nurs Adm. Jun 2003;33(6):337-342. Not 

eligible outcomes. 

1299. Hoffman LA, Tasota FJ, Zullo TG, Scharfenberg C, 

Donahoe MP. Outcomes of care managed by an acute 

care nurse practitioner/attending physician team in a 

subacute medical intensive care unit. Am J Crit Care. 

Mar 2005;14(2):121-130; quiz 131-122. Not eligible 

exposure. 

1300. Hogan J. Staff ratios in intensive care: are they 

adequate? Br J Nurs. Jul 13-26 2000;9(13):817. Not 

eligible target population. 

1301. Hogan J, Playle JF. The utilization of the healthcare 

assistant role in intensive care. Br J Nurs. Jun 22-Jul 

12 2000;9(12):794-801. Not eligible target 

population. 

1302. Hogan M. Understanding rostering. Part 5. Shiftwork 

and the hierarchy. Aust Nurs J. Jul 1995;3(1):34-36. 

Comment. 

1303. Hogston R. Evaluating quality nursing care through 

peer review and reflection; the findings of a 

qualitative study. Int J Nurs Stud. Apr 

1995;32(2):162-172. Not eligible target population. 

1304. Holdnak BJ, Harsh J, Bushardt SC. An examination 

of leadership style and its relevance to shift work in 

an organizational setting. Health care management 

review Summer 1993;18(3):21-30. Not relevant.

1305. Hollar-Ruegg T. Recruiting nurses from the 

Philippines to combat the nursing shortage in central 

Ohio. Ohio Nurses Rev. Feb 2002;77(2):4. Letter. 

1306. Holle ML. A prescription for success: integrating 12 

inpatient and 17 outpatient programs. Aspens Advis 

Nurse Exec. Jan 1995;10(4):1-3. Comment.

1307. Hollingdale R, Warin J. Back pain in nursing and 

associated factors: a study. Nurs Stand. Jun 18 

1997;11(39):35-38. Not eligible exposure. 

1308. Holloway IM, Smith P, Warren J. Time in hospital. J 

Clin Nurs. Sep 1998;7(5):460-466. Not eligible target 

population. 

1309. Holmas TH. Keeping nurses at work: a duration 

analysis. Health Econ. Sep 2002;11(6):493-503. Not 

eligible target population. 

1310. Holmes L. Theatre nursing (2). Br J Theatre Nurs. 

Oct 1994;4(7):27-28. Comment. 

1311. Holness A, Williams J, Scott E, Bolstad B, McCrary 

P. Shift coordinators dispel myths. Nurs Manage. Oct 

1992;23(10):81-82. Comment. 

1312. Holness DL, Tarlo SM, Sussman G, Nethercott JR. 

Exposure characteristics and cutaneous problems in 

operating room staff. Contact Dermatitis. Jun 

1995;32(6):352-358. Not eligible exposure. 

1313. Holt AW, Bersten AD, Fuller S, Piper RK, Worthley 

LI, Vedig AE. Intensive care costing methodology: 

cost benefit analysis of mask continuous positive 

airway pressure for severe cardiogenic pulmonary 

oedema. Anaesth Intensive Care. Apr 

1994;22(2):170-174. Not eligible target population. 

1314. Holt AW, Bury LK, Bersten AD, Skowronski GA, 

Vedig AE. Prospective evaluation of residents and 

nurses as severity score data collectors. Crit Care 

Med. Dec 1992;20(12):1688-1691. Not eligible target 

population. 

1315. Holtom BC, O'Neill BS. Job embeddedness: a 

theoretical foundation for developing a 

comprehensive nurse retention plan. J Nurs Adm. 

May 2004;34(5):216-227. Not eligible outcomes. 

1316. Holyoake DD. Who's the boss? Children's perception 

of hospital hierarchy. Paediatr Nurs. Jun 

1999;11(5):33-36. Not eligible exposure. 

1317. Homsted L, Nilsson M. Safe staffing: a serious 

concern. Fla Nurse. Mar 2003;51(1):1, 14. Comment. 

1318. Hopia H, Tomlinson PS, Paavilainen E, Astedt-Kurki 

P. Child in hospital: family experiences and 

expectations of how nurses can promote family 

health. J Clin Nurs. Feb 2005;14(2):212-222. Not 

eligible target population. 

1319. Hopkins S. Junior doctors' hours and the expanding 

role of the nurse. Nurs Times. Apr 3-9 

1996;92(14):35-36. Not eligible exposure.

1320. Horner M. A review of a supervised practice 

programme for overseas nurses. Nurs Times. Jul 6-12 

2004;100(27):38-41. Not eligible exposure.

1321. Horns KM, Gills MB. Neonatal nurse knowledge of 

penicillin therapy. Neonatal Netw. Oct 

1998;17(7):52-55. Case Reports. 

1322. Hostetter A, Roda PI, Phillips CY. Heart-smart 

service. Nurs Manage. Jan 2001;32(1):22-25. Not 

eligible exposure. 

1323. Hostutler JJ, Taft SH, Snyder C. Patient needs in the 

emergency department: nurses' and patients' 

perceptions. J Nurs Adm. Jan 1999;29(1):43-50. Not 

eligible exposure. 

1324. Hotchkiss JR, Strike DG, Simonson DA, Broccard 

AF, Crooke PS. An agent-based and spatially explicit 

model of pathogen dissemination in the intensive care 

unit. Crit Care Med. Jan 2005;33(1):168-176; 

discussion 253-164. Not eligible exposure.

1325. Houchins G. Taking a closer look at employee 

turnover in the dialysis unit. Nephrol News Issues. 

Sep 1995;9(9):37-38. Comment. 

1326. Houser BP. The power of collaboration: Arizona's 

best kept secret. Nurs Adm Q. Jul-Sep 

2005;29(3):263-267. Review. 

1327. Houser E. It's all in the mix. Mich Health Hosp. MarApr 2000;36(2):24-26. Comment. 
B-39 

1328. Houser J. A model for evaluating the context of 

nursing care delivery. J Nurs Adm. Jan 

2003;33(1):39-47. Not eligible target population. 

1329. Howell M. Confidentiality during staff reports at the 

bedside. Nurs Times. Aug 24-30 1994;90(34):44-45. 

Not eligible exposure. 

1330. Howenstein MA, Bilodeau K, Brogna MJ, Good G. 

Factors associated with critical thinking among 

nurses. J Contin Educ Nurs. May-Jun 

1996;27(3):100-103. Not eligible outcomes. 

1331. Howse E, Bailey J. Resistance to documentation--a 

nursing research issue. Int J Nurs Stud. Nov 

1992;29(4):371-380. Review. 

1332. Huang PY, Yano EM, Lee ML, Chang BL, 

Rubenstein LV. Variations in nurse practitioner use in 

Veterans Affairs primary care practices. Health Serv 

Res. Aug 2004;39(4 Pt 1):887-904. Not eligible 

exposure. 

1333. Huarng F. A primary shift rotation nurse scheduling 

using zero-one linear goal programming. Comput 

Nurs. May-Jun 1999;17(3):135-144. Not eligible 

target population. 

1334. Huber DA. Staffing issues in the gastroenterology 

setting. Gastroenterol Nurs. Jan-Feb 2005;28(1):43-

44. Editorial. 

1335. Huch MH. Case management: is it another passing 

fad? Nurs Sci Q. Jan 2000;13(1):73-74. Comment. 

1336. Huckabay LM, Tilem-Kessler D. Patterns of parental 

stress in PICU emergency admission. Dimens Crit 

Care Nurs. Mar-Apr 1999;18(2):36-42. Case Reports.

1337. Hudon PS. Leapfrog standards: implications for 

nursing practice. Nurs Econ. Sep-Oct 2003;21(5):233-

236. Review. 

1338. Hudson J, Caruthers TE, Lantiegne K. Intensive care 

nursing requirements: resource allocation according 

to patient status. Crit Care Med. Feb 1979;7(2):69-75. 

Not eligible year. 

1339. Huff C. Workforce. Crossing the U.S. border. Hosp 

Health Netw. Sep 2004;78(9):24, 26. News. 

1340. Hughes KK, Marcantonio RJ. Recruitment, retention, 

and compensation of agency and hospital nurses. J 

Nurs Adm. Oct 1991;21(10):46-52. Not eligible 

outcomes. 

1341. Hughes KK, Marcantonio RJ. The clinical practice of 

supplemental nursing personnel. Nurs Adm Q. Spring 

1993;17(3):83-87. Not eligible outcomes. 

1342. Hughes KK, Young WB. Decision making: stability 

of clinical decisions. Nurse educator May-Jun 

1992;17(3):12-6. Not relevant. 

1343. Hughes R, Stone P. The perils of shift work: evening 

shift, night shift, and rotating shifts: are they for you? 

Am J Nurs. Sep 2004;104(9):60-63. Review.

1344. Humenick SS, Hill PD, Spiegelberg PL. 

Breastfeeding and health professional encouragement. 

J Hum Lact. Dec 1998;14(4):305-310. Not eligible 

exposure. 

1345. Humm C. Night duty: all night long. Nurs Stand. Aug 

17-23 1994;8(47):40. Comment. 

1346. Humm C. A shift in time. Nurs Stand. Jun 12 

1996;10(38):22-24. Comment. 

1347. Hundley VA, Cruickshank FM, Milne JM, Glazener 

CM, Lang GD, Turner M, Blyth D, Mollison J. 

Satisfaction and continuity of care: staff views of care 

in a midwife-managed delivery unit. Midwifery. Dec 

1995;11(4):163-173. Not eligible target population.

1348. Hung R. A cyclical schedule of 10-hour, four-day 

workweeks. Nurs Manage. Sep 1991;22(9):30-33. Not 

eligible outcomes. 

1349. Hung R. A note on nurse self-scheduling. Nurs Econ. 

Jan-Feb 2002;20(1):37-39. Not eligible target 

population. 

1350. Hunt J, Hagen S. Nurse to patient ratios and patient 

outcomes. Nurs Times. Nov 11-17 1998;94(45):63-

66. Not eligible target population.

1351. Hunt JM. The cardiac surgical patient's expectations 

and experiences of nursing care in the intensive care 

unit. Aust Crit Care. Jun 1999;12(2):47-53. Not 

eligible target population. 

1352. Hunter PR, Harrison GA, Fraser CA. Cross-infection 

and diversity of Candida albicans strain carriage in 

patients and nursing staff on an intensive care unit. J 

Med Vet Mycol. 1990;28(4):317-325. Not eligible 

target population. 

1353. Hupcey JE, Penrod J, Morse JM. Establishing and 

maintaining trust during acute care hospitalizations. 

Sch Inq Nurs Pract. Fall 2000;14(3):227-242; 

discussion 243-228. Not eligible exposure. 

1354. Hurst I. Vigilant watching over: mothers' actions to 

safeguard their premature babies in the newborn 

intensive care nursery. J Perinat Neonatal Nurs. Dec 

2001;15(3):39-57. Not eligible exposure. 

1355. Hurst K. Multi-skilled health carers: nature, purpose 

and implications. Health Manpow Manage. 

1997;23(6):197-211. Not eligible target population. 

1356. Hurst K. Relationships between patient dependency, 

nursing workload and quality. Int J Nurs Stud. Jan 

2005;42(1):75-84. Not eligible target population. 

1357. Hwang JL, Desombre T, Eves A, Kipps M. An 

analysis of catering options within NHS acute 

hospitals. Int J Health Care Qual Assur Inc Leadersh 

Health Serv. 1999;12(6-7):293-308. Not eligible 

target population. 

1358. Hydes-Greenwood J, Nellestein I, Leach V. Home 

and away. Successful strategies in recruitment and 

retention of overseas nurses. Nurs Manag (Harrow). 

Sep 2002;9(5):26-29. Not eligible target population.

1359. Iapichino G, Radrizzani D, Bertolini G, Ferla L, 

Pasetti G, Pezzi A, Porta F, Miranda DR. Daily 

classification of the level of care. A method to 

describe clinical course of illness, use of resources 

and quality of intensive care assistance. Intensive 

Care Med. Jan 2001;27(1):131-136. Not eligible 

target population. 

1360. Idel M, Melamed S, Merlob P, Yahav J, Hendel T, 

Kaplan B. Influence of a merger on nurses' emotional 

well-being: the importance of self-efficacy and 

emotional reactivity. J Nurs Manag. Jan 

2003;11(1):59-63. Not eligible target population.

1361. Idelson C. RNs press California to finalize ratios. 

Hospitals step up attack at public hearings. 

Revolution. Nov-Dec 2002;3(6):10-12. News. 
B-40 

1362. Idelson C. Hospital industry still resisting ratios. 

Revolution. Jan-Feb 2004;5(1):6. Comment. 

1363. Idelson C. RNs win court fight, keep ratios. 

Revolution. May-Jun 2005;6(3):8-9. News. 

1364. Idvall E, Hamrin E, Sjostrom B, Unosson M. Patient 

and nurse assessment of quality of care in 

postoperative pain management. Qual Saf Health 

Care. Dec 2002;11(4):327-334. Not eligible target 

population. 

1365. Ikegami A, Niwa A. A study of nurse scheduling in 

Japan. J Hum Ergol (Tokyo). Dec 2001;30(1-2):71-

76. Not eligible target population.

1366. Iliffe J. Campaigning for quality health care. Aust 

Nurs J. May 2000;7(10):1. Editorial.

1367. Ingersoll GL, Brooks AM, Fischer MS, Hoffere DA, 

Lodge RH, Wigsten KS, Costello D, Hartung DA, 

Kiernan ME, Parrinello KM, et al. Professional 

practice model research collaboration. Issues in 

longitudinal, multisite designs. J Nurs Adm. Jan 

1995;25(1):39-46. No association tested. 

1368. Ingersoll GL, Fisher M, Ross B, et al. Employee 

response to major organizational redesign. Applied 

Nursing Research Feb 2001;14(1):18-28. Not 

relevant. 

1369. Innis J, Bikaunieks N, Petryshen P, Zellermeyer V, 

Ciccarelli L. Patient satisfaction and pain 

management: an educational approach. J Nurs Care 

Qual. Oct-Dec 2004;19(4):322-327. Not eligible 

exposure. 

1370. Inwood H. Knowledge of resuscitation. Intensive Crit 

Care Nurs. Feb 1996;12(1):33-39. Not eligible target 

population. 

1371. Irurita VF. Factors affecting the quality of nursing 

care: the patient's perspective. Int J Nurs Pract. Jun 

1999;5(2):86-94. Not eligible target population. 

1372. Irurita VF. The problem of patient vulnerability. 

Collegian. Jan 1999;6(1):10-15. Not eligible target 

population. 

1373. Irurita VF, Williams AM. Balancing and 

compromising: nurses and patients preserving 

integrity of self and each other. Int J Nurs Stud. Oct 

2001;38(5):579-589. Not eligible target population. 

1374. Irving K. Governing the conduct of conduct: are 

restraints inevitable? J Adv Nurs. Nov 

2002;40(4):405-412. Not eligible target population.

1375. Isken MW, Hancock WM. A heuristic approach to 

nurse scheduling in hospital units with non-stationary, 

urgent demand, and a fixed staff size. J Soc Health 

Syst. 1991;2(2):24-41. No association tested. 

1376. Ito H, Nozaki M, Maruyama T, Kaji Y, Tsuda Y. 

Shift work modifies the circadian patterns of heart 

rate variability in nurses. Int J Cardiol. Jul 2001;79(2-

3):231-236. Not eligible target population. 

1377. Itzhaky H, Gerber P, Dekel R. Empowerment, skills, 

and values: a comparative study of nurses and social 

workers. Int J Nurs Stud. May 2004;41(4):447-455. 

Not eligible target population. 

1378. Iverson J, Kirklin S, Becket N, Stone T, Pesanti L. 

Premium pay cuts agency costs. J Nurs Adm. Oct 

1992;22(10):8, 33. Comment. 

1379. Iwata N, Ichii S, Egashira K. Effects of bright 

artificial light on subjective mood of shift work 

nurses. Ind Health. 1997;35(1):41-47. Not eligible 

target population. 

1380. Jabez A. Nursing abroad: a place of extremes. Nurs 

Stand. Apr 21-27 1993;7(31):18-19. Comment.

1381. Jacelon CS. Attitudes and behaviors of hospital staff 

toward elders in an acute care setting. Appl Nurs Res. 

Nov 2002;15(4):227-234. Not eligible exposure.

1382. Jackson A. Improving staffing and quality: a nursing 

support team. Paediatr Nurs. Nov 1999;11(9):22-24. 

Not eligible target population.

1383. Jackson AL, Pokorny ME, Vincent P. Relative 

satisfaction with nursing care of patients with 

ostomies. J ET Nurs. Nov-Dec 1993;20(6):233-238. 

Not eligible exposure. 

1384. Jackson BS, Kasoff J, Casavis L, Hoffmeister R. 

Raising the bar and keeping it there. J Nurs Adm. Mar 

2003;33(3):134-135. Comment. 

1385. Jackson BS, Robley LR, Cortes TA, Annella EJ. How 

far do we go to protect patient welfare? Breaching 

unit staff confidentiality and trust. J Nurs Adm. Jun 

1997;27(6):7-9. Comment. 

1386. Jackson L. Nurs/patient ratio too high. Nursing. Dec 

1991;21(12):6. Letter.

1387. Jackson LB, Marcell J, Benedict S. Nurses' attitudes 

toward parental visitation on the postanesthesia care 

unit. J Perianesth Nurs. Feb 1997;12(1):2-6. Not 

eligible outcomes. 

1388. Jackson M. A preceptor incentive program. Am J 

Nurs. Jun 2001;101(6):24A-24C, 24E. Comment. 

1389. Jackson NV. A survey of part-time faculty in 

baccalaureate schools of nursing and their learning 

needs. Not relevant. 

1390. Jackson TL, Beun L. A prospective study of cost, 

patient satisfaction, and outcome of treatment of 

chalazion by medical and nursing staff. Br J 

Ophthalmol. Jul 2000;84(7):782-785. Not eligible 

target population. 

1391. Jacobs C. How to plan for times of high patient 

census. Nurs Manage. May 2002;33(5):46, 48-51. 

Comment. 

1392. Jacobs L. 'Saint B' gets an A in ratios. Revolution. 

Jan-Feb 2004;5(1):22-26. Comment.

1393. Jacobsen C, Holson D, Farley J, Charles J, Suel P. 

Surviving the perfect storm: staff perceptions of 

mandatory overtime. JONAS Healthc Law Ethics 

Regul. Sep 2002;4(3):57-66. Not eligible exposure. 

1394. Jacobson AK, Seltzer JE, Dam EJ. New methodology 

for analyzing fluctuating unit activity. Nurs Econ. 

Jan-Feb 1999;17(1):55-59. Not eligible outcomes.

1395 Jacobson SF, Jordan KF. Nurses' reasons for 

participating in a longitudinal panel survey. West J 

Nurs Res. Aug 1993;15(4):509-515. Not eligible 

outcomes. 

1396. Jaklevic MC. Law allows some hiring of foreign 

nurses. Mod Healthc. Nov 29 1999;29(48):38. News.

1397. Jakob SM, Rothen HU. Intensive care 1980-1995: 

change in patient characteristics, nursing workload 

and outcome. Intensive Care Med. Nov 

1997;23(11):1165-1170. Not eligible target 

population. 
B-41 

1398. James DV, Fineberg NA, Shah AK, Priest RG. An 

increase in violence on an acute psychiatric ward. A 

study of associated factors. Br J Psychiatry. Jun 

1990;156:846-852. Not eligible target population.

1399. James G. Nursing precious resources. Health Serv J. 

May 16 1991;101(5252):24-25. Not eligible target 

population. 

1400. Jannotta M, Maldonado T. Self-management for 

nurses. J Nurs Adm. Jun 1992;22(6):59-63. No 

association tested. 

1401. Janssen PA, Keen L, Soolsma J, Seymour LC, Harris 

SJ, Klein MC, Reime B. Perinatal nursing education 

for single-room maternity care: an evaluation of a 

competency-based model. J Clin Nurs. Jan 

2005;14(1):95-101. Not eligible exposure. 

1402. Jarman H, Jacobs E, Zielinski V. Medication study 

supports registered nurses' competence for single 

checking. Int J Nurs Pract. Dec 2002;8(6):330-335. 

Not eligible target population. 

1403. Jarvi M, Uusitalo T. Job rotation in nursing: a study 

of job rotation among nursing personnel from the 

literature and via a questionnaire. J Nurs Manag. Sep 

2004;12(5):337-347. Not eligible target population.

1404. Jarvis LA, Beale B, Martin K. A client-centered 

model: discharge planning in Juvenile Justice Centres 

in New South Wales, Australia. Int Nurs Rev. Sep 

2000;47(3):184-190. Not eligible target population. 

1405. Jarvis R, Young SW, Hardy P, Ward S. 

Implementation of a patient classification system: 

using current resources to achieve organizational 

goals. Health Care Superv. Sep 1991;10(1):51-57. No 

association tested. 

1406. Jaworski Miller L, Corbett G, Herold M, Tavares D, 

Kirchner L, Heath J. Journey to the Beacon Award: 

the Georgetown University Hospital perspective. Crit 

Care Nurs Clin North Am. Jun 2005;17(2):155-161, 

x. Review.

1407. Jeang A. Flexible nursing staff planning when patient 

demands are uncertain. J Med Syst. Jun 

1994;18(3):125-138. Not eligible target population. 

1408. Jeang A. Flexible nursing staff planning with 

adjustable patient demands. J Med Syst. Aug 

1996;20(4):173-182. Not eligible target population. 

1409. Jeffe DB, Dunagan WC, Garbutt J, Burroughs TE, 

Gallagher TH, Hill PR, Harris CB, Bommarito K, 

Fraser VJ. Using focus groups to understand 

physicians' and nurses' perspectives on error reporting 

in hospitals. Jt Comm J Qual Saf. Sep 

2004;30(9):471-479. Not eligible exposure.

1410. Jenkins CG. (Relatively) painless downsizing. MLO 

Med Lab Obs. Mar 1996;28(3):36-39. Comment. 

1411. Jenkins LS, George V. Heart Watch: national survey 

of continuous electrocardiographic monitoring in U.S. 

hospitals. J Nurs Adm. Apr 1995;25(4):38-44. Not 

eligible exposure. 

1412. Jenkins R, Elliott P. Stressors, burnout and social 

support: nurses in acute mental health settings. J Adv 

Nurs. Dec 2004;48(6):622-631. Not eligible target 

population. 

1413. Jennings BM. The role of research in the policy 

puzzle: nurse staffing research as a case in point. Res 

Nurs Health. Dec 2001;24(6):443-445. Editorial.

1414. Jennings BM, Loan LA, DePaul D, Brosch LR, 

Hildreth P. Lessons learned while collecting ANA 

indicator data. J Nurs Adm. Mar 2001;31(3):121-129. 

Review. 

1415. Jensen L. Self-administered cardiac medication 

program evaluation. Can J Cardiovasc Nurs. 

2003;13(2):35-44. Not eligible target population.

1416. Jeppesen HJ, Boggild H. Management of health and 

safety in the organization of worktime at the local 

level. Scand J Work Environ Health. 1998;24 Suppl 

3:81-87. Not eligible target population.

1417. Jerant AF, Azari R, Martinez C, Nesbitt TS. A 

randomized trial of telenursing to reduce 

hospitalization for heart failure: patient-centered 

outcomes and nursing indicators. Home Health Care 

Serv Q. 2003;22(1):1-20. Not eligible exposure.

1418. Jette DU, Warren RL, Wirtalla C. Rehabilitation in 

skilled nursing facilities: effect of nursing staff level 

and therapy intensity on outcomes. Am J Phys Med 

Rehabil. Sep 2004;83(9):704-712. Not eligible target 

population. 

1419. Jevitt CM, Beckstead JW. Retirement among 

Florida's certified nurse-midwives: an impending 

workforce crisis. Journal of midwifery & women's 

health Jan-Feb 2004;49(1):39-46. Not relevant.

1420. Jickling JL, Graydon JE. The information needs at 

time of hospital discharge of male and female patients 

who have undergone coronary artery bypass grafting: 

a pilot study. Heart Lung. Sep-Oct 1997;26(5):350-

357. Not eligible exposure.

1421. Jinks A, Smith M, Ashdown-Lambert J. The public 

health roles of health visitors and school nurses: a 

survey. Br J Community Nurs. Nov 2003;8(11):496-

501. Not eligible target population. 

1422. Johanson W. Nurse staffing. Health Aff (Millwood). 

Jan-Feb 2003;22(1):281; author reply 281-282. 

Comment. 

1423. Johansson P, Oleni M, Fridlund B. Nurses' 

assessments and patients' perceptions: development of 

the Night Nursing Care Instrument (NNCI), 

measuring nursing care at night. Int J Nurs Stud. Jul 

2005;42(5):569-578. Not eligible target population. 

1424. Johnson DE. Hospitals can control patient days to 

stem nurse demand. Health Care Strateg Manage. Jul 

2001;19(7):1, 18-19. Comment. 

1425. Johnson DE. Leapfrog's report is incomplete, 

misleading. Health Care Strateg Manage. Feb 

2002;20(2):2-3. Review. 

1426. Johnson DE. How severe is the nurse shortage? 

Health Care Strateg Manage. Jan 2003;21(1):2-3. 

Comment. 

1427. Johnson F, Smithson S. International recruitment. 

Travellers' checks. Health Serv J. Jul 4 

2002;112(5812):25. News. 

1428. Johnson J, Brown KK, Neal K. Designs that make a 

difference: the Cardiac Universal Bed model. J 

Cardiovasc Manag. Sep-Oct 2003;14(5):16-20. No 

association tested. 

1429. Johnson JE. Management perspectives. I am a nursing 

executive in an institution whose goal is to change its 

culture to become more customer oriented. Nurs 

Spectr (Wash D C). Aug 7 1995;5(16):5. Comment. 
B-42 

1430. Johnson LJ. Your liability for a nurse's mistake. Med 

Econ. Sep 9 2002;79(17):115. Comment. 

1431. Johnson M, Stewart H, Langdon R, Kelly P, Yong L. 

Women-centred care and caseload models of 

midwifery. Collegian. Jan 2003;10(1):30-34. Not 

eligible target population. 

1432. Johnson N. Congressional outlook: nursing shortages. 

Hosp Outlook. Feb 2001;4(2):7. Comment.

1433. Johnson SH. The right balance. Dimens Crit Care 

Nurs. Jan-Feb 1996;15(1):2-3. Editorial.

1434. Johnson SH. Coping with census fluctuations. Nurs 

Manage. Oct 1998;29(10):48L. Comment. 

1435. Johnston CL. Changing care patterns and registered 

nurse job satisfaction. Holist Nurs Pract. Apr 

1997;11(3):69-77. Review.

1436. Johnstone L. Mental health. In the same boat? Nurs 

Times. Jul 7-13 1993;89(27):30-31. Comment.

1437. Jolley S. Promoting teenage sexual health: an 

investigation into the knowledge, activities and 

perceptions of gynaecology nurses. J Adv Nurs. Oct 

2001;36(2):246-255. Not eligible target population. 

1438. Jones A. Perceptions on individualized approaches to 

mental health care. J Psychiatr Ment Health Nurs. 

Aug 2005;12(4):396-404. Not eligible target 

population. 

1439. Jones CB. The costs of nurse turnover, part 2: 

application of the Nursing Turnover Cost Calculation 

Methodology. J Nurs Adm. Jan 2005;35(1):41-49. 

Not eligible outcomes.

1440. Jones D. I am that agency nurse. Accid Emerg Nurs. 

Jan 1998;6(1):51-52. Comment. 

1441. Jones GJ, Vanderpump MP, Easton M, Baker DM, 

Ball C, Leenane M, O'Brien H, Turner N, Else M, 

Reid WM, Johnson M. Achieving compliance with 

the European Working Time Directive in a large 

teaching hospital: a strategic approach. Clin Med. 

Sep-Oct 2004;4(5):427-430. Not eligible target 

population. 

1442. Jones HE, Cleave B, Zinman B, Szalai JP, Nichol HL, 

Hoffman BR. Efficacy of feedback from quarterly 

laboratory comparison in maintaining quality of a 

hospital capillary blood glucose monitoring program. 

Diabetes Care. Feb 1996;19(2):168-170. Not eligible 

exposure. 

1443. Jones IH. Night moves. Nurs Times. May 2-8 

1990;86(18):21. Comment. 

1444. Jones J, Black N, Sanderson C. Levels of nurse 

staffing. Sr Nurse. Jan-Feb 1993;13(1):20-24. 

Comment.

1445. Jones J, Ward M, Wellman N, Hall J, Lowe T. 

Psychiatric inpatients' experience of nursing 

observation. A United Kingdom perspective. J 

Psychosoc Nurs Ment Health Serv. Dec 

2000;38(12):10-20. Not eligible target population.

1446. Jones JS, Holstege CP, Riekse R, White L, Bergquist 

T. Metered-dose inhalers: do emergency health care 

providers know what to teach? Ann Emerg Med. Sep 

1995;26(3):308-311. Not eligible exposure.

1447. Jones K, Yancer DA, McGinley SJ, Galbraith P. An 

agency-staffed nursing unit project. Nurs Manage. 

Oct 1990;21(10):36-37, 40. No association tested. 

1448. Jones M. Stress and burnout in nursing: causes and 

prevention. Okla Nurse. Apr-Jun 1996;41(2):20-21. 

Comment. 

1449. Jones S. Managing pain using the partnership model 

of care. Paediatr Nurs. Feb 1995;7(1):21-24. No 

association tested. 

1450. Jordan C, Tabone S. Mandatory overtime and on call: 

growing concerns for nurses. Tex Nurs. Sep 

2000;74(8):4-6. Comment.

1451. Jordan CB. Nurse staffing: are the answers emerging? 

Tex Nurs. May 2000;74(5):4-5, 15. Comment.

1452. Jordan CB. Preparing for the 2001 Texas Legislative 

session. Nurse staffing. What's adequate? What's 

safe? Tex Nurs. Feb 2000;74(2):4-5, 10. Comment. 

1453. Jorde R, Nordoy A. Improvement in clinical work 

through feedback: intervention study. Bmj. Jun 26 

1999;318(7200):1738-1739. Not eligible target 

population. 

1454. Joseph HJ. Attitudes and cultural self-efficacy levels 

of nurses caring for patients in army hospitals. J Natl 

Black Nurses Assoc. Jul 2004;15(1):5-16. Not eligible 

target population. 

1455. Jung FD, Pearcey LG, Phillips JL. Evaluation of a 

program to improve nursing assistant use. J Nurs 

Adm. Mar 1994;24(3):42-47. Not eligible exposure. 

1456. Junger A, Brenck F, Hartmann B, Klasen J, Quinzio 

L, Benson M, Michel A, Rohrig R, Hempelmann G. 

Automatic calculation of the nine equivalents of 

nursing manpower use score (NEMS) using a patient 

data management system. Intensive Care Med. Jul 

2004;30(7):1487-1490. Not eligible target population. 

1457. Kafkia T, Kourakos M, Lagkazali B, Eleftheroudi M, 

Tsougia P, Doula M, Laskari A, Thanassa G, De Vos 

JY, Elseviers M. European practice database: results 

from Greece. Edtna Erca J. Jan-Mar 2005;31(1):43-

48. Not eligible target population. 

1458. Kageyama T, Kobayashi T, Nishikido N, Oga J, 

Kawashima M. Associations of sleep problems and 

recent life events with smoking behaviors among 

female staff nurses in Japanese hospitals. Ind Health. 

Jan 2005;43(1):133-141. Not eligible target 

population. 

1459. Kageyama T, Nishikido N, Kobayashi T, Oga J, 

Kawashima M. Cross-sectional survey on risk factors 

for insomnia in Japanese female hospital nurses 

working rapidly rotating shift systems. J Hum Ergol 

(Tokyo). Dec 2001;30(1-2):149-154. Not eligible 

target population. 

1460. Kaissi A, Johnson T, Kirschbaum MS. Measuring 

teamwork and patient safety attitudes of high-risk 

areas. Nurs Econ. Sep-Oct 2003;21(5):211-218, 207. 

Not eligible exposure. 

1461. Kamineni S, Higgins A, Edmunds C. Specialist 

surgical nursing assistant. Br J Hosp Med. Feb 5-18 

1997;57(3):112. Letter. 

1462. Kandolin I, Huida O. Individual flexibility: an 

essential prerequisite in arranging shift schedules for 

midwives. J Nurs Manag. Jul 1996;4(4):213-217. Not 

eligible target population. 

1463. Kane D. Job sharing as a part-time employment 

alternative. J Nurs Adm. Mar 1995;25(3):5, 33. 

Comment.
B-43 

1464. Kane D. Job sharing: a retention strategy for nurses. 

Can J Nurs Leadersh. Nov-Dec 1999;12(4):16-22. 

Not eligible exposure.

1465. Kane-Urrabazo C. Should you dive into that float 

assignment? Nursing. Jun 2004;34(6):64. Comment. 

1466. Kangas S, Kee CC, McKee-Waddle R. Organizational 

factors, nurses' job satisfaction, and patient 

satisfaction with nursing care. J Nurs Adm. Jan 

1999;29(1):32-42. Not eligible exposure. 

1467. Kanji Z. Implementation of a sedation and analgesia 

scale. J Nurs Care Qual. Jan-Mar 2005;20(1):13-15. 

Not eligible exposure. 

1468. Kany K. How can nurses combat mandatory 

overtime? Am J Nurs. Aug 1999;99(8):77. Comment. 

1469. Kany K. Combating staffing problems. Am J Nurs. 

Apr 1999;99(4):68. Comment.

1470. Kany K. Policy vs. reality. Am J Nurs. May 

2001;101(5):87. Comment.

1471. Kaplan M. Hospital caregivers are in a bad mood. Am 

J Nurs. Mar 2000;100(3):25. Comment.

1472. Kaplow R. AACN Synergy Model for Patient Care: a 

framework to optimize outcomes. Crit Care Nurse. 

Feb 2003;Suppl:27-30. Review.

1473. Kaprowy J, Schilder E. Restraint or martial arts: 

should nurses tie people down? Ky Hosp Mag. Winter 

1991;8(1):12-16. Comment. 

1474. Karadeniz G, Cakmakci A. Nurses' perceptions of 

medication errors. Int J Clin Pharmacol Res. 

2002;22(3-4):111-116. Not eligible target population.

1475. Karas C. RN staffing is key. Hosp Health Netw. Aug 

2001;75(8):16. Comment. 

1476. Karch AM, Karch FE. What did you say? I can't quite 

understand your spoken order. Am J Nurs. Aug 

1999;99(8):12. Case Reports.

1477. Karch AM, Karch FE. The naked decimal point. And 

eight other common errors that can be avoided. Am J 

Nurs. Dec 2001;101(12):22. Case Reports. 

1478. Kardos L, Szeles G, Gombkoto G, Szeremi M, 

Tompa A, Adany R. Cancer deaths among hospital 

staff potentially exposed to ethylene oxide: an 

epidemiological analysis. Environ Mol Mutagen. 

2003;42(1):59-60. Not eligible target population. 

1479. Karkkainen O, Eriksson K. Recording the content of 

the caring process. J Nurs Manag. May 

2005;13(3):202-208. Not eligible target population. 

1480. Karlowicz MG, McMurray JL. Comparison of 

neonatal nurse practitioners' and pediatric residents' 

care of extremely low-birth-weight infants. Arch 

Pediatr Adolesc Med. Nov 2000;154(11):1123-1126. 

Not eligible exposure. 

1481. Kater V, Braverman N, Chuwers P. Would provision 

of childcare for nurses with young children ensure 

response to a call-up during a wartime disaster? An 

Israeli hospital nursing survey. Public Health Rev. 

1992;20(3-4):313-316. Not eligible exposure.

1482. Kauffmann E, Harrison MB, Burke SO, Wong C. 

Stress-point intervention for parents of children 

hospitalized with chronic conditions. Pediatr Nurs. 

Jul-Aug 1998;24(4):362-366. Not eligible exposure. 

1483. Kautzman L, Miller LH. Growing replacements for 

our 'graying' perioperative nurses. Todays Surg 

Nurse. Mar-Apr 1999;21(2):22-25. Comment. 

1484. Kavanaugh K, Engstrom JL, Meier PP, Lysakowski 

TY. How reliable are scales for weighing preterm 

infants? Neonatal Netw. Oct 1990;9(3):29-32. Not 

eligible exposure. 

1485. Kawik L. Nurses' and parents' perceptions of 

participation and partnership in caring for a 

hospitalized child. Br J Nurs. Apr 11-24 

1996;5(7):430-437. Not eligible target population.

1486. Kaya S, Vural G, Eroglu K, Sain G, Mersin H, 

Karabeyoglu M, Sezer K, Turkkani B, Restuccia JD. 

Liability and validity of the Appropriateness 

Evaluation Protocol in Turkey. Int J Qual Health 

Care. Aug 2000;12(4):325-329. Not eligible target 

population. 

1487. Kaye W, Mancini ME, Giuliano KK, Richards N, 

Nagid DM, Marler CA, Sawyer-Silva S. 

Strengthening the in-hospital chain of survival with 

rapid defibrillation by first responders using 

automated external defibrillators: training and 

retention issues. Ann Emerg Med. Feb 

1995;25(2):163-168. Not eligible exposure.

1488. Kayuha AA. Acclimating to shift work--a survival kit. 

Healthc Trends Transit. Apr 1990;1(5):18, 20, 22-15. 

No association tested. 

1489. Keatinge D, Gilmore V. Shared care: a partnership 

between parents and nurses. Aust J Adv Nurs. SepNov 1996;14(1):28-36. Not eligible target population.

1490. Keddy B, Gregor F, Foster S, et al. Theorizing about 

nurses' work lives: the personal and professional 

aftermath of living with healthcare 'reform'. Nursing 

inquiry Mar 1999;6(1):58-64. Not relevant. 

1491. Keenan GM, Cooke R, Hillis SL. Norms and nurse 

management of conflicts: keys to understanding 

nurse-physician collaboration. Res Nurs Health. Feb 

1998;21(1):59-72. Not eligible exposure. 

1492. Keim J, Robinson S. Work environment factors 

influencing burnout among third shift nurses. J Nurs 

Adm. Nov 1992;22(11):52, 56. Comment. 

1493. Keller KL. The management of stress and prevention 

of burnout in emergency nurses. J Emerg Nurs. MarApr 1990;16(2):90-95. Not eligible exposure.

1494. Keller LO, Strohschein S, Lia-Hoagberg B, Schaffer 

M. Population-based public health nursing 

interventions: a model from practice. Public Health 

Nurs. Jun 1998;15(3):207-215. Not eligible exposure. 

1495. Kellett J. Taking the blame. Nurs Stand. Dec 11 

1996;11(12):21-23. Not eligible target population. 

1496. Kelley LS, Swanson E, Maas ML, Tripp-Reimer T. 

Family visitation on special care units. J Gerontol 

Nurs. Feb 1999;25(2):14-21. Not eligible exposure. 

1497. Kelly AM. Nurse-managed analgesia for renal colic 

pain in the emergency department. Aust Health Rev. 

2000;23(2):185-189. Not eligible target population.

1498. Kelly AM, Miljesic S, Mant P, Ashton W. Plaster 

checks by nurses: safe and efficient? Accid Emerg 

Nurs. Apr 1996;4(2):76-77. Not eligible exposure. 

1499. Kelly B. Hospital nursing: 'it's a battle!' A follow-up 

study of English graduate nurses. J Adv Nurs. Nov 

1996;24(5):1063-1069. No association tested. 
B-44 

1500. Kelly M, Williams C, Murdoch I. Comparison of 

costing tools in paediatric intensive care. Paediatr 

Nurs. Nov 1999;11(9):14-16. Not eligible target 

population. 

1501. Kelly TM, Donovan K. Cardiac rehabilitation in the 

time of health-care reform. AACN Clin Issues. Aug 

1995;6(3):432-442. Not eligible exposure. 

1502. Kemper KJ, Benson MS, Bishop MJ. Interobserver 

variability in assessing pediatric postextubation 

stridor. Clin Pediatr (Phila). Jul 1992;31(7):405-408. 

Not eligible exposure. 

1503. Kemppainen JK, Dubbert PM, McWilliams P. Effects 

of group discussion and guided patient care 

experience on nurses' attitudes towards care of 

patients with AIDS. J Adv Nurs. Aug 

1996;24(2):296-302. Not eligible target population.

1504. Kendig EL, Jr., Kirkpatrick BV, Carter WH, Hill FA, 

Caldwell K, Entwistle M. Underreading of the 

tuberculin skin test reaction. Chest. May 

1998;113(5):1175-1177. Not eligible exposure. 

1505. Kenney PA. Maintaining quality care during a 

nursing shortage using licensed practical nurses in 

acute care. J Nurs Care Qual. Jul 2001;15(4):60-68. 

Not eligible exposure. 

1506. Kenny MF, Gapas J, Hilton G. Cross utilization in 

critical care. Nurs Manage. May 1995;26(5):48D, 

48F-48I. No association tested.

1507. Kenny P, King MT, Cameron S, Shiell A. Satisfaction 

with postnatal care--the choice of home or hospital. 

Midwifery. Sep 1993;9(3):146-153. Not eligible 

exposure. 

1508. Keogh A, Dealey C. Profiling beds versus standard 

hospital beds: effects on pressure ulcer incidence 

outcomes. J Wound Care. Feb 2001;10(2):15-19. Not 

eligible exposure. 

1509. Kercher LL. Appropriate staffing: our right, our 

responsibility. Nurs Manage. Feb 1999;30(2):4. 

Editorial.

1510. Kerfoot KM, Cox M. The synergy model: the 

ultimate mentoring model. Crit Care Nurs Clin North 

Am. Jun 2005;17(2):109-112, ix. Comment. 

1511. Kern D, Kettner P, Albrizio M. An exploration of the 

variables involved when instituting a do-notresuscitate order for patients undergoing bone marrow 

transplantation. Oncol Nurs Forum. May 

1992;19(4):635-640. Not eligible exposure. 

1512. Kerr MP. A qualitative study of shift handover 

practice and function from a socio-technical 

perspective. J Adv Nurs. Jan 2002;37(2):125-134. Not 

eligible target population. 

1513. Kester-Beaver P. Tales from travelers. Am J Nurs. 

Apr 1991;91(4):50-56. Comment. 

1514. Ketter J. Have you worked through lunch lately? Fair 

Labor Standards Act protectsRNs against wage abuse. 

Am Nurse. Jul-Aug 1995;27(5):14. Comment. 

1515. Ketter J. ANA and SNAs tackle hospital 

restructuring. Am Nurse. Mar 1995;27(2):8, 18. 

Comment. 

1516. Khan ZU, Chandy R, Metwali KE. Candida albicans 

strain carriage in patients and nursing staff of an 

intensive care unit: a study of morphotypes and 

resistotypes. Mycoses. Dec 2003;46(11-12):479-486. 

Not eligible target population.

1517. Kidner MC. How to keep float nurses from sinking. 

Rn. Sep 1999;62(9):35-39. Comment.

1518. Kiekkas P, Poulopoulou M, Papahatzi A, 

Androutsopoulou C, Maliouki M, Prinou A. 

Workload of postanaesthesia care unit nurses and 

intensive care overflow. Br J Nurs. Apr 28-May 11 

2005;14(8):434-438. Not eligible target population. 

1519. Killeen MB. A system with many methods to adjust 

staffing. Mich Nurse. Sep 2004:13-15. Comment. 

1520. Kinard J, Little B. Are hospitals facing a critical 

shortage of skilled workers? Health Care Superv. Jun 

1999;17(4):54-62. No association tested. 

1521. King LA, Wasdovich A, Young C. Transforming 

nursing practice: clinical systems and the nursing unit 

of the future. J Healthc Inf Manag. Summer 

2004;18(3):32-36. Not eligible exposure. 

1522. King RB, Shaw K, Adams JG. ED overcrowdingmeeting many needs. Pediatr Emerg Care. Oct 

2004;20(10):710-716. Interview.

1523. King S. Goodbye Holladay Park. Oreg Nurse. Sep 

1994;59(3):3. Comment.

1524. King S. Hospital nurse staffing--the public's interest. 

Oreg Nurse. Sep 1999;64(3):3. Comment. 

1525. King S. Safe staffing levels for children's wards. 

Paediatr Nurs. Mar 2000;12(2):28-31. No association 

tested. 

1526. King S. Hospital staffing law effective Oct. 1. Oreg 

Nurse. Sep 2002;67(3):1, 8. Legal Cases. 

1527. Kinley H, Czoski-Murray C, George S, McCabe C, 

Primrose J, Reilly C, Wood R, Nicolson P, Healy C, 

Read S, Norman J, Janke E, Alhameed H, Fernandes 

N, Thomas E. Effectiveness of appropriately trained 

nurses in preoperative assessment: randomised 

controlled equivalence/non-inferiority trial. Bmj. Dec 

7 2002;325(7376):1323. Not eligible target 

population. 

1528. Kinley H, Czoski-Murray C, George S, McCabe C, 

Primrose J, Reilly C, Wood R, Nicolson P, Healy C, 

Read S, Norman J, Janke E, Alhameed H, Fernandez 

N, Thomas E. Extended scope of nursing practice: a 

multicentre randomised controlled trial of 

appropriately trained nurses and pre-registration 

house officers in pre-operative assessment in elective 

general surgery. Health Technol Assess. 

2001;5(20):1-87. Not eligible target population. 

1529. Kinn S, Scott J. Nutritional awareness of critically ill 

surgical high-dependency patients. Br J Nurs. Jun 14-

27 2001;10(11):704-709. Not eligible target 

population. 

1530. Kinney M. Flexible scheduling and part-time work: 

what price do we pay? Focus Crit Care. Dec 

1990;17(6):439. Editorial. 

1531. Kinrade S. Acting against discrimination. Prof Nurse. 

Aug 2003;18(12):714-715. Not eligible target 

population. 
B-45 

1532. Kirby KK, Garfink CM. The University Hospital 

Nurse Extender Model. Part I, An overview and 

conceptual framework. J Nurs Adm. Jan 

1991;21(1):25-30. Not eligible target population.

1533. Kirchhoff KT, Beckstrand RL. Critical care nurses' 

perceptions of obstacles and helpful behaviors in 

providing end-of-life care to dying patients. Am J Crit 

Care. Mar 2000;9(2):96-105. Not eligible exposure. 

1534 .Kirchhoff KT, Mateo MA. Roles and responsibilities 

of clinical nurse researchers. J Prof Nurs. Mar-Apr 

1996;12(2):86-90. Not eligible exposure. 

1535. Kirkhart DG. Shared care: improving health care, 

reducing costs. Nurs Manage. Jun 1995;26(6):26, 28, 

30 passim. Not eligible exposure. 

1536. Kirsch E, Talbott J. Outpatient and short-stay patient 

classification systems. Nurs Manage. Sep 

1990;21(9):118-119, 122. No association tested. 

1537. Kitajima T, Ohida T, Harano S, Kamal AM, 

Takemura S, Nozaki N, Kawahara K, Minaowa M. 

Smoking behavior, initiating and cessation factors 

among Japanese nurses: a cohort study. Public Health. 

Nov 2002;116(6):347-352. Not eligible target 

population. 

1538. Kivimaki M, Makinen A, Elovainio M, Vahtera J, 

Virtanen M, Firth-Cozens J. Sickness absence and the 

organization of nursing care among hospital nurses. 

Scand J Work Environ Health. Dec 2004;30(6):468-

476; quiz 476. Not eligible target population.

1539. Kjellberg K, Lagerstrom M, Hagberg M. Patient 

safety and comfort during transfers in relation to 

nurses' work technique. J Adv Nurs. Aug 

2004;47(3):251-259. Not eligible target population. 

1540. Kleinbeck SV, McKennett M. Challenges of 

measuring intraoperative patient outcomes. Aorn J. 

Nov 2000;72(5):845-850, 853. No association tested. 

1541. Kleinman C. The relationship between managerial 

leadership behaviors and staff nurse retention. Hosp 

Top. Fall 2004;82(4):2-9. Not eligible outcomes.

1542. Kluska KM, Laschinger HK, Kerr MS. Staff nurse 

empowerment and effort-reward imbalance. Can J 

Nurs Leadersh. Mar 2004;17(1):112-128. Not eligible 

exposure. 

1543. Knight P, Cassady G. Control of infection due to 

Klebsiella pneumoniae in an intensive care nursery. J 

Perinatol. Dec 1990;10(4):357-360. Not eligible 

exposure. 

1544. Kobylus K. Innovations, local solutions arise from the 

shortage. Healthtexas. Mar 1991;46(9):15-16. 

comment. 

1545. Koch F. Staffing outcomes: skill mix changes. Semin 

Perioper Nurs. Jan 1996;5(1):32-35. No association 

tested. 

1546. Koenig HG, Bearon LB, Hover M, Travis JL, 3rd. 

Religious perspectives of doctors, nurses, patients, 

and families. J Pastoral Care. Fall 1991;45(3):254-

267. Not eligible exposure. 

1547. Koivisto K, Janhonen S, Vaisanen L. Patients' 

experiences of being helped in an inpatient setting. J 

Psychiatr Ment Health Nurs. Jun 2004;11(3):268-275. 

Not eligible target population. 

1548. Koivula M, Paunonen M, Laippala P. Prerequisites 

for quality improvement in nursing. J Nurs Manag. 

Nov 1998;6(6):333-342. Not eligible target 

population. 

1549. Kollee I, Pearson E. Hemodialysis teaching protocols: 

an educational tool for both patients and nurses. 

Cannt J. Apr-Jun 2000;10(2):26-29. Not eligible 

exposure. 

1550. Kollef MH, Shapiro SD, Silver P, St John RE, 

Prentice D, Sauer S, Ahrens TS, Shannon W, BakerClinkscale D. A randomized, controlled trial of 

protocol-directed versus physician-directed weaning 

from mechanical ventilation. Crit Care Med. Apr 

1997;25(4):567-574. Not eligible exposure. 

1551. Koncar DR. A day in the life ... sudden shifts. Debbie 

Cuaresma, RN cardiac nurse. Revolution. Nov-Dec 

2001;2(6):18-21. Interview. 

1552. Kooijman CJ, Klaassen-Leil CC. Extraction, 

preparation, and presentation of patient classificationdata for the benefit of management overviews. 

Medinfo. 1995;8 Pt 2:1382-1385. Not eligible target 

population. 

1553. Korst LM, EusebioAngeja AC, Chamorro T, et al. 

Nursing documentation time during implementation 

of an electronic medical record. Journal of Nursing 

Administration Jan 2003;33(1):24-30. Not relevant. 

1554. Kosgeroglu N, Ayranci U, Vardareli E, Dincer S. 

Occupational exposure to hepatitis infection among 

Turkish nurses: frequency of needle exposure, sharps 

injuries and vaccination. Epidemiol Infect. Jan 

2004;132(1):27-33. Not eligible target population. 

1555. Kosowsky JM, Shindel S, Liu T, Hamilton C, 

Pancioli AM. Can emergency department triage 

nurses predict patients' dispositions? Am J Emerg 

Med. Jan 2001;19(1):10-14. Not eligible exposure. 

1556. Kovner C, Stave CM, Lavelle K, et al. An analysis of 

vacancy rates, turnover, and wages among nursing 

occupations in New York state hospitals, nursing 

homes, and diagnostic and treatment facilities. 

Journal of the New York State Nurses Association 

Sep 1994;25(3):20-7. Not peer reviewed. 

1557. Kovner CT. State regulation of RN-to-patient ratios. 

Am J Nurs. Nov 2000;100(11):61-63, 65. Review. 

1558. Kovner CT, Harrington C. The changing picture of 

hospital nurses. Am J Nurs. May 2002;102(5):93-94. 

Review.

1559. Kramer M, Schmalenberg C. Job satisfaction and 

retention. Insights for the '90s. Part 2. Nursing. Apr 

1991;21(4):51-55. Not eligible exposure. 

1560. Kramer M, Schmalenberg C. Development and 

evaluation of essentials of magnetism tool. J Nurs 

Adm. Jul-Aug 2004;34(7-8):365-378. Not eligible 

exposure. 

1561. Kramer M, Schmalenberg C. Revising the Essentials 

of Magnetism tool: there is more to adequate staffing 

than numbers. J Nurs Adm. Apr 2005;35(4):188-198. 

Not eligible exposure. 

1562. Kramer M, Schmalenberg C, Maguire P. Essentials of 

a magnetic work environment: part 3. Nursing. Aug 

2004;34(8):44-47. Not eligible exposure. 
B-46 

1563. Kreplick J. Unlicensed hospital assistive personnel: 

efficiency or liability? J Health Hosp Law. Sep-Oct 

1995;28(5):292-309. Review. 

1564. Krishnasamy M. What do cancer patients identify as 

supportive and unsupportive behaviour of nurses? A 

pilot study. Eur J Cancer Care (Engl). Jun 

1996;5(2):103-110. Not eligible exposure. 

1565. Kristensson-Hallstrom I. Strategies for feeling secure 

influence parents' participation in care. J Clin Nurs. 

Sep 1999;8(5):586-592. Not eligible target 

population. 

1566. Kromhout H, Hoek F, Uitterhoeve R, Huijbers R, 

Overmars RF, Anzion R, Vermeulen R. Postulating a 

dermal pathway for exposure to anti-neoplastic drugs 

among hospital workers. Applying a conceptual 

model to the results of three workplace surveys. Ann 

Occup Hyg. Oct 2000;44(7):551-560. Not eligible 

target population. 

1567. Kroposki M, Murdaugh CL, Tavakoli AS, Parsons M. 

Role clarity, organizational commitment, and job 

satisfaction during hospital reengineering. 

Nursingconnections. Spring 1999;12(1):27-34. Not 

eligible exposure. 

1568. Krugman M, Smith V. Charge nurse leadership 

development and evaluation. J Nurs Adm. May 

2003;33(5):284-292. Not eligible exposure. 

1569. Ksykiewicz-Dorota A. Development of nursing time 

standards as a problem of optimalisation of health 

care system management. II. Comparative analysis of 

demand for nursing care. Ann Univ Mariae Curie 

Sklodowska [Med]. 1999;54:87-96. Not eligible 

target population. 

1570. Ksykiewicz-Dorota A. Development of nursing time 

standards as a problem of optimalisation of health 

care system management. I. Evaluation of the 

correctness of patients' classification. Ann Univ 

Mariae Curie Sklodowska [Med]. 1999;54:79-86. Not 

eligible target population. 

1571. Ksykiewicz-Dorota A, Wysokinski M. Special 

characteristics of nursing staff scheduling in intensive 

care units. Ann Univ Mariae Curie Sklodowska 

[Med]. 2001;56:313-318. Not eligible target 

population. 

1572. Kubecka KE, Simon JM, Boettcher JH. Pain 

management knowledge of hospital-based nurses in a 

rural Appalachian area. J Adv Nurs. May 

1996;23(5):861-867. Not eligible exposure. 

1573. Kubisiak J. Is this midwifery? Midwifery Today Int 

Midwife. Summer 1998(46):42. Comment. 

1574. Kuhn EM, Hartz AJ, Gottlieb MS, Rimm AA. The 

relationship of hospital characteristics and the results 

of peer review in six large states. Med Care. Oct 

1991;29(10):1028-1038. Not eligible exposure. 

1575. Kumarich D, Biordi DL, Milazzo-Chornick N. The 

impact of the 23-hour patient on nursing workload. J 

Nurs Adm. Nov 1990;20(11):47-52. Not eligible 

exposure. 

1576. Kupferman K. 10 ways to help students grow. 

Nursing. Apr 2005;35(4):56. Comment. 

1577. Kurian VA. Life-style impact for Christ. Christ Nurse 

Int. 1995;11(3):5. Comment. 

1578. Kutash MB, Nelson D. Optimizing the use of nursing 

pool resources. J Nurs Adm. Jan 1993;23(1):65-68. 

No association tested. 

1579. Kydd A. Education and training in dementia care. 

Community Nurse. Jan 2000;5(12):15-16. Comment. 

1580. Kyle F. Your shift penalties under attack. Aust Nurses 

J. Apr 1990;19(9):10-11. Not eligible target 

population. 

1581. Lacombe DC. Avoiding a malpractice nightmare. 

Nursing. Jun 1990;20(6):42-43. Case Reports. 

1582. Lacovara JE. Does your acuity system come up short? 

Nurs Manage. Jun 1999;30(6):40A-40C. Not eligible 

exposure. 

1583. LaDuke S. It can happen to you: the firsthand 

accounts of six nurses accused of and disciplined for 

professional misconduct. J Emerg Nurs. Aug 

2001;27(4):369-376. Legal cases. 

1584. Lageson C. Quality focus of the first line nurse 

manager and relationship to unit outcomes. J Nurs 

Care Qual. Oct-Dec 2004;19(4):336-342. Not eligible 

exposure. 

1585. Laitinen P, Isola A. Promoting participation of 

informal caregivers in the hospital care of the elderly 

patient: informal caregivers' perceptions. J Adv Nurs. 

May 1996;23(5):942-947. Not eligible target 

population. 

1586. Lalani NS, Gulzar AZ. Nurses' role in patients' 

discharge planning at the Aga Khan University 

Hospital, Pakistan. J Nurses Staff Dev. Nov-Dec 

2001;17(6):314-319. Not eligible target population. 

1587. Lamb J, Ross S. Pain management. A patient's 

perspective. Can Nurse. Aug 1999;95(7):30-33. 

Comment. 

1588. Lamb LS, Jr., Parrish RS, Goran SF, Biel MH. 

Current nursing practice of point-of-care laboratory 

diagnostic testing in critical care units. Am J Crit 

Care. Nov 1995;4(6):429-434. Not eligible exposure.

1589. Lambert C. In the red. Nurs Times. Oct 27-Nov 2 

1999;95(43):16-17. Comment. 

1590. Lambing AY, Adams DL, Fox DH, Divine G. Nurse 

practitioners' and physicians' care activities and 

clinical outcomes with an inpatient geriatric 

population. J Am Acad Nurse Pract. Aug 

2004;16(8):343-352. Not eligible exposure. 

1591. Lamkin L, Rosiak J, Buerhaus P, Mallory G, 

Williams M. Oncology Nursing Society Workforce 

Survey. Part II: perceptions of the nursing workforce 

environment and adequacy of nurse staffing in 

outpatient and inpatient oncology settings. Oncol 

Nurs Forum. Jan-Feb 2002;29(1):93-100. Not eligible 

outcomes. 

1592. Lampat L, Frederick B, Young D, Dankbar G. 

Changing the start of the hospital workweek. Nurs 

Econ. Jul-Aug 1991;9(4):263-265. Not eligible 

exposure. 

1593. Lancaster R. Lifting the lid. Nurs Stand. Aug 5-11 

1998;12(46):20-22. Comment. 

1594. Lancelot A, Sims J. Mental illness and substance 

abuse. Nurs Times. Sep 27-Oct 3 2001;97(39):36-37. 

Case reports. 

1595. Landergan E. Staffing for census fluctuations. Nurs 

Manage. May 1997;28(5):77-78. Comment.
B-47 

1596. Landreville P, Dicaire L, Verrault R, et al. A training 

program for managing agitation of residents in longterm care facilities: description and preliminary 

findings. Journal of gerontological nursing Mar 

2005;31(3):34-42, 55-6. Nursing home. 

1597. Lang TA, Hodge M, Olson V, Romano PS, Kravitz 

RL. Nurse-patient ratios: a systematic review on the 

effects of nurse staffing on patient, nurse employee, 

and hospital outcomes. J Nurs Adm. Jul-Aug 

2004;34(7-8):326-337. Review. 

1598. Langslow A. Nursing and the law. Vigilance in the 

OR. Aust Nurs J. Oct 1996;4(4):30-32. Case Reports. 

1599. Lankshear AJ, Sheldon TA, Maynard A. Nurse 

staffing and healthcare outcomes: a systematic review 

of the international research evidence. ANS Adv Nurs 

Sci. Apr-Jun 2005;28(2):163-174. Review. 

1600. Lanser EG. Leveraging your nursing resources. 

Healthc Exec. Jul-Aug 2001;16(4):50-51. Comment. 

1601. Lanza ML, Kayne HL, Hicks C, Milner J. Nursing 

staff characteristics related to patient assault. Issues 

Ment Health Nurs. Jun-Sep 1991;12(3):253-265. Not 

eligible outcomes. 

1602. Larcombe J. Bed-blockers. Mental block. Nurs 

Times. Jun 20-26 1990;86(25):33-34. Case Reports. 

1603. Lark K, Dean K, Mikos CA. Nursing liability risk--

three perspectives. Fla Nurse. Mar 2000;48(1):22-23. 

Legal Cases.

1604. Larkin GL, Rolniak S, Hyman KB, MacLeod BA, 

Savage R. Effect of an administrative intervention on 

rates of screening for domestic violence in an urban 

emergency department. Am J Public Health. Sep 

2000;90(9):1444-1448. Not eligible outcomes. 

1605. Larkin H. The case for nurse practitioners. Used 

correctly, they can improve outcomes, lower costs 

and make up for reduced residents' hours. Hosp 

Health Netw. Aug 2003;77(8):54-58, 52. Not eligible 

exposure. 

1606. Larrabee JH. Achieving outcomes in a jointappointment role. Outcomes Manag Nurs Pract. AprJun 2001;5(2):52-56. Comment. 

1607. Larrabee JH, Ostrow CL, Withrow ML, Janney MA, 

Hobbs GR, Jr., Burant C. Predictors of patient 

satisfaction with inpatient hospital nursing care. Res 

Nurs Health. Aug 2004;27(4):254-268. Not eligible 

exposure. 

1608. Larson EL, Bryan JL, Adler LM, Blane C. A 

multifaceted approach to changing handwashing 

behavior. Am J Infect Control. Feb 1997;25(1):3-10. 

Not eligible exposure.

1609. Larson EL, Cimiotti J, Haas J, Parides M, Nesin M, 

Della-Latta P, Saiman L. Effect of antiseptic 

handwashing vs alcohol sanitizer on health careassociated infections in neonatal intensive care units. 

Arch Pediatr Adolesc Med. Apr 2005;159(4):377-

383. Not eligible exposure. 

1610. Larson L. Restoring the relationship: the key to nurse 

and patient satisfaction. Trustee. Oct 2004;57(9):8-10, 

12-14, 11. Comment. 

1611. Larsson G, Berg V. Linen in the hospital bed: effects 

on patients' well-being. J Adv Nurs. Aug 

1991;16(8):1004-1008. Not eligible target population. 

1612. Larter J. Three-part model manages care from 

admission through postdischarge. Disch Plann 

Update. Mar-Apr 1993;13(2):1, 20-23. Not eligible 

outcomes. 

1613. Laschinger HK, Almost J, Tuer-Hodes D. Workplace 

empowerment and magnet hospital characteristics: 

making the link. J Nurs Adm. Jul-Aug 2003;33(7-

8):410-422. Not eligible exposure. 

1614. Laschinger HK, Finegan J, Shamian J, Casier S. 

Organizational trust and empowerment in restructured 

healthcare settings. Effects on staff nurse 

commitment. J Nurs Adm. Sep 2000;30(9):413-425. 

Not eligible exposure. 

1615. Laschinger HK, Finegan J, Shamian J, Wilk P. Impact 

of structural and psychological empowerment on job 

strain in nursing work settings: expanding Kanter's 

model. J Nurs Adm. May 2001;31(5):260-272. Not 

eligible exposure. 

1616. Laschinger HK, Wong C, McMahon L, Kaufmann C. 

Leader behavior impact on staff nurse empowerment, 

job tension, and work effectiveness. J Nurs Adm. 

May 1999;29(5):28-39. Not eligible exposure.

1617. Laurent C. Ward managers. Too hot to handle? 

Health Serv J. Aug 23 2001;111(5769):22-25. Not 

eligible target population. 

1618. Lauri S, Lepisto M, Kappeli S. Patients' needs in 

hospital: nurses' and patients' views. J Adv Nurs. Feb 

1997;25(2):339-346. Not eligible target population. 

1619. Lawler K. How audit can improve provision of inpatient pain services. Prof Nurse. Sep 2001;17(1):41. 

Comment. 

1620. Lawson K. Trading places--a seasonal exchange 

program. Rn. Oct 1990;53(10):19-21. No association 

tested. 

1621. Lawson S, Aston S, Baker L, Fegan CD, Milligan 

DW. Trained nurses can obtain satisfactory bone 

marrow aspirates and trephine biopsies. J Clin Pathol. 

Feb 1999;52(2):154-156. Not eligible target 

population. 

1622. Lawton LC, Rose P. Changing practice in invasive 

procedures: the experience of the Krishnan Chandran 

children's centre. J Child Health Care. Dec 

2003;7(4):248-257. Not eligible target population. 

1623. Layon AJ, George BE, Hamby B, Gallagher TJ. Do 

elderly patients overutilize healthcare resources and 

benefit less from them than younger patients? A study 

of patients who underwent craniotomy for treatment 

of neoplasm. Crit Care Med. May 1995;23(5):829-

834. Not eligible exposure. 

1624. Lazure LL. Strategies to increase patient control of 

visiting. Dimens Crit Care Nurs. Jan-Feb 

1997;16(1):11-19. Not eligible exposure. 

1625. Le Blanc PM, de Jonge J, de Rijk AE, Schaufeli WB. 

Well-being of intensive care nurses (WEBIC): a job 

analytic approach. J Adv Nurs. Nov 2001;36(3):460-

470. Not eligible target population. 

1626. Lea A, Bloodworth C. Modernising the 12-hour shift. 

Nurs Stand. Jan 22-28 2003;17(19):33-36. Not 

eligible target population. 

1627. Leach E. Have qualifications, will travel. Nurs Times. 

Apr 13-19 2000;96(15):55-57. Comment. 
B-48 

1628. Leary TS, Milner QJ, Niblett DJ. The accuracy of the 

estimation of body weight and height in the intensive 

care unit. Eur J Anaesthesiol. Nov 2000;17(11):698-

703. Not eligible target population. 

1629. L'Ecuyer PB, Schwab EO, Iademarco E, Barr N, Aton 

EA, Fraser VJ. Randomized prospective study of the 

impact of three needleless intravenous systems on 

needlestick injury rates. Infect Control Hosp 

Epidemiol. Dec 1996;17(12):803-808. Not eligible 

exposure. 

1630. Lee CS, Shiu AT. Perceived health care climate, 

diabetes knowledge and self-care practice of Hong 

Kong Chinese older patients: a pilot study. J Clin 

Nurs. May 2004;13(4):534-535. Not eligible target 

population. 

1631. Lee D. Overtime--mandatory or voluntary? Br J 

Perioper Nurs. Feb 2002;12(2):63. Not eligible target 

population. 

1632. Lee DS. The morning tea break ritual: a case study. 

Int J Nurs Pract. Apr 2001;7(2):69-73. Not eligible 

target population. 

1633. Lee EH. Breast self-examination performance among 

Korean nurses. J Nurses Staff Dev. Mar-Apr 

2003;19(2):81-87. Not eligible target population.

1634. Lee EO, Ahn SH, You C, Lee DS, Han W, Choe KJ, 

Noh DY. Determining the main risk factors and highrisk groups of breast cancer using a predictive model 

for breast cancer risk assessment in South Korea. 

Cancer Nurs. Sep-Oct 2004;27(5):400-406. Not 

eligible target population. 

1635. Lee F. Violence in A&E: the role of training and selfefficacy. Nurs Stand. Aug 1-7 2001;15(46):33-38. Not 

eligible target population. 

1636. Lee G. The needs of the service. Pract Midwife. Feb 

2000;3(2):44. Comment.

1637. Lee H, Hwang S, Kim J, Daly B. Predictors of life 

satisfaction of Korean nurses. J Adv Nurs. Dec 

2004;48(6):632-641. Not eligible target population. 

1638. Lee H, Song R, Cho YS, Lee GZ, Daly B. A 

comprehensive model for predicting burnout in 

Korean nurses. J Adv Nurs. Dec 2003;44(5):534-545. 

Not eligible target population. 

1639. Lee JM, Botteman MF, Nicklasson L, Cobden D, 

Pashos CL. Needlestick injury in acute care nurses 

caring for patients with diabetes mellitus: a 

retrospective study. Curr Med Res Opin. May 

2005;21(5):741-747. Not eligible exposure 

1640. Lee KA, Lipscomb J. Clinical update. Sleep among 

shiftworkers -- a priority for clinical practice and 

research in occupational health nursing. AAOHN 

Journal Oct 2003;51(10):418-20. Not relevant. 

1641. Lee KA. Self-reported sleep disturbances in employed 

women. Sleep. Dec 1992;15(6):493-498. Not eligible 

outcomes. 

1642. Lee KA, Rittenhouse CA. Prevalence of 

perimenstrual symptoms in employed women. 

Women Health. 1991;17(3):17-32. Not eligible 

outcomes. 

1643. Lee KA, Rittenhouse CA. Health and perimenstrual 

symptoms: health outcomes for employed women 

who experience perimenstrual symptoms. Women 

Health. 1992;19(1):65-78. Not eligible exposure. 

1644. Lee L, Goor E, Kennedy C, Walters S, Kirby L. Nonacute casemix in the Illawarra. J Qual Clin Pract. Mar 

1994;14(1):23-30. Not eligible target population. 

1645. Lee RJ, Mills MEE. Management issues. International 

nursing recruitment experience. Journal of Nursing 

Administration Nov 2005;35(11):478-81. Not 

research. 

1646. Lee S. Relocating elderly people and nursing staff 

from the NHS to the independent sector. J Adv Nurs. 

Oct 1998;28(4):859-864. Not eligible target 

population. 

1647. Lee S, Crockett MS. Effect of assertiveness training 

on levels of stress and assertiveness experienced by 

nurses in Taiwan, Republic of China. Issues Ment 

Health Nurs. Jul-Aug 1994;15(4):419-432. Not 

eligible target population. 

1648. Lee TH, Cook EF, Fendrick AM, Shammash JB, 

Wolfe EP, Weisberg MC, Goldman L. Impact of 

initial triage decisions on nursing intensity for 

patients with acute chest pain. Med Care. Aug 

1990;28(8):737-745. Not eligible exposure. 

1649. Lee TT. Nurses' concerns about using information 

systems: analysis of comments on a computerized 

nursing care plan system in Taiwan. J Clin Nurs. Mar 

2005;14(3):344-353. Not eligible target population. 

1650. Lee TT, Chang PC. Standardized care plans: 

experiences of nurses in Taiwan. J Clin Nurs. Jan 

2004;13(1):33-40. Not eligible target population. 

1651. Lee YL, Cesario T, Tran C, Stone G, Thrupp L. Nasal 

colonization by methicillin-resistant coagulasenegative staphylococcus in community skilled nursing 

facility patients. Am J Infect Control. Jun 

2000;28(3):269-272. Not eligible target population. 

1652. Lees L, Holmes C. Estimating date of discharge at 

ward level: a pilot study. Nurs Stand. Jan 5-11 

2005;19(17):40-43. Not eligible target population. 

1653. Leftridge DW, Lydford CW. Decentralizing an 

overtime budget. Nurs Manage. Aug 1993;24(8):52-

53. No association tested. 

1654. Leggett J, Silvester J. Care staff attributions for 

violent incidents involving male and female patients: 

a field study. Br J Clin Psychol. Nov 2003;42(Pt 

4):393-406. Not eligible target population. 

1655. Leicht KT, Fennell ML, Witkowski KM. The effects 

of hospital characteristics and radical organizational 

change on the relative standing of health care 

professions. J Health Soc Behav. Jun 1995;36(2):151-

167. Not eligible outcomes. 

1656. Leifer D. Anything but magnolia. Nurs Stand. Apr 3-

9 2002;16(29):16-17. Not eligible target population. 

1657. Leifer D. A rotation programme that works. Nurs 

Stand. Mar 19-25 2003;17(27):16. Comment. 

1658. Leininger SM. Tools for building a successful 

orthopaedic pathway. Orthop Nurs. Mar-Apr 

1996;15(2):11-19. Not eligible exposure. 

1659. Leino-Kilpi H, Valimaki M, Dassen T, Gasull M, 

Lemonidou C, Scott PA, Arndt M, Kaljonen A. 

Maintaining privacy on post-natal wards: a study in 

five European countries. J Adv Nurs. Jan 

2002;37(2):145-154. Not eligible target population. 
B-49 

1660. Leinonen T, Leino-Kilpi H, Stahlberg MR, Lertola K. 

Comparing patient and nurse perceptions of 

perioperative care quality. Appl Nurs Res. Feb 

2003;16(1):29-37. Not eligible target population.

1661. Lemmen SW, Zolldann D, Gastmeier P, Lutticken R. 

Implementing and evaluating a rotating surveillance 

system and infection control guidelines in 4 intensive 

care units. Am J Infect Control. Apr 2001;29(2):89-

93. Not eligible target population. 

1662. Lemonidou C, Plati C, Brokalaki H, Mantas J, Lanara 

V. Allocation of nursing time. Scand J Caring Sci. 

1996;10(3):131-136. Not eligible target population.

1663. Lenehan GP. ED short staffing: It is time to take a 

hard look at a growing problem and strategies such as 

standard nurse-patient ratios. J Emerg Nurs. Apr 

1999;25(2):77-78. Editorial. 

1664. Lenehan GP. On mandatory overtime and wearing 

blue ribbons. J Emerg Nurs. Jun 2000;26(3):201-202. 

Editorial. 

1665. Lengacher CA, Kent K, Mabe PR, Heinemann D, 

VanCott ML, Bowling CD. Effects of the partners in 

care practice model on nursing outcomes. Nurs Econ. 

Nov-Dec 1994;12(6):300-308. Not eligible exposure. 

1666. Lengacher CA, Mabe PR, Heinemann D, VanCott 

ML, Kent K, Swymer S. Collaboration in research: 

testing the PIPC model on clinical and nonclinical 

outcomes. Nursingconnections. Spring 

1997;10(1):17-30. Not eligible exposure. 

1667. Lepola I, Blom-Lange M. Participation in change: 

self-reflection of staff in a psychiatric admission unit. 

Nurs Health Sci. Sep 1999;1(3):171-177. Not eligible 

target population. 

1668. Leslie GD. Know your staff numbers--and know 

you're right. Aust Crit Care. Aug 2003;16(3):83. 

Editorial. 

1669. Letvak SA. Should a staff nurse's age be a 

consideration in making patient and shift 

assignments? Pro. MCN Am J Matern Child Nurs. 

Mar-Apr 2005;30(2):84. Comment. 

1670. Leveck ML, Jones CB. The nursing practice 

environment, staff retention, and quality of care. Res 

Nurs Health. Aug 1996;19(4):331-343. Not eligible 

outcomes. 

1671. Levenstam AK, Engberg IB. The Zebra system--a 

new patient classification system. J Nurs Manag. Sep 

1993;1(5):229-237. Not eligible target population.

1672. Levenstam AK, Engberg IB. How to translate nursing 

care into costs and staffing requirements: part two in 

the Zebra system. J Nurs Manag. Mar 1997;5(2):105-

114. Not eligible target population. 

1673. Levy CR, Ely EW, Payne K, Engelberg RA, Patrick 

DL, Curtis JR. Quality of dying and death in two 

medical ICUs: perceptions of family and clinicians. 

Chest. May 2005;127(5):1775-1783. Not eligible 

exposure. 

1674. Lewandrowski K, Cheek R, Nathan DM, Godine JE, 

Hurxthal K, Eschenbach K, Laposata M. 

Implementation of capillary blood glucose monitoring 

in a teaching hospital and determination of program 

requirements to maintain quality testing. Am J Med. 

Oct 1992;93(4):419-426. Not eligible exposure. 

1675. Lewis EN. An in-house registry: a pragmatic 

approach that works! Nurs Manage. Feb 

1991;22(2):43-44, 48. No association tested. 

1676. Lewis JA, Della PR. Alternative nurse rostering: an 

evaluation. Aust Health Rev. 1994;17(2):29-39. Not 

eligible target population. 

1677. Lewis KK. Nurse-to-patient ratios: research and 

reality. Issue Brief (Mass Health Policy Forum). Mar 

30 2005(25):1-19. Review.

1678. Lewis L. Discussion & recommendations: safe 

medication administration: an invitational symposium 

recommends ways of addressing obstacles. J Infus 

Nurs. Mar-Apr 2005;28(2 Suppl):42-44, 46-47. 

Review. 

1679. Lewis T, Abanobi B, Alleman P, et al. The Methodist 

Hospital CCU: a Beacon unit of excellence. Crit Care 

Nurs Clin North Am. Jun 2005;17(2):149-154, x. 

Review. 

1680. Lewis T, Oliver G. Improving tracheostomy care for 

ward patients. Nurs Stand. Jan 19-25 2005;19(19):33-

37. Not eligible exposure. 

1681. Libby DL, Bolduc PC. Float pool orientation. J Nurs 

Staff Dev. Nov-Dec 1995;11(6):297-299. No 

association tested. 

1682. Lichtenstein B, Brumfield C, Cliver S, Chapman V, 

Lenze D, Davis V. Giving birth, going home: 

influences on when low-income women leave 

hospital. Health (London). Jan 2004;8(1):81-100. Not 

eligible exposure. 

1683. Lilienberg A, Bengtsson M, Starkhammar H. 

Implantable devices for venous access: nurses' and 

patients' evaluation of three different port systems. J 

Adv Nurs. Jan 1994;19(1):21-28. Not eligible target 

population. 

1684. Lilley LL, Guanci R. Applying systems theory. Am J 

Nurs. Nov 1995;95(11):14-15. Comment. 

1685. Lilley LL, Guanci R. Sound-alike cephalosporins. 

How drugs with similar spellings and sounds can lead 

to serious errors. Am J Nurs. Jun 1995;95(6):14. 

Comment.

1686. Lilley LL, Guanci R. Med errors: watch those labels. 

Am J Nurs. May 1996;96(5):14. Case Reports. 

1687. Lilley LL, Guanci R. Avoiding heparin dosing 

mistakes. Am J Nurs. Dec 1997;97(12):12. Comment. 

1688. Lilley LL, Guanci R. Look-alike abbreviations: 

prescriptions for confusion. Am J Nurs. Nov 

1997;97(11):12. Case Reports. 

1689. Lilley LL, Guanci R. Careful with the zeros! How to 

minimize one of the most persistent causes of gross 

medication errors. Am J Nurs. May 1997;97(5):14. 

Comment. 

1690. Lilley LL, Guanci R. Neuromuscular blocking agents. 

Am J Nurs. Feb 1997;97(2):12-14. Comment. 

1691. Lilley LL, Guanci R. Distraction delays a dose. Am J 

Nurs. Feb 1998;98(2):12. Case Reports. 

1692. Lin MC, Chen CH. An investigation on the nursing 

competence of southern Taiwan nurses who have 

passed N3 case report accreditation. J Nurs Res. Sep 

2004;12(3):203-212. Not eligible target population. 
B-50 

1693. Lincoln LL, Dudley MN. Potential effect of oral 

antimicrobial therapy on nurse staffing requirements. 

Am J Hosp Pharm. Feb 1990;47(2):386-388. No 

association tested. 

1694. Lindley-Jones M, Finlayson BJ. Triage nurse 

requested x rays--are they worthwhile? J Accid 

Emerg Med. Mar 2000;17(2):103-107. Not eligible 

target population. 

1695. Lindsay M. Is the postanesthesia care unit becoming 

an intensive care unit? J Perianesth Nurs. Apr 

1999;14(2):73-77. Comment. 

1696. Lindsey T, Watts-Tate N, Southwood E, Routhieaux 

J, Beatty J, Diane C, Phillips M, Lea G, Brown E, 

DeBaun MR. Chronic blood transfusion therapy 

practices to treat strokes in children with sickle cell 

disease. J Am Acad Nurse Pract. Jul 2005;17(7):277-

282. Not eligible exposure. 

1697. Lininger RA. Pediatric peripheral i.v. insertion 

success rates. Pediatr Nurs. Sep-Oct 2003;29(5):351-

354. Not eligible outcomes. 

1698. Lipley N. Millennium bed bug. Nurs Stand. Nov 3-9 

1999;14(7):12. Not eligible target population. 

1699. Lipley N. Pressure gauge. Nurs Stand. Feb 9-15 

2000;14(21):12-13. Comment. 

1700. Lipley N. Breaking the cycle of bad news. Nurs 

Stand. Oct 10-16 2001;16(4):13. Comment. 

1701. Little K, Palmer D. Central line exit sites: which 

dressing? Nurs Stand. Aug 19-25 1998;12(48):42-44. 

Not eligible exposure. 

1702. Little M. When do you 'say no' to work assignments? 

Tenn Nurse. Jun 1991;54(3):17-19. Comment. 

1703. Litvak E, Buerhaus PI, Davidoff F, et al. Managing 

unnecessary variability in patient demand to reduce 

nursing stress and improve patient safety. Jt Comm J 

Qual Patient Saf. Jun 2005;31(6):330-338. Review. 

1704. Liu JJ. Assessing the relationship between staffing 

levels and quality outcomes in nursing facilities. 

Dissertation. 2003;DAI-A 64/06, p. 2211, Dec 

2003:AAT 3092765. Not eligible Target population.

1705. Livesley J. Telling tales: a qualitative exploration of 

how children's nurses interpret work with 

unaccompanied hospitalized children. J Clin Nurs. 

Jan 2005;14(1):43-50. Not eligible exposure. 

1706. Livingston C. Chicago jobfocus. A forceful health 

care community. Am J Nurs. Mar 1991;91(3):89-90, 

92, 94-85. News. 

1707. Livne M, Steinmann M. Pressure ulcer prevention 

project: an international outcomes report from Israel. 

Outcomes Manag. Jul-Sep 2002;6(3):99-102. Not 

eligible target population. 

1708. Lloyd G, McLauchlan A. Nurses' attitudes towards 

management of pain. Nurs Times. Oct 26-Nov 1 

1994;90(43):40-43. Not eligible exposure. 

1709. Lloyd R, Goulding J. Nursing rotas. Shift up. Health 

Serv J. Oct 14 1999;109(5676):28. Not eligible target 

population. 

1710. Locsin RC. Caring and curing orientations of foreigneducated professional nurses. Philippine Journal of 

Nursing Jan-Jun 1997;67(1-2):27-32. Not relevant.

1711. Lomas C. Make the most of flexible working. Nurs 

Times. May 3-9 2005;101(18):76-77. Comment. 

1712. Long CG, Blackwell CC, Midgley M. An evaluation 

of two systems of in-patient care in a general hospital 

psychiatric unit. II: Measures of staff and patient 

performance. J Adv Nurs. Dec 1990;15(12):1436-

1442. Not eligible target population. 

1713. Long CG, Blackwell CC, Midgley M. An evaluation 

of two systems of in-patient care in a general hospital 

psychiatric unit I: staff and patient perceptions and 

attitudes. J Adv Nurs. Jan 1992;17(1):64-71. Not 

eligible target population. 

1714. Long G. Measuring the benefits of bedside 

documentation systems. Aspens Advis Nurse Exec. 

Dec 1994;10(3):1-4. Not eligible exposure. 

1715. Long T. Pointing out medication errors. Am J Nurs. 

Feb 1992;92(2):76-78. Comment.

1716. Lookinland S, Crenshaw J. Rewarding clinical 

competence in the ICU: using outcomes to reward 

performance. Dimens Crit Care Nurs. Jul-Aug 

1996;15(4):206-215. Comment. 

1717. Lough-Miramontes A. Stop announcing JCAHO 

inspections. Nursing. Sep 2002;32(9):12. Letter. 

1718. Lovern E. Study: RNs can bolster outcomes. Mod 

Healthc. Apr 30 2001;31(18):4-5. News.

1719. Lovett RB, McMillan SC. Validity and reliability of a 

bone marrow transplant acuity tool. Oncol Nurs 

Forum. Oct 1993;20(9):1385-1392. Not eligible target 

population. 

1720. Lovett RB, Wagner L, McMillan S. Validity and 

reliability of a pediatric hematology oncology patient 

acuity tool. J Pediatr Oncol Nurs. Jul 1991;8(3):122-

130. Not eligible outcomes.

1721. Lu WH, Kolkman K, Seger M, Sugrue M. An 

evaluation of trauma team response in a major trauma 

hospital in 100 patients with predominantly minor 

injuries. Aust N Z J Surg. May 2000;70(5):329-332. 

Not eligible target population.

1722. Ludkin H, Quinn P, Jones SE, Wilkinson K. The 

benefits of setting up a nurse hysteroscopy service. 

Prof Nurse. Dec 2003;19(4):220-222. Not eligible 

target population. 

1723. Ludwig-Beymer P, Czurylo KT, Gattuso MC, 

Hennessy KA, Ryan CJ. The effect of testing on the 

reported incidence of medication errors in a medical 

center. J Contin Educ Nurs. Jan-Feb 1990;21(1):11-

17. Not eligible exposure. 

1724. Lukacs A. Issues surrounding early postpartum 

discharge: effects on the caregiver. J Perinat Neonatal 

Nurs. Jun 1991;5(1):33-42. Not eligible exposure. 

1725. Lukman D, May JH, Shuman LJ, Wolfe HB. 

Knowledge-based schedule formulation and 

maintenance under uncertainty. J Soc Health Syst. 

1991;2(2):42-64. No association tested. 

1726. Lumsdon K. Crash course: piecing together the 

continuum of care. Hosp Health Netw. Nov 20 

1994;68(22):26-28, 30, 32 passim. Comment. 

1727. Lund CH, Osborne JW. Validity and reliability of the 

neonatal skin condition score. J Obstet Gynecol 

Neonatal Nurs. May-Jun 2004;33(3):320-327. Not 

eligible exposure. 
B-51 

1728. Lund CH, Osborne JW, Kuller J, Lane AT, Lott JW, 

Raines DA. Neonatal skin care: clinical outcomes of 

the AWHONN/NANN evidence-based clinical 

practice guideline. Association of Women's Health, 

Obstetric and Neonatal Nurses and the National 

Association of Neonatal Nurses. J Obstet Gynecol 

Neonatal Nurs. Jan-Feb 2001;30(1):41-51. Not 

eligible exposure. 

1729. Lundgren A, Wahren LK. Effect of education on 

evidence-based care and handling of peripheral 

intravenous lines. J Clin Nurs. Sep 1999;8(5):577-

585. Not eligible target population.

1730. Lundgren S, Segesten K. Nurses' use of time in a 

medical-surgical ward with all-RN staffing. J Nurs 

Manag. Jan 2001;9(1):13-20. Not eligible target 

population. 

1731. Lundgren SM, Nordholm L, Segesten K. Job 

satisfaction in relation to change to all-RN staffing. J 

Nurs Manag. Jul 2005;13(4):322-328. Not eligible 

target population. 

1732. Lundgren SM, Segesten K. Nurses' altered 

conceptions of work in a ward with all-RN staffing. J 

Clin Nurs. Mar 2002;11(2):197-204. Not eligible 

target population. 

1733. Lunetta C. Employing foreign nurses. Trustee. Apr 

1991;44(4):3. News.

1734. Lunney M, Karlik BA, Kiss M, Murphy P. Accuracy 

of nurses' diagnoses of psychosocial responses. Nurs 

Diagn. Oct-Dec 1997;8(4):157-166. Not eligible 

exposure. 

1735. Lupfer PA, Altieri M, Sheridan MJ, Lilly CC. Patient 

flow in the emergency department: the chest pain 

patient. Am J Emerg Med. Mar 1991;9(2):127-130. 

Not eligible exposure. 

1736. Lupton D, Fenwick J. 'They've forgotten that I'm the 

mum': constructing and practising motherhood in 

special care nurseries. Soc Sci Med. Oct 

2001;53(8):1011-1021. Not eligible target population. 

1737. Lush MT, Henry SB. Nurses use of health status data 

to plan for patient care: implications for the 

development of a computer-based outcomes 

infrastructure. Proc AMIA Annu Fall Symp. 

1997:136-140. Not eligible exposure. 

1738. Luther KM, Maguire L, Mazabob J, Sexton JB, 

Helmreich RL, Thomas E. Engaging nurses in patient 

safety. Crit Care Nurs Clin North Am. Dec 

2002;14(4):341-346. Not eligible exposure. 

1739. Luther KM, Walsh K. Moving out of the red zone: 

addressing staff allocation to improve patient 

satisfaction. Jt Comm J Qual Improv. Jul 

1999;25(7):363-368. Not eligible exposure. 

1740. Lynn MR, Kelley B. Effects of case management on 

the nursing context--perceived quality of care, work 

satisfaction, and control over practice. Image J Nurs 

Sch. 1997;29(3):237-241. Not eligible exposure. 

1741. Lynn MR, McMillen BJ. Do nurses know what 

patients think is important in nursing care? J Nurs 

Care Qual. Jun 1999;13(5):65-74. Not eligible 

exposure. 

1742. Lyon J. Power napping and work performance. Nev 

Rnformation. Nov 1995;4(4):18. Comment. 

1743. Lyon JC, Gerbis PR. Acuity vs staffing mix. Nev 

Rnformation. Nov 1994;3(4):1, 3. Comment. 

1744. Ma CC, Samuels ME, Alexander JW. Factors that 

influence nurses' job satisfaction. J Nurs Adm. May 

2003;33(5):293-299. Not eligible exposure. 

1745. MacDonald M, Bodzak W. The performance of a 

self-managing day surgery nurse team. J Adv Nurs. 

Apr 1999;29(4):859-868. Not eligible target 

population. 

1746. MacDonald MR, Miller-Grolla L. Developing a 

collective future: creating a culture specific nurse 

caring practice model for hospitals. Can J Nurs Adm. 

Sep-Oct 1995;8(3):78-95. No association tested. 

1747. Mackay I, Paterson B, Cassells C. Constant or special 

observations of inpatients presenting a risk of 

aggression or violence: nurses' perceptions of the 

rules of engagement. J Psychiatr Ment Health Nurs. 

Aug 2005;12(4):464-471. Not eligible target 

population. 

1748. MacKenzie J, Jordan K. Discharge planning. Oiling 

the wheels. Health Serv J. Oct 23 1997;107(5576):32-

33. Not eligible target population.

1749. Mackie PL, Joannidis PA, Beattie J. Evaluation of an 

acute point-of-care system screening for respiratory 

syncytial virus infection. J Hosp Infect. May 

2001;48(1):66-71. Not eligible target population. 

1750. Mackintosh C. Do nurses provide adequate 

postoperative pain relief? Br J Nurs. Apr 14-27 

1994;3(7):342-347. Not eligible target population. 

1751. Macleod AJ, Freeland P. Should nurses be allowed to 

request X-rays in an accident & emergency 

department? Arch Emerg Med. Mar 1992;9(1):19-22. 

Not eligible target population. 

1752. MacPhee M. Hospital networking. Comparing the 

work of nurses with flexible and traditional schedules. 

J Nurs Adm. Apr 2000;30(4):190-198. Not eligible 

outcomes. 

1753. Macready N. Trial of Denver nurses points up system 

flaws. OR Manager. Mar 1999;15(3):32-33. 

Comment. 

1754. MacStravic S. Employee success management: a cure 

for the staffing crisis? Health Care Strateg Manage. 

Aug 2002;20(8):1, 15-19. Comment. 

1755. MacVicar J, Dobbie G, Owen-Johnstone L, Jagger C, 

Hopkins M, Kennedy J. Simulated home delivery in 

hospital: a randomised controlled trial. Br J Obstet 

Gynaecol. Apr 1993;100(4):316-323. Not eligible 

target population. 

1756. MacWhannell D. Take the medical model out of the 

menopause. Nurs Times. Oct 13-19 1999;95(41):45-

46. Not eligible target population. 

1757. Mahon A. HSJ people. Ifs and cuts. Health Serv J. 

Dec 11 2003;113(5885):36-37. Not eligible target 

population. 

1758. Mahoney. The extent, nature, and response to 

victimization of emergency nurses in Pennsylvania... 

including commentary by Lanza ML with author 

response. Journal of Emergency Nursing Oct 

1991;17(5):282-94. Not relevant. 

1759. Mahony C. Watchdog's verdict: millions squandered, 

nurses neglected. Nurs Times. Sep 6-12 

2001;97(36):10-11. Not eligible target population.
B-52 

1760. Mahrenholz DM. Colleagues in caring. Connecticut 

Nursing News Jun-Aug 1999;72(2):22-3. Not peer 

reviewed.

1761. Main J. Management of relatives of patients who are 

dying. J Clin Nurs. Nov 2002;11(6):794-801. Not 

eligible target population. 

1762. Makinen A, Kivimaki M, Elovainio M, Virtanen M, 

Bond S. Organization of nursing care as a determinant 

of job satisfaction among hospital nurses. J Nurs 

Manag. Sep 2003;11(5):299-306. Not eligible target 

population. 

1763. Makowiec-Dabrowska T, Krawczyk-Adamus P, 

Sprusinska E, Jozwiak ZW. Can nurses be employed 

in 12-hour shift systems? Int J Occup Saf Ergon. 

2000;6(3):393-403. Not eligible target population. 

1764. Malcolmson L, Lavender T, Walkinshaw S. Visiting 

on the maternity wards. Pract Midwife. Mar 

1999;2(3):20-23. Not eligible target population. 

1765. Malik U. Clients' health needs: nurses' concern. Nurs 

J India. Feb 1996;87(2):29-32. Not eligible target 

population. 

1766. Mallison MB. Let's identify the Yellowhearts in our 

midst. Am J Nurs. Feb 1991;91(2):7. Editorial. 

1767. Mallison MB. Cadillac or Chevrolet nursing? Look 

under the hood. Am J Nurs. Jan 1992;92(1):7. 

Editorial. 

1768. Malloch K, Conovaloff A. Patient classification 

systems, Part 1: The third generation. J Nurs Adm. 

Jul-Aug 1999;29(7-8):49-56. No association tested. 

1769. Malloch K, Neeld AP, McMurry C, Meeks L, 

Wallach M, Williams S, Conovaloff A. Patient 

classification systems, Part 2: The third generation. J 

Nurs Adm. Sep 1999;29(9):33-42. Not eligible 

outcomes. 

1770. Malone JA. Milieu and part-time nurses: a 

contradiction? J Psychosoc Nurs Ment Health Serv. 

Jul 1994;32(7):7. Editorial.

1771. Malone RE. Night shifts and breast cancer risk: policy 

implications. J Emerg Nurs. Apr 2002;28(2):169-171. 

Review. 

1772. Mamaril M. The official ASPAN position: ICU 

overflow patients in the PACU. J Perianesth Nurs. 

Aug 2001;16(4):274-277. Comment. 

1773. Mancher T. A better model by design ... and it works! 

Nurs Manage. May 2001;32(5):45-47. Comment. 

1774. Manchester A. New care model threatens patient 

safety. Nurs N Z. Oct 1997;3(9):26-27. News. 

1775. Manheim LM, Feinglass J, Shortell SM, Hughes EF. 

Regional variation in Medicare hospital mortality. 

Inquiry. Spring 1992;29(1):55-66. Not eligible 

exposure. 

1776. Manias E, Aitken R, Dunning T. Medication 

management by graduate nurses: before, during and 

following medication administration. Nurs Health Sci. 

Jun 2004;6(2):83-91. Not eligible target population.

1777. Manias E, Aitken R, Peerson A, Parker J, Wong K. 

Agency nursing work in acute care settings: 

perceptions of hospital nursing managers and agency 

nurse providers. J Clin Nurs. Jul 2003;12(4):457-466. 

Not eligible target population. 

1778. Manias E, Aitken R, Peerson A, Parker J, Wong K. 

Agency-nursing work: perceptions and experiences of 

agency nurses. Int J Nurs Stud. Mar 2003;40(3):269-

279. Not eligible target population.

1779. Manne SL, Jacobsen PB, Redd WH. Assessment of 

acute pediatric pain: do child self-report, parent 

ratings, and nurse ratings measure the same 

phenomenon? Pain. Jan 1992;48(1):45-52. Not 

eligible exposure. 

1780. Manning ML, Archibald LK, Bell LM, Banerjee SN, 

Jarvis WR. Serratia marcescens transmission in a 

pediatric intensive care unit: a multifactorial 

occurrence. Am J Infect Control. Apr 

2001;29(2):115-119. Not eligible exposure. 

1781. Manojlovich M, Spence Laschinger HK. The 

relationship of empowerment and selected personality 

characteristics to nursing job satisfaction. J Nurs 

Adm. Nov 2002;32(11):586-595. Not eligible 

exposure. 

1782. Mansheim P. Short-term psychiatric inpatient 

treatment of preschool children. Hosp Community 

Psychiatry. Jun 1990;41(6):670-672. Not eligible 

exposure. 

1783. Mansley A. Caring for rape survivors. Nurs Times. 

Apr 29-May 5 1998;94(17):24-26. Case Reports. 

1784. Mansson ME, Dykes AK. Practices for preparing 

children for clinical examinations and procedures in 

Swedish pediatric wards. Pediatr Nurs. May-Jun 

2004;30(3):182-187, 229. Not eligible target 

population. 

1785. Manthey M. Staffing and productivity. Nurs Manage. 

Dec 1991;22(12):20-21. Comment. 

1786. Manthey M. A core incremental staffing plan. J Nurs 

Adm. Sep 2001;31(9):424-425. Comment. 

1787. Maras V. Implementing cluster staffing. One 

manager's experience. Aorn J. Apr 1992;55(4):1074-

1077, 1080. Comment. 

1788. Marasovic C, Kenney C, Elliott D, Sindhusake D. 

Attitudes of Australian nurses toward the 

implementation of a clinical information system. 

Comput Nurs. Mar-Apr 1997;15(2):91-98. Not 

eligible target population. 

1789. Marchewka AE. The demand for hospital nursing 

personnel. DAI-A 55/07, p. 2087, Jan 1995. 

1993:AAT 9432310. Not eligible outcomes.

347. Marcus N. Night duty: sleeping sickness. Nurs Stand. 

Feb 22-28 1995;9(22):56. Comment.

348. Marden W. One bright initiative. Mater Manag Health 

Care. Jul 2002;11(7):20-22, 24. Comment. 

349. Mark BA. Characteristics of nursing practice models. 

J Nurs Adm. Nov 1992;22(11):57-63. Not eligible 

outcomes. 

1790. Mark BA, Salyer J, Harless DW. What explains 

nurses' perceptions of staffing adequacy? J Nurs 

Adm. May 2002;32(5):234-242. Not eligible 

exposure. 

1791. Mark BA, Salyer J, Wan TT. Market, hospital, and 

nursing unit characteristics as predictors of nursing 

unit skill mix: a contextual analysis. J Nurs Adm. Nov 

2000;30(11):552-560. Not eligible outcomes. 
B-53 

1792. Markey DW. Applying the synergy model: clinical 

strategies. Crit Care Nurse. Jun 2001;21(3):72-76. 

Comment. 

1793. Markwick A. Defining what nursing is. Nurs Times. 

Mar 11-17 1998;94(10):21. Case Reports. 

1794. Maroun VM. A look at licensure of foreign-educated 

nurses. Issues 1991;12(2):7. Not relevant. 

1796. Marra C, Nimmo CR, Jewesson P. A prospective 

survey of knowledge and perceptions of ondansetron: 

what do health care workers know about this drug? 

Can J Hosp Pharm. Dec 1995;48(6):336-342. Not 

eligible exposure. 

1797. Marson R, Taylor DM, Ashby K, Cassell E. Victorian 

Emergency Minimum Dataset: factors that impact 

upon the data quality. Emerg Med Australas. Apr 

2005;17(2):104-112. Not eligible exposure. 

1798. Martin B, Mathisen L. Use of physical restraints in 

adult critical care: a bicultural study. Am J Crit Care. 

Mar 2005;14(2):133-142. Not eligible exposure. 

1799. Martin BJ. A successful approach to absenteeism. 

Nurs Manage. Aug 1990;21(8):45-48. Not eligible 

exposure. 

1800. Martin PA, Gustin TJ, Uddin DE, Risner P. 

Organizational dimensions of hospital nursing 

practice: longitudinal results. J Nurs Adm. Dec 

2004;34(12):554-561. No association tested. 

1801. Martin SD. Striking nurses win from coast to coast. 

Am Nurse. Mar-Apr 2002;34(2):8. Comment. 

1802. Martinello RA, Jones L, Topal JE. Correlation 

between healthcare workers' knowledge of influenza 

vaccine and vaccine receipt. Infect Control Hosp 

Epidemiol. Nov 2003;24(11):845-847. Not eligible 

exposure. 

1803. Martorella C. Implementing a patient classification 

system. Nurs Manage. Dec 1996;27(12):29-31. No 

association tested. 

1804. Mason DJ. Nursing science: who cares? Am J Nurs. 

Dec 1999;99(12):7. Editorial. 

1805. Mason DJ. How many patients are too many? Am J 

Nurs. Nov 2003;103(11):7. Editorial. 

1806. Mason DJ. That's nursing! No, that's appalling. Am J 

Nurs. Jul 2004;104(7):11. Editorial. 

1807. Mason DJ, Kany KA. The state of the science: focus 

on work environments. Am J Nurs. Mar 

2005;105(3):33-34. Comment. 

1808. Masta O. Night cover. Nurs Stand. Aug 20-26 

2003;17(49):16-18. Comment. 

1809. Mateo MA, Smith SP. Workforce diversity in 

hospitals. Nurs Leadersh Forum. Summer 

2003;7(4):143-149. Not eligible outcomes. 

1810. Mathew LJ, Gutsch HM, Hackney NW, Munsat EM. 

Promoting quality and cost-effective care to 

geropsychiatric patients. Issues Ment Health Nurs. 

Mar-Apr 1994;15(2):169-185. Not eligible exposure.

1811. Mathias JM. Sharing OR staff can help meet 

unpredictable staffing demands. OR Manager. May 

2005;21(5):1, 12, 14. Comment. 

1812. Mathias Judith M, Patterson P. Leaders find ways to 

tackle staff shortage. OR Manager. Sep 

2002;18(9):20-22, 26. Comment. 

1813. Mathur K, Bhattacharya SK, Kashyap SK. Behavioral 

effects and body activity level in female hospital staff 

nurses during work hour. J Hum Ergol (Tokyo). Jun 

1995;24(1):1-11. Not eligible target population. 

1814. Mattera MD. Outside the box. Rn. Apr 1997;60(4):7. 

Editorial. 

1815. Mattera MD. Strike? Rn. Nov 1999;62(11):7. 

Editorial. 

1816. Mattera MD. Guts. Rn. Mar 2000;63(3):7. Editorial. 

1817. Matthiesen V, Lamb KV, McCann J, Hollinger-Smith 

L, Walton JC. Hospital nurses' views about physical 

restraint use with older patients. J Gerontol Nurs. Jun 

1996;22(6):8-16. Not eligible exposure. 

1818. Maul I, Laubli T, Klipstein A, Krueger H. Course of 

low back pain among nurses: a longitudinal study 

across eight years. Occup Environ Med. Jul 

2003;60(7):497-503. Not eligible exposure. 

1819. Maunder RG, Lancee WJ, Rourke S, Hunter JJ, 

Goldbloom D, Balderson K, Petryshen P, Steinberg 

R, Wasylenki D, Koh D, Fones CS. Factors 

associated with the psychological impact of severe 

acute respiratory syndrome on nurses and other 

hospital workers in Toronto. Psychosom Med. NovDec 2004;66(6):938-942. Not eligible exposure. 

1820. Maurier WL, Northcott HC. Job uncertainty and 

health status for nurses during restructuring of health 

care in Alberta. West J Nurs Res. Aug 

2000;22(5):623-641. Not eligible outcomes. 

1821. Maxam-Moore VA, Wilkie DJ, Woods SL. 

Analgesics for cardiac surgery patients in critical 

care: describing current practice. Am J Crit Care. Jan 

1994;3(1):31-39. Not eligible exposure. 

1822. Maxwell M. Are you an HR star? Test your 

knowledge. Nurs Econ. Jul-Aug 2004;22(4):214-215. 

Comment. 

1823. May DD, Grubbs LM. The extent, nature, and 

precipitating factors of nurse assault among three 

groups of registered nurses in a regional medical 

center. J Emerg Nurs. Feb 2002;28(1):11-17. Not 

eligible exposure. 

1824. May J, Ellis-Hill C, Payne S. Gatekeeping and 

legitimization: how informal carers' relationship with 

health care workers is revealed in their everyday 

interactions. J Adv Nurs. Nov 2001;36(3):364-375. 

Not eligible target population. 

1825. Mayer C, Andrusyszyn MA, Iwasiw C. Codman 

Award Paper: self-efficacy of staff nurses for health 

promotion counselling of patients at risk for stroke. 

Axone. Jun 2005;26(4):14-21. Not eligible exposure.

1826 Mayer GG, Buckley RF, White TL. Direct nursing 

care given to patients in a subacute rehabilitation 

center. Rehabilitation Nursing Mar-Apr 

1990;15(2):86-8. Not relevant. 

1827. Mayer T, Cates R, Flinn R. Fee-for-service nursing: 

an idea ready to be tested. ED Manag. Dec 

1998;10(12):142-144. Comment. 

1828. Mayer TA, Cates RJ, Mastorovich MJ, Royalty DL. 

Emergency department patient satisfaction: customer 

service training improves patient satisfaction and 

ratings of physician and nurse skill. J Healthc Manag. 

Sep-Oct 1998;43(5):427-440; discussion 441-422. 

Not eligible exposure. 
B-54 

1829. Mayer TA, Zimmermann PG. ED customer 

satisfaction survival skills: one hospital's experience. 

J Emerg Nurs. Jun 1999;25(3):187-191. Not eligible 

exposure. 

1830. Mayne JE. Teaching path balances LOS, education 

needs for MI. Hosp Case Manag. Nov 

1995;3(11):171-174. Not eligible exposure. 

1831. Mayo AM, Duncan D. Nurse perceptions of 

medication errors: what we need to know for patient 

safety. J Nurs Care Qual. Jul-Sep 2004;19(3):209-

217. Not eligible exposure. 

1832. McAlpine LC, Cargill G. Effects of summer 

employment on student nurses: implications for 

recruitment and retention of staff nurses. Canadian 

journal of nursing administration Sep-Oct 

1992;5(3):23-7. Not relevant. 

1833. McBride L, Walden-McBride D. Balancing the 'heart' 

of patient care. Home Healthc Nurse. Jul-Aug 

1995;13(4):46-49. Not eligible target population. 

1834. McCabe C. Nurse-patient communication: an 

exploration of patients' experiences. J Clin Nurs. Jan 

2004;13(1):41-49. Not eligible exposure. 

1835. McCann E, Bowers L. Training in cognitive 

behavioural interventions on acute psychiatric 

inpatient wards. J Psychiatr Ment Health Nurs. Apr 

2005;12(2):215-222. Not eligible target population. 

1836. McCann TV. Willingness to provide care and 

treatment for patients with HIV/AIDS. J Adv Nurs. 

May 1997;25(5):1033-1039. Not eligible target 

population. 

1837. McCartney PR. Centering pregnancy: a renaissance in 

prenatal care? MCN Am J Matern Child Nurs. JulAug 2004;29(4):261. Comment. 

1838. McCarty MC, Zander KM, Hennrikus DJ, Lando HA. 

Barriers among nurses to providing smoking 

cessation advice to hospitalized smokers. Am J 

Health Promot. Nov-Dec 2001;16(2):85-87, ii. Not 

eligible exposure. 

1839. McCloskey JM. Nurse staffing and patient outcomes. 

Nurs Outlook. Sep-Oct 1998;46(5):199-200. Review.

1840. McConnell EA. American registered nurse medical 

device education: a comparison of simple and 

complex devices. Biomed Instrum Technol. Nov-Dec 

1995;29(6):520-526. Not eligible exposure.

1841. McConnell EA. How and what staff nurses learn 

about the medical devices they use in direct patient 

care. Res Nurs Health. Apr 1995;18(2):165-172. Not 

eligible exposure. 

1842. McConnell EA. Patients, machines, and staff nurses. 

Nursingconnections. Summer 1997;10(2):5-11. Not 

eligible exposure. 

1843. McConnell EA, Cattonar M, Manning J. Australian 

registered nurse medical device education: a 

comparison of simple vs. complex devices. J Adv 

Nurs. Feb 1996;23(2):322-328. Not eligible target 

population. 

1844. McConnell EA, Fletcher J, Nissen JH. A comparison 

of Australian and American registered nurses' use of 

life-sustaining medical devices in critical care and 

high-dependency units. Heart Lung. Sep-Oct 

1993;22(5):421-427. Not eligible target population. 

1845. McConnell EA, Fletcher J, Nissen JH. Medical device 

education among Australian registered nurses. A 

comparison of agency and hospital nurses. Int J 

Technol Assess Health Care. Summer 

1995;11(3):585-594. Not eligible target population. 

1846. McCormack B. A case study identifying nursing 

staffs' perception of the delivery method of nursing 

care in practice on a particular ward. J Adv Nurs. Feb 

1992;17(2):187-197. Not eligible target population. 

1847. McCormack PJ, Cooper R, Sutherland S, Stewart H. 

The safe use of syringe drivers for palliative care: an 

action research project. Int J Palliat Nurs. Dec 

2001;7(12):574-580. Not eligible target population. 

1848. McCoy AK. Developing self-scheduling in critical 

care. Dimens Crit Care Nurs. May-Jun 

1992;11(3):152-156. No association tested. 

1849. McCrea J. Four honoured for rescue role. N Z Nurs J. 

Jun 1992;85(5):9, 34. News. 

1850. McCrea MA, Atkinson M, Bloom T, Merkh K, 

Najera IL, Smith C. The healing energy of 

relationships. A journey to excellence. Nurs Adm Q. 

Jul-Sep 2003;27(3):240-248. Comment. 

1851. McCue M, Mark BA, Harless DW. Nurse staffing, 

quality, and financial performance. J Health Care 

Finance. Summer 2003;29(4):54-76. Not eligible 

outcomes. 

1852. McDaniel AM, Kristeller JL, Hudson DM. Chart 

reminders increase referrals for inpatient smoking 

cessation intervention. Nicotine Tob Res. Jun 

1999;1(2):175-180. Not eligible exposure. 

1853. McDaniel C. Organizational culture and ethics work 

satisfaction. J Nurs Adm. Nov 1995;25(11):15-21. 

Not eligible exposure. 

1854. McDonald DD. Gender and ethnic stereotyping and 

narcotic analgesic administration. Res Nurs Health. 

Feb 1994;17(1):45-49. Not eligible exposure. 

1855. McDonald J. Justifying our practice. Can Nurse. Oct 

1998;94(9):47-48. Comment.

1856. McDonald S. An ethical dilemma: risk versus 

responsibility. J Psychosoc Nurs Ment Health Serv. 

Jan 1994;32(1):19-25. No association tested. 

1857. McElligott D, Holz MB, Carollo L, Somerville S, 

Baggett M, Kuzniewski S, Shi Q. A pilot feasibility 

study of the effects of touch therapy on nurses. J N Y 

State Nurses Assoc. Spring-Summer 2003;34(1):16-

24. Not eligible exposure. 

1858. McEndree B. Shoes. Okla Nurse. Oct-Dec 

1996;41(4):13. Comment. 

1859. McGavock MB. Third Annual Nursing 

Administration Recognition Program. Third 

Place...Flextra and incentive compensation. J Nurs 

Adm. Apr 1991;21(4):16. Comment. 

1860. McGillis Hall L, Doran D, Baker GR, Pink GH, 

Sidani S, O'Brien-Pallas L, Donner GJ. Nurse staffing 

models as predictors of patient outcomes. Med Care. 

Sep 2003;41(9):1096-1109. Not eligible association 

presentation. 

1861. McGillis Hall L, Doran D, Pink GH. Nurse staffing 

models, nursing hours, and patient safety outcomes. J 

Nurs Adm. Jan 2004;34(1):41-45. Not eligible 

association presentation. 
B-55 

1862. McGloin S, Knowles J. An evaluation of the critical 

care assistant role within an acute NHS Trust Critical 

Care Unit. Nurs Crit Care. Jul-Aug 2005;10(4):210-

215. Not eligible exposure. 

1863. McGregor LA. Short, shorter, shortest: continuing to 

improve the hospital stay for mothers and newborns. 

MCN Am J Matern Child Nurs. Jul-Aug 

1996;21(4):191-196. Comment. 

1864. McGuire LC, Bell AZ. Developing an enhanced 

minor injury unit for support of urban festivities. Eur 

J Emerg Med. Sep 2001;8(3):193-197. Not eligible 

exposure. 

1865. McGuire T. Shiftwork. How to cope with life in the 

shadows. Alta RN. Oct 2001;57(5):9. Comment.

1866. McHugh ML. Cost-effectiveness of clustered unit vs. 

unclustered nurse floating. Nursing Economics NovDec 1997;15(6):294-300. Not relevant. 

1867. McKay S, Smith SY. "What are they talking about? Is 

something wrong?" Information sharing during the 

second stage of labor. Birth. Sep 1993;20(3):142-147. 

Not eligible exposure.

1868. McKenna H, Hasson F. A study of skill mix issues in 

midwifery: a multimethod approach. J Adv Nurs. Jan 

2002;37(1):52-61. Not eligible target population. 

1869. McKenna HP. Nursing skill mix substitutions and 

quality of care: an exploration of assumptions from 

the research literature. J Adv Nurs. Mar 

1995;21(3):452-459. Not eligible target population.

1870. McKiel E. Impact of organizational restructuring on 

nurses' facilitation of parental participatory care. Can 

J Nurs Leadersh. Jan-Feb 2002;15(1):14-17. 

Comment. 

1871. McKillop A. Casual nurses meet a demand. Nurs N Z. 

Nov 1995;1(10):20-21. Not eligible target population. 

1872. McKinley A. Health care providers and facilities 

issue brief: health facilities: year end report-2004. 

Issue Brief Health Policy Track Serv. Dec 31 2004:1-

12. Not eligible target population. 

1873. McKnight JD, Glass DC. Perceptions of control, 

burnout, and depressive symptomatology: a 

replication and extension. J Consult Clin Psychol. Jun 

1995;63(3):490-494. Comment. 

1874. McLain SR. Hospital workforce shortages--a glimpse 

at the reasons and possible solutions. Okla Nurse. 

Jun-Aug 2003;48(2):14-16. Comment. 

1875. McLaren BJ. Limitations on employment protection 

provided by the Americans with Disabilities Act 

(ADA). Colo Nurse. Dec 1998;98(4):20-21. Legal 

Cases. 

1876. McLaughlin FE, Barter M, Thomas SA, Rix G, 

Coulter M, Chadderton H. Perceptions of registered 

nurses working with assistive personnel in the United 

Kingdom and the United States. Int J Nurs Pract. Feb 

2000;6(1):46-57. Not eligible target population. 

1877. McLennan CA. Workload measurement tool for an 

integrated OR/PACU. Can Oper Room Nurs J. MarApr 1994;12(1):28-31. Comment.

1878. McLeod A. Support role spreads the workload in 

intensive care. Nurs Times. Jul 19-25 

2001;97(29):40-41. Comment. 

1879. McMillan SC, Tittle M, Hagan S, et al. Knowledge 

and attitudes of nurses in veterans hospitals about 

pain management in patients with cancer. Oncology 

nursing forum Oct 2000;27(9):1415-23. Not relevant.

1880. McMullin JP, Cook DJ, Meade MO, Weaver BR, 

Letelier LM, Kahmamoui K, Higgins DA, Guyatt 

GH. Clinical estimation of trunk position among 

mechanically ventilated patients. Intensive Care Med. 

Mar 2002;28(3):304-309. Not eligible exposure. 

1881. McNeal LJ. Should a staff nurse's age be a 

consideration in making patient and shift 

assignments? Con. MCN Am J Matern Child Nurs. 

Mar-Apr 2005;30(2):85. Comment. 

1882. McNees P, Dow KH, Loerzel VW. Application of the 

CuSum technique to evaluate changes in recruitment 

strategies. Nursing research Nov-Dec 

2005;54(6):399-405. Not relevant. 

1883. McSharry M. Quality of life: but in whose 

judgement? Edtna Erca J. Jul-Sep 1996;22(3):15-18. 

Not eligible target population. 

1884. McVay K. Bottom line concerns eroding quality 

health care. Revolution. Winter 1997;7(4):11. 

Comment. 

1885. McWilliam CL, Stewart M, Vingilis E, Hoch J, 

Ward-Griffin C, Donner A, Browne G, Coyte P, 

Anderson K. Flexible client-driven in-home case 

management: an option to consider. Care Manag J. 

Summer 2004;5(2):73-86. Not eligible target 

population. 

1886. Medland JJ, Marcon J, Curia M. Sabbatical leave: a 

creative retention strategy. Crit Care Nurse. Dec 

1994;14(6):63-67. Not eligible exposure. 

1887. Mee CL, Cirone NR, Levinger CV. MERG: 

medication event rating grid. Nurs Manage. Apr 

1996;27(4):34, 36, 38. Comment. 

1888. Meehan AJ, Carey N, Haynes DE. A clinical pathway 

for the secondary diagnosis of alcohol misuse: 

implications for the orthopaedic patient. Orthop Nurs. 

Nov-Dec 1998;17(6):49-54, 64. Not eligible 

exposure. 

1889. Meehan TC. Careful nursing: a model for 

contemporary nursing practice. J Adv Nurs. Oct 

2003;44(1):99-107. Not eligible target population. 

1890. Mehn J, Haas D. What to tell families about drug 

errors. Hosp Health Netw. Feb 1999;73(2):30. News. 

1891. Meikle K. The role of health care assistants in 

hospitals. Nurs N Z. Feb 2002;8(1):18-19. Not 

eligible target population. 

1892. Melchior ME, Philipsen H, Abu-Saad HH, Halfens 

RJ, van de Berg AA, Gassman P. The effectiveness of 

primary nursing on burnout among psychiatric nurses 

in long-stay settings. J Adv Nurs. Oct 

1996;24(4):694-702. Not eligible target population. 

1893. Melchior ME, van den Berg AA, Halfens R, Huyer 

Abu-Saad H, Philipsen H, Gassman P. Burnout and 

the work environment of nurses in psychiatric longstay care settings. Soc Psychiatry Psychiatr 

Epidemiol. Apr 1997;32(3):158-164. Not eligible 

target population. 

1894. Melifonwu R. Ward leaders. Miracle worker. 

Interview by Jenine Willis. Nurs Times. Jun 23-29 

1999;95(25):30-31. Interview. 
B-56 

1895. Meltzer LS, Huckabay LM. Critical care nurses' 

perceptions of futile care and its effect on burnout. 

Am J Crit Care. May 2004;13(3):202-208. Not 

eligible exposure. 

1896. Melville E. Flexible working: banking your assets. 

Nurs Stand. Apr 20-26 1994;8(30):90-91. Not eligible 

target population. 

1897. Menzel NN, Brooks SM, Bernard TE, Nelson A. The 

physical workload of nursing personnel: association 

with musculoskeletal discomfort. Int J Nurs Stud. 

Nov 2004;41(8):859-867. Not eligible Exposure. 

1898. Merkouris A, Papathanassoglou ED, Lemonidou C. 

Evaluation of patient satisfaction with nursing care: 

quantitative or qualitative approach? Int J Nurs Stud. 

May 2004;41(4):355-367. Not eligible target 

population. 

1899. Merkouris A, Papathanassoglou ED, Pistolas D, 

Papagiannaki V, Floros J, Lemonidou C. Staffing and 

organisation of nursing care in cardiac intensive care 

units in Greece. Eur J Cardiovasc Nurs. Jul 

2003;2(2):123-129. Not eligible target population.

1900. Merrion P, Ngeo C. Nursing relief. In answer to 

hospital shortages, bill would allow some foreign 

nurses to work in U.S. Mod Healthc. Nov 10 

1997;27(45):56. News. 

1901. Metcalf KM. The helper model: nine ways to make it 

work. Nurs Manage. Dec 1992;23(12):40-43. 

Comment. 

1902. Meurier CE, Vincent CA, Parmar DG. Learning from 

errors in nursing practice. J Adv Nurs. Jul 

1997;26(1):111-119. Not eligible target population. 

1903. Meyer MS, Siegel M. How much is enough? Agency 

nurse orientation. J Nurs Staff Dev. Jan-Feb 

1996;12(1):41-42. Comment. 

1904. Meyers S. Real men choose nursing. Nursing schools 

and hospitals target men in their recruitment efforts. 

Trustee. May 2003;56(5):18-21, 11. News. 

1905. Michael JE. Is it patient abandonment--or not? Rn. 

Aug 2002;65(8):67-70. Comment. 

1906. Michie S, Ridout K, Johnston M. Stress in nursing 

and patients' satisfaction with health care. Br J Nurs. 

Sep 12-25 1996;5(16):1002-1006. Not eligible target 

population. 

1907. Middleton S, Lumby J. Comparing professional and 

patient outcomes for the same episode of care. Aust J 

Adv Nurs. Sep-Nov 1999;17(1):22-27. Not eligible 

target population. 

1908. Milette IH, Carnevale FA. I'm trying to heal...noise 

levels in a pediatric intensive care unit. Dynamics. 

Winter 2003;14(4):14-21. Not eligible exposure. 

1909. Millar B. Behind every great nurse. Nurs Times. Mar 

22-28 2001;97(12):24-26. Not eligible target 

population. 

1910. Miller BK, Haber J, Byrne MW. The experience of 

caring in the acute care setting: patient and nurse 

perspectives. NLN Publ. Apr 1992(15-2465):137-156. 

No association tested. 

1911. Miller D. Comparisons of pain ratings from 

postoperative children, their mothers, and their 

nurses. Pediatr Nurs. Mar-Apr 1996;22(2):145-149. 

Not eligible exposure. 

1912. Miller DL. Post procedural interventional cardiology 

patients on the progressive care unit. Prog Cardiovasc 

Nurs. Winter 1999;14(1):14-17, 36. Not eligible 

exposure. 

1913. Miller E. Record snowstorm transforms hospitals to 

RN "dorms". Nurs Spectr (Wash D C). Jan 16 

1996;6(2):4. Comment. 

1914. Miller K. The road taken. Revolution. Oct-Nov 

2003;4(5):18-23. Comment. 

1915. Miller KH, Grindel CG, Patsdaughter CA. Risk 

classification, clinical outcomes, and the use of 

nursing resources for cardiac surgery patients. 

Dimens Crit Care Nurs. Mar-Apr 1999;18(2):44-49. 

Not eligible exposure. 

1916. Miller KH, Grindel CG, Patsdaughter CA. Cardiac 

surgery's calculated risk. Nurs Manage. Jul 

1999;30(7):34-36, 38-40. No association tested. 

1917. Miller SF, Finley RK, Waltman M, Lincks J. Burn 

size estimate reliability: a study. J Burn Care Rehabil. 

Nov-Dec 1991;12(6):546-559. Not eligible exposure. 

1918. Mills-Senn P. Staffing. Avoiding culture clash. As the 

number of foreign-born nurses climbs, executives 

look for ways to bridge cultural gap. Hosp Health 

Netw. Apr 2005;79(4):30, 32. News. 

1919. Milstead JA. Leapfrog Group: a prince in disguise or 

just another frog? Nurs Adm Q. Summer 

2002;26(4):16-25. Review. 

1920. Minichiello TM, Auerbach AD, Wachter RM. 

Caregiver perceptions of the reasons for delayed 

hospital discharge. Eff Clin Pract. Nov-Dec 

2001;4(6):250-255. Not eligible exposure. 

1921. Minnick A, Leahey M, Pischke-Winn K. The impact 

of patient point-of-view pharmacy delivery on labor 

and quality. Nurs Econ. Jan-Feb 1994;12(1):45-50. 

Not eligible exposure. 

1922. Minnick A, Leipzig RM. The restraint match-up. 

Three lessons show how nurse leaders can influence 

the use of physical restraints. Nurs Manage. Mar 

2001;32(3):37-39. Comment. 

1923. Minton JA, Creason NS. Evaluation of admission 

nursing diagnoses. Nurs Diagn. Jul-Sep 

1991;2(3):119-125. Not eligible outcomes.

1924. Miracle K. Restraints: friend or foe? Ky Hosp Mag. 

Winter 1991;8(1):10-11. Comment.

1925. Mistiaen P, van Harteveld J. A comment on the Duke 

University Center Health Profile. Med Care. Jun 

1992;30(6):471-472 .Editorial. 

1926. Mitchell A, Van Berkel C, Adam V, Ciliska D, 

Sheppard K, Baumann A, Underwood J, Walter S, 

Gafni A, Edwards N, et al. Comparison of liaison and 

staff nurses in discharge referrals of postpartum 

patients for public health nursing follow-up. Nurs 

Res. Jul-Aug 1993;42(4):245-249. Not eligible 

exposure. 

1927. Mitchell D, Grindel CG, Laurenzano C. Sexual abuse 

assessment on admission by nursing staff in general 

hospital psychiatric settings. Psychiatr Serv. Feb 

1996;47(2):159-164. Not eligible exposure. 

1928. Mitchell GJ, Closson T, Coulis N, Flint F, Gray B. 

Patient-focused care and human becoming thought: 

connecting the right stuff. Nurs Sci Q. Jul 

2000;13(3):216-224. Case Reports. 
B-57 

1929. Mitchell PH, Lang NM. Nurse staffing: a structural 

proxy for hospital quality? Med Care. Jan 

2004;42(1):1-3. Comment. 

1930. Moait S. 10 hr night duty win. Lamp. May 

1996;53(4):10-12. Comment. 

1931. Mobberley T. NT/3M National Nursing Awards. 

Family favourite. Nurs Times. Dec 29-2000 Jan 5 

1999;95(50):34-35. Comment. 

1932. Moens G, Mylle G, Johannik K, Van Hoof R, Helsen 

G. Analysing and interpreting routinely collected data 

on sharps injuries in assessing preventative actions. 

Occup Med (Lond). Jun 2004;54(4):245-249. Not 

eligible target population. 

1933. Molloy P. Promoting night shift. Nurs N Z. Aug 

1995;1(7):13-15. Not eligible target population. 

1934. Molzahn AE, Northcott HC, Dossetor JB. Quality of 

life of individuals with end stage renal disease: 

perceptions of patients, nurses, and physicians. Anna 

J. Jun 1997;24(3):325-333; discussion 334-325. Not 

eligible exposure. 

1935. Monet SS. Nurses indicted ... a wave of the future? 

Hawaii Nurse (Honol). Jul-Aug 1997;4(4):1, 5. Legal 

Cases. 

1936. Mongeau C. Voices from Colorado. Nursing. Jun 

1998;28(6):48-49. Case Reports. 

1937 Moody L, Snyder PE. Hospital provider satisfaction 

with a new documentation system. Nursing 

Economics Jan-Feb 1995;13(1):24-31. Not relevant. 

1938. Moody LE, Slocumb E, Berg B, Jackson D. 

Electronic health records documentation in nursing: 

nurses' perceptions, attitudes, and preferences. 

Comput Inform Nurs. Nov-Dec 2004;22(6):337-344. 

Not eligible exposure. 

1939. Moolenaar RL, Crutcher JM, San Joaquin VH, Sewell 

LV, Hutwagner LC, Carson LA, Robison DA, 

Smithee LM, Jarvis WR. A prolonged outbreak of 

Pseudomonas aeruginosa in a neonatal intensive care 

unit: did staff fingernails play a role in disease 

transmission? Infect Control Hosp Epidemiol. Feb 

2000;21(2):80-85. Not eligible exposure. 

1940. Moons M, Kerkstra A, Biewenga T. Specialized 

home care for patients with AIDS: an experiment in 

Rotterdam, The Netherlands. J Adv Nurs. Jun 

1994;19(6):1132-1140. Not eligible target population. 

1941. Moore K, Lynn MR, McMillen BJ, Evans S. 

Implementation of the ANA report card. J Nurs Adm. 

Jun 1999;29(6):48-54. Not eligible association 

presentation. 

1942. Moore MM, Nguyen D, Nolan SP, Robinson SP, 

Ryals B, Imbrie JZ, Spotnitz W. Interventions to 

reduce decibel levels on patient care units. Am Surg. 

Sep 1998;64(9):894-899. Not eligible exposure. 

1943. Moran J. Finally, the 38-hour week. Qld Nurse. NovDec 1994;13(6):6-8. Comment. 

1944. Morath J, Fleischmann R, Boggs G. A missing 

consideration: the psychiatric patient classification for 

scheduling-staffing systems. Perspect Psychiatr Care. 

1990;25(3-4):40-47. Not eligible exposure. 

1945. Moreno R, Reis Miranda D. Nursing staff in intensive 

care in Europe: the mismatch between planning and 

practice. Chest. Mar 1998;113(3):752-758. Not 

eligible target population. 

1946. Morgan SP, DeRose C. Reduce workload intensity 

with PCTs. Nurs Manage. Nov 2003;34(11):9. Not 

eligible exposure. 

1947. Morita T, Miyashita M, Kimura R, Adachi I, Shima 

Y. Emotional burden of nurses in palliative sedation 

therapy. Palliat Med. Sep 2004;18(6):550-557. Not 

eligible target population. 

1948. Morita T, Shima Y, Miyashita M, Kimura R, Adachi 

I. Physician- and nurse-reported effects of intravenous 

hydration therapy on symptoms of terminally ill 

patients with cancer. J Palliat Med. Oct 

2004;7(5):683-693. Not eligible target population. 

1949. Morley B. Reclaiming the night. Nurs Times. Jun 29-

Jul 5 1994;90(26):54-55. Comment.

1950. Morohashi Y. Questions concerning medical care 

provided in hospitals. Jpn Hosp. Jul 1992;11:1-9. Not 

eligible target population. 

1951. Morrison AL, Beckmann U, Durie M, Carless R, 

Gillies DM. The effects of nursing staff inexperience 

(NSI) on the occurrence of adverse patient 

experiences in ICUs. Aust Crit Care. Aug 

2001;14(3):116-121. Not eligible target population. 

1952. Morrison M. The paradigm shift from traditional 

obstetrics to single room maternity care. Fla Nurse. 

Mar 1993;41(3):7. Comment. 

1953. Morrison P. A multidimensional scalogram analysis 

of the use of seclusion in acute psychiatric settings. J 

Adv Nurs. Jan 1990;15(1):59-66. Not eligible target 

population. 

1954. Morrison P, Lehane M. The effect of staffing levels 

on the use of seclusion. J Psychiatr Ment Health Nurs. 

1995;2(6):365-366. Comment. 

1955. Morrison P, Lehane M. A study of the official records 

of seclusion. Int J Nurs Stud. Apr 1996;33(2):223-

235. Not eligible target population. 

1956. Morrison P, Phillips C, Burnard P. Staff and patient 

satisfaction in a forensic unit. J Psychiatr Ment Health 

Nurs. 1996;3(1):67-69. Comment. 

1957. Morrison WE, Haas EC, Shaffner DH, Garrett ES, 

Fackler JC. Noise, stress, and annoyance in a 

pediatric intensive care unit. Crit Care Med. Jan 

2003;31(1):113-119. Not eligible exposure. 

1958. Morrissey J. Quality vs. quantity. IOM report: 

hospitals must cut back workload and hours of nurses 

to maintain patient safety. Mod Healthc. Nov 10 

2003;33(45):8, 11. News. 

1959. Morrow KL. Using staffing and scheduling 

information to support change. Nurs Manage. May 

1994;25(5):78-80. Comment.

1960. Morton HR, Himes JK, Stevens B. The Foreign Nurse 

Program: an innovative NCLEX review. J Contin 

Educ Nurs. Mar-Apr 1992;23(2):81-82. Comment. 

1961. Moskowitz DB. Marketplace. Why hospitals' staffing 

woes today are unlike previous nurse shortages. Med 

Health. Oct 30 2000;54(42):suppl 1-2. Comment. 

1962. Moss J, Xiao Y. Improving operating room 

coordination: communication pattern assessment. J 

Nurs Adm. Feb 2004;34(2):93-100. Not eligible 

exposure. 
B-58 

1963. Mrayyan MT. Perceptions of jordanian head nurses of 

variables that influence the quality of nursing care. J 

Nurs Care Qual. Jul-Sep 2004;19(3):276-279. Not 

eligible target population. 

1964. Mudge B, Helferty M, Wallace L, Ouwendyk M. 

Nocturnal hemodialysis (NHD) adapted to the incentre setting--a pilot study. J Cannt. Winter 

1998;8(1):30-31. Not eligible target population. 

1965. Muller K, Schwesig R, Leuchte S, Riede D. 

[Coordinative treatment and quality of life - a 

randomised trial of nurses with back pain]. 

Gesundheitswesen. Oct 2001;63(10):609-618. Not 

eligible target population. 

1966. Murphy CL, McLaws ML. Who coordinates infection 

control programs in Australia? Am J Infect Control. 

Jun 1999;27(3):291-295. Not eligible target 

population. 

1967. Murphy F. Stress among nephrology nurses in 

Northern Ireland. Nephrol Nurs J. Jul-Aug 

2004;31(4):423-431. Not eligible target population. 

1968. Murray MG, Snyder JC. When staff are assaulted. A 

nursing consultation support service. J Psychosoc 

Nurs Ment Health Serv. Jul 1991;29(7):24-29. Not 

eligible outcomes. 

1969. Mustard LW. The culture of patient safety. JONAS 

Healthc Law Ethics Regul. Dec 2002;4(4):111-115. 

Review. 

1970. Mustard LW. Improving patient satisfaction through 

the consistent use of scripting by the nursing staff. 

JONAS Healthc Law Ethics Regul. Sep 2003;5(3):68-

72. Not eligible exposure. 

1971. Myers H, Nikoletti S. Fall risk assessment: a 

prospective investigation of nurses' clinical 

judgement and risk assessment tools in predicting 

patient falls. Int J Nurs Pract. Jun 2003;9(3):158-165. 

Not eligible target population. 

1972. Myers L. The NHS--a patient's perspective. Health 

Expect. Dec 2001;4(4):205-208. Not eligible target 

population. 

1973. Myers M. Trauma coordinator: full-time or part-time? 

J Trauma Nurs. Jul-Sep 1998;5(3):59-61. Editorial. 

1974. Myers SM. Patient-focused care: what managers 

should know. Nurs Econ. Jul-Aug 1998;16(4):180-

188. No association tested. 

1975. Myles GL, Perry AG, Malkoff MD, Shatto BJ, ScottKillmade MC. Quantifying nursing care in 

barbiturate-induced coma with the therapeutic 

intervention scoring system. J Neurosci Nurs. Feb 

1995;27(1):35-42. Not eligible exposure. 

1976. Nader R. Arnold imitates art. Revolution. Mar-Apr 

2005;6(2):7-8. Review. 

1977. Nahalla CK, FitzGerald M. The impact of regular 

hospitalization of children living with thalassaemia on 

their parents in Sri Lanka: a phenomenological study. 

Int J Nurs Pract. Jun 2003;9(3):131-139. Not eligible 

target population. 

1978. Naish J. Recruitment crisis returns. Nurs Manag 

(Harrow). Jan 1995;1(8):6-7. Comment. 

1979. Naish J. Part-time working. Balancing act. Nurs 

Times. Feb 28-Mar 5 1996;92(9):28-30. Not eligible 

target population. 

1980. Nakagawa J, Ouk S, Schwartz B, Schriger DL. 

Interobserver agreement in emergency department 

triage. Ann Emerg Med. Feb 2003;41(2):191-195. Not 

eligible outcomes. 

1981 Napholz L. Sex role typology as a function of age 

among registered nurses. Health care for women 

international Jul-Sep 1992;13(3):303-12. Not 

relevant. 

1982. Napthine R. Pen power--doctors under scrutiny. Aust 

Nurs J. Sep 1995;3(3):28-29. Comment. 

1983. Nardini J. Medical errors--is the system "ill?" 

Nephrol Nurs J. Jun 2000;27(3):272-273. Comment.

1984. Nash MG, Blackwood D, Boone EB, 3rd, Klar R, 

Lewis E, MacInnis K, McKay J, Okress J, Richer S, 

Tannas C. Managing expectations between patient 

and nurse. J Nurs Adm. Nov 1994;24(11):49-55. No 

association tested. 

1985. Nash MG, Miller G, Everett LN, Faber-Bermudez I, 

Libcke J, Nalon K. Third Annual Nursing 

Administration Recognition Program. Honorable 

Mention...Economic model for a hospital-based 

supplemental staffing program. J Nurs Adm. Apr 

1991;21(4):17-18. Comment. 

1986. Naumanen-Tuomela P. Finnish occupational health 

nurses' work and expertise: the clients' perspective. J 

Adv Nurs. May 2001;34(4):538-544. Not eligible 

target population. 

1987. Nava S, Evangelisti I, Rampulla C, Compagnoni ML, 

Fracchia C, Rubini F. Human and financial costs of 

noninvasive mechanical ventilation in patients 

affected by COPD and acute respiratory failure. 

Chest. Jun 1997;111(6):1631-1638. Not eligible 

target population. 

1988. Navarro VB, Stout WA, Jr., Tolley FM. Allocation of 

nursing care hours in a combined ophthalmic nursing 

unit. Insight. Apr 1995;20(1):14-16. No association 

tested. 

1989. Nazarko L. Working parents: primary or secondary? 

Nurs Stand. Mar 11-17 1992;6(25):53-54. Not eligible 

target population. 

1990. Nazarko L. Working parents: turning against rotation. 

Nurs Stand. Jun 10-16 1992;6(38):44. Comment. 

1991. Nazarko L. Working mothers: short shrift for long. 

Not eligible target population. 

1992. Needham I, Abderhalden C, Dassen T, Haug HJ, 

Fischer JE. The perception of aggression by nurses: 

psychometric scale testing and derivation of a short 

instrument. J Psychiatr Ment Health Nurs. Feb 

2004;11(1):36-42. Not eligible target population. 

1993. Needham I, Abderhalden C, Halfens RJ, Dassen T, 

Haug HJ, Fischer JE. The effect of a training course 

in aggression management on mental health nurses' 

perceptions of aggression: a cluster randomised 

controlled trial. Int J Nurs Stud. Aug 2005;42(6):649-

655. Not eligible exposure. 

1994. Neitzel JJ, Miller EH, Shepherd MF, Belgrade M. 

Improving pain management after total joint 

replacement surgery. Orthop Nurs. Jul-Aug 

1999;18(4):37-45, 64. Not eligible exposure. 

1995. Nelson J. Visit at your peril. Nurs Stand. Mar 13-19 

1991;5(25):46. Case Reports. 
B-59 

1996. Nelson J. Shift patterns: a hard day's night. Nurs 

Stand. Jan 29-Feb 4 1992;6(19):54. Comment.

1997. Nelson MS. A triage-based emergency department 

patient classification system. J Emerg Nurs. Dec 

1994;20(6):511-516. Not eligible exposure. 

1998. Nelson NC, Evans RS, Samore MH, Gardner RM. 

Detection and prevention of medication errors using 

real-time bedside nurse charting. J Am Med Inform 

Assoc. Jul-Aug 2005;12(4):390-397. Not eligible 

exposure. 

1999. Nelson S. Staffing, ratios and skill mix--is there an 

Australian story? Nurs Inq. Mar 2005;12(1):1. 

Editorial.

2000. Nerdahl P, Berglund D, Bearinger LH, et al. New 

challenges, new answers: pediatric nurse practitioners 

and the care of adolescents. Journal of Pediatric 

Health Care Jul-Aug 1999;13(4):183-90. Not 

relevant. 

2001. Nesbitt-Johnson M. Burn unit ensures expert, 

specialized staffing. Nurs Manage. Sep 

1998;29(9):40F. Comment. 

2002. Neuhs HP. The nursing shortage: crisis as 

opportunity. J Nurs Adm. Mar 1991;21(3):5, 36. 

Editorial. 

2003. Nevidjon B. Due to the nursing shortage, mandatory 

overtime is a necessary evil. Nurs Leadersh Forum. 

Winter 2001;6(2):32, 37-38. Comment.

2004. Newhouse RP, Johantgen M, Pronovost PJ, Johnson 

E. Perioperative nurses and patient outcomes--

mortality, complications, and length of stay. Aorn J. 

Mar 2005;81(3):508-509, 513-522, 525-508. Not 

eligible exposure. 

2005. Newman KM, Heine C. Availability of scheduling 

options important. J Nurs Adm. Jul-Aug 1991;21(7-

8):46, 49. Comment. 

2006. Ngin PM, Simms LM. Computer use for work 

accomplishment. A comparison between nurse 

managers and staff nurses. J Nurs Adm. Mar 

1996;26(3):47-55. Not eligible target population. 

2007. Nguyen BQ. You're not one of us. When 

discrimination based on national origin becomes a 

problem. Am J Nurs. Jan 2001;101(1):77. Comment.

2008. Nguyen GT, Proctor SE, SinkowitzCochran RL, et al. 

Status of infection surveillance and control programs 

in the United States, 1992-1996. American Journal of 

Infection Control Dec 2000;28(6):392-400. Not 

relevant. 

2009. Nichol KL, Hauge M. Influenza vaccination of 

healthcare workers. Infect Control Hosp Epidemiol. 

Mar 1997;18(3):189-194. Not eligible exposure. 

2010. Nicholls DJ, Duplaga EA, Meyer LM. Nurses' 

attitudes about floating. Nurs Manage. Jan 

1996;27(1):56-58. Comment. 

2011. Nicholson D, Ravenscroft E, Ray J, Stuart L. Staff 

mix and public safety. Nurs BC. Oct 2004;36(4):5. 

Letter. 

2012. Nicklin W, Graves E. Nursing and patient outcomes: 

it's time for healthcare leadership to respond. Healthc 

Manage Forum. Spring 2005;18(1):9-13, 40-15. 

Review. 

2013. Niederstadt JA. Frequency and timing of activated 

clotting time levels for sheath removal. J Nurs Care 

Qual. Jan-Mar 2004;19(1):34-38. Not eligible target 

population. 

2014. Niedhammer I, Lert F, Marne MJ. Psychotropic drug 

use and shift work among French nurses (1980-1990). 

Psychol Med. Mar 1995;25(2):329-338. Not eligible 

target population. 

2015. Noak J. Do we need another model for mental health 

care? Nurs Stand. Nov 7-13 2001;16(8):33-35. 

Comment. 

2016. Norrie P. Nurses' time management in intensive care. 

Nurs Crit Care. May-Jun 1997;2(3):121-125. Not 

eligible target population. 

2017. Northcott N, Facey S. Twelve-hour shifts: helpful or 

hazardous to patients? Nurs Times. Feb 15-22 

1995;91(7):29-31. Comment. 

2018. Norton A. Realistic rostering. Nurs N Z. Nov 

1994;2(10):11. Not eligible target population. 

2019. Norton A. Shifting the emphasis. Nurs N Z. Jun 

1995;1(5):12. Not eligible target population. 

2020. Noyes J. Are nurses respecting and upholding the 

human rights of children and young people in their 

care? Paediatr Nurs. Mar 2000;12(2):23-27. Not 

eligible target population. 

2021. Nugent J. The NurseLink model of care. Contemp 

Nurse. Aug 2003;15(1-2):110-113. Not eligible target 

population. 

2022. Nyqvist KH, Rubertsson C, Ewald U, Sjoden PO. 

Development of the Preterm Infant Breastfeeding 

Behavior Scale (PIBBS): a study of nurse-mother 

agreement. J Hum Lact. Sep 1996;12(3):207-219. Not 

eligible target population. 

2023. Oates JD, Snowdon SL, Jayson DW. Failure of pain 

relief after surgery. Attitudes of ward staff and 

patients to postoperative analgesia. Anaesthesia. Sep 

1994;49(9):755-758. Not eligible exposure. 

2024. O'Brien JA. Utilization of nursing personnel from 

supplemental staffing agencies by health care 

facilities in Minnesota. Minnesota nursing accent Jan 

1991;63(1):16-7. Not peer reviewed. 

2025. O'Brien RL, Serbin MF, O'Brien KD, Maier RV, 

Grady MS. Improvement in the organ donation rate at 

a large urban trauma center. Arch Surg. Feb 

1996;131(2):153-159. Not eligible exposure. 

2026. O'Brien SP, Wind S, van Rijswijk L, Kerstein MD. 

Sequential biannual prevalence studies of pressure 

ulcers at Allegheny-Hahnemann University Hospital. 

Ostomy Wound Manage. Mar 1998;44(3A 

Suppl):78S-88S; discussion 89S. Not eligible 

exposure. 

2027. O'Brien-Pallas L, Shamian J, Thomson D, Alksnis C, 

Koehoorn M, Kerr M, Bruce S. Work-related 

disability in Canadian nurses. J Nurs Scholarsh. 

2004;36(4):352-357. Not eligible outcomes.

2028. O'Brodovich M, Rappaport P. A study pre and post 

unit dose conversion in a pediatric hospital. Can J 

Hosp Pharm. Feb 1991;44(1):5-15, 50. Not eligible 

outcomes. 

2029. O'Connor R. Getting them over there. Nurs Stand. 

Mar 5-11 2003;17(25):16-17. News. 
B-60 

2030. O'Connor T. 12 hour shifts begin in Dunedin. N Z 

Nurs J. Nov 1992;85(10):20-21. Not eligible target 

population. 

2031. O'Connor T. Statistics show sick system. Nurs N Z. 

Jul 1995;1(6):18-19. Not eligible target population. 

2032. O'Connor T. Staffing levels cause concern. Nurs N Z. 

Nov 1999;5(10):11. Comment. 

2033. O'Dowd A. Scotland. Soaring violence against nurses. 

Nurs Times. Jul 13-19 2000;96(28):5. News. 

2034. O'Dowd A. Workplace violence. Call for police 

officer in every A&E. Nurs Times. Jul 20-26 

2000;96(29):12-13. News. 

2035. O'Dowd A. London trust in a royal mess. Nurs Times. 

Oct 19-25 2000;96(42):10-11. News.

2036. O'Dowd A. Are minimum staff ratios needed? Nurs 

Times. Apr 6-12 2004;100(14):12-13. Not eligible 

target population. 

2037. O'Dowd A. Weighing up nurse-to-patient ratios. Nurs 

Times. Aug 2-8 2005;101(31):20-22. Comment. 

2038. Oehler JM, Davidson MG. Job stress and burnout in 

acute and nonacute pediatric nurses. Am J Crit Care. 

Sep 1992;1(2):81-90. Not eligible exposure. 

2039. Ofili AN, Asuzu MC, Okojie OH. Hospital workers' 

opinions on the predisposing factors to blood-related 

work accidents in Central Hospital, Benin City, Edo 

State, Nigeria. Public Health. Sep 2003;117(5):333-

338. Not eligible target population.

2040. O'Hare MC, Bradley AM, Gallagher T, Shields MD. 

Errors in administration of intravenous drugs. Bmj. 

Jun 10 1995;310(6993):1536-1537. Letter. 

2041. O'Hern-Martin P. Suburban hospital nurses fight for 

safe staffing. Revolution. Spring 1997;7(1):18-20. 

Legal Cases. 

2042. Ohrn KE, Wahlin YB, Sjoden PO. Oral care in cancer 

nursing. Eur J Cancer Care (Engl). Mar 2000;9(1):22-

29. Not eligible target population. 

2043. Okolo SN, Ogbonna C. Knowledge, attitude and 

practice of health workers in Keffi local government 

hospitals regarding Baby-Friendly Hospital Initiative 

(BFHI) practices. Eur J Clin Nutr. May 

2002;56(5):438-441. Not eligible target population. 

2044. Oldenkamp JH, Heesen C, Simons JL. Application of 

telematics for improving multiple schedules. Stud 

Health Technol Inform. 1997;43 Pt A:64-68. Not 

eligible target population. 

2045. O'Leary J, Williamson J. Meeting the challanges in 

today's outpatient oncology setting: a case study. J 

Oncol Manag. May-Jun 2003;12(3):24-26. No 

association tested. 

2046. Oleni M, Johansson P, Fridlund B. Nursing care at 

night: an evaluation using the Night Nursing Care 

Instrument. J Adv Nurs. Jul 2004;47(1):25-32. Not 

eligible target population. 

2047. Oleson M, Heading C, Shadick KM, Bistodeau JA. 

Quality of life in long-stay institutions in England: 

nurse and resident perceptions. J Adv Nurs. Jul 

1994;20(1):23-32. Not eligible target population. 

2048. Olive KE, Ballard JA. Attitudes of patients toward 

smoking by health professionals. Public Health Rep. 

May-Jun 1992;107(3):335-339. Not eligible exposure. 

2049. Olson ME, Smith MJ. An evaluation of single-room 

maternity care. Health Care Superv. Sep 

1992;11(1):43-49. Not eligible exposure. 

2050. O'Neil E, Seago JA. Meeting the challenge of nursing 

and the nation's health. Jama. Oct 23-30 

2002;288(16):2040-2041. Comment. 

2051. O'Neill KL, Ross-Kerr JC. Impact of an instructional 

program on nurses' accuracy in capillary blood 

glucose monitoring. Clin Nurs Res. May 

1999;8(2):166-178. Not eligible exposure. 

2052. O'Neill TR, Tannenbaum RJ, Tiffen J. 

Recommending a minimum English proficiency 

standard for entry-level nursing. Journal of nursing 

measurement Fall 2005;13(2):129-46. Not relevant. 

2053. O'Reilly M. Dying in an acute-care setting. Nurs N Z. 

Nov 2000;6(10):16-17. Comment.

2054. Ornstein H. The floating dilemma. Can Nurse. Oct 

1992;88(9):20-22. Comment. 

2055. Orsted HL, Campbell KE, Keast DH, Coutts P, 

Sterling W. Chronic wound caring ... a long journey 

toward healing. Ostomy Wound Manage. Oct 

2001;47(10):26-36. Case Reports. 

2056. Osborne J, Blais K, Hayes JS. Nurses' perceptions: 

when is it a medication error? J Nurs Adm. Apr 

1999;29(4):33-38. Not eligible exposure. 

2057. Osmon S, Harris CB, Dunagan WC, Prentice D, 

Fraser VJ, Kollef MH. Reporting of medical errors: 

an intensive care unit experience. Crit Care Med. Mar 

2004;32(3):727-733. Not eligible exposure.

2058. Ostrowski M. Turn up the volume. Rn. Mar 

2002;65(3):7. Editorial. 

2059. Ostry AS, Tomlin KM, Cvitkovich Y, Ratner PA, 

Park IH, Tate RB, Yassi A. Choosing a model of care 

for patients in alternate level care: caregiver 

perspectives with respect to staff injury. Can J Nurs 

Res. Mar 2004;36(1):142-157. Not eligible outcomes. 

2060. Ostry AS, Yassi A, Ratner PA, Park I, Tate R, Kidd 

C. Work organization and patient care staff injuries: 

the impact of different care models for "alternate level 

of care" patients. Am J Ind Med. Oct 2003;44(4):392-

399. Not eligible outcomes. 

2061. O'Sullivan J. Healthcare changes bring increased 

liability risk for nurses. Mo Nurse. Sep-Oct 

1995;64(5):4. Comment. 

2062. Overdyk FJ, Harvey SC, Fishman RL, Shippey F. 

Successful strategies for improving operating room 

efficiency at academic institutions. Anesth Analg. 

Apr 1998;86(4):896-906. Not eligible exposure. 

2063. Owen BD, Keene K, Olson S. An ergonomic 

approach to reducing back/shoulder stress in hospital 

nursing personnel: a five year follow up. Int J Nurs 

Stud. Mar 2002;39(3):295-302. Not eligible exposure. 

2064. Owen C, Tarantello C, Jones M, Tennant C. Violence 

and aggression in psychiatric units. Psychiatr Serv. 

Nov 1998;49(11):1452-1457. Not eligible target 

population. 

2065. Owen L. The named nurse: patient and nurse 

expectations. Prof Nurse. Aug 1997;12(11):769-771. 

Not eligible target population.
B-61 

2066. Oz F. Impact of training on empathic communication 

skills and tendency of nurses. Clin Excell Nurse 

Pract. 2001;5(1):44-51. Not eligible target 

population. 

2067. Ozkarahan I. An integrated nurse scheduling model. J 

Soc Health Syst. 1991;3(2):79-101. No association 

tested. 

2069. Pacini CM. Synergy: a framework for leadership 

development and transformation. Crit Care Nurs Clin 

North Am. Jun 2005;17(2):113-119, ix. No 

association tested. 

2070. Padilla-Harris C. Night fever. Nurs Stand. Oct 17-23 

2001;16(5):23. News. 

2071. Padmam R. Extroversion, neuroticism and job 

satisfaction: a comparative study of staff nurses and 

students. Nurs J India. Mar 1995;86(3):65-68. Not 

eligible target population. 

2072. Page B. Where have all the nurses gone? Can Oncol 

Nurs J. May 1998;8(2):91-92. Editorial. 

2073. Page D. Paramedics--above & beyond. Hosp Health 

Netw. Mar 2000;74(3):30. Comment.

2074. Page JS. Nurse staffing and outcomes: differentiating 

care delivery by education preparation. J Nurs Adm. 

Jan 2005;35(1):7. Comment. 

2075. Page L, McCourt C, Beake S, Vail A, Hewison J. 

Clinical interventions and outcomes of One-to-One 

midwifery practice. J Public Health Med. Sep 

1999;21(3):243-248. Not eligible target population. 

2076. Page M. Tailoring nursing models to clients' needs. 

Using the Roper, Logan and Tierney model after 

discharge. Prof Nurse. Feb 1995;10(5):284-288. 

Comment. 

2077. Paget-Wilkes M. Self-rostering on a neonatal 

intensive care unit. Nurs Stand. Feb 19 

1997;11(22):39-42. Not eligible target population. 

2078. Pallarito K. Rule delay leaves foreign nurses in limbo. 

Mod Healthc. Dec 3 1990;20(48):6. News. 

2079. Pallarito K. Labor proposes rules governing foreign 

nurses. Mod Healthc. Jul 23 1990;20(29):4. News. 

2080. Palmer J. Eight- and 12-hour shifts: comparing 

nurses' behavior patterns. Nurs Manage. Sep 

1991;22(9):42-44. No association tested. 

2081. Panagiotopoulou K, Kerr SM. Pressure area care: an 

exploration of Greek nurses' knowledge and practice. 

J Adv Nurs. Nov 2002;40(3):285-296. Not eligible 

target population. 

2082. Papadatou D, Martinson IM, Chung PM. Caring for 

dying children: a comparative study of nurses' 

experiences in Greece and Hong Kong. Cancer Nurs. 

Oct 2001;24(5):402-412. Not eligible target 

population. 

2083. Pape TM. Applying airline safety practices to 

medication administration. Medsurg Nurs. Apr 

2003;12(2):77-93; quiz 94. Not eligible exposure.

2084. Pape TM, Guerra DM, Muzquiz M, Bryant JB, 

Ingram M, Schranner B, Alcala A, Sharp J, Bishop D, 

Carreno E, Welker J. Innovative approaches to 

reducing nurses' distractions during medication 

administration. J Contin Educ Nurs. May-Jun 

2005;36(3):108-116; quiz 141-102. Not eligible 

exposure. 

2085. Paredes SD, Frank DI. Nurse/parent role perceptions 

in care of neonatal intensive care unit infants: 

implications for the advanced practice nurse. Clin 

Excell Nurse Pract. Sep 2000;4(5):294-301. Not 

eligible exposure. 

2086. Parish C. Minimum effort. Nurs Stand. Jul 3-9 

2002;16(42):12-13. Comment. 

2087. Park EK, Song M. Communication barriers perceived 

by older patients and nurses. Int J Nurs Stud. Feb 

2005;42(2):159-166. Not eligible target population.

2088. Park HA, Park JH. Development of a computerized 

patient classification and staffing system. Stud Health 

Technol Inform. 1997;46:508-511. Not eligible target 

population. 

2089. Parker MT, Leggett-Frazier N, Vincent PA, Swanson 

MS. The impact of an educational program on 

improving diabetes knowledge and changing 

behaviors of nurses in long-term care facilities. 

Diabetes Educ. Nov-Dec 1995;21(6):541-545. Not 

eligible exposure. 

2090. Parse RR. Language: words reflect and cocreate 

meaning. Nurs Sci Q. Jul 2000;13(3):187. Editorial. 

2091. Parsons LC. Building RN confidence for delegation 

decision-making skills in practice. J Nurses Staff Dev. 

Nov-Dec 1999;15(6):263-269. Not eligible exposure. 

2092. Parsons ML, Scaltrito S, Vondle DP. A program to 

manage nurse staffing costs. Nurs Manage. Oct 

1990;21(10):42-44. No association tested. 

2093. Parsons ML, Stonestreet J. Staff nurse retention. 

Laying the groundwork by listening. Nurs Leadersh 

Forum. Spring 2004;8(3):107-113. No association 

tested. 

2094. Paterson I. Service assistants threaten nursing. Nurs N 

Z. May 1997;3(4):32-33. Not eligible target 

population. 

2095. Patrician PA. Multiple imputation for missing data. 

Res Nurs Health. Feb 2002;25(1):76-84. Review. 

2096. Patterson B. Safe patient care legislation addresses 

growing national problem. Mich Nurse. Aug 2004:5, 

16. Review. 

2097. Patterson P. PACU staffing. Staffing the recovery 

areas an art as well as a science. OR Manager. Apr 

1998;14(4):1, 19-22. Not eligible target population. 

2098. Patterson P. How ORs manage on-call varies by local 

market. OR Manager. Feb 2000;16(2):1, 8-11. 

Comment. 

2099. Payne D. Time for judgement. Nurs Times. Jun 3-9 

1998;94(22):15. Comment. 

2100. Payne S, Hardey M, Coleman P. Interactions between 

nurses during handovers in elderly care. J Adv Nurs. 

Aug 2000;32(2):277-285. Not eligible target 

population. 

2101. Pearce L. Your hospital needs you. Nurs Stand. Nov 

1-7 2000;15(7):14-15. Comment. 

2102. Pederson C. Nonpharmacologic interventions to 

manage children's pain: immediate and short-term 

effects of a continuing education program. J Contin 

Educ Nurs. May-Jun 1996;27(3):131-140. Not 

eligible exposure. 
B-62 

2103. Peerson A, Aitken R, Manias E, Parker J, Wong K. 

Agency nursing in Melbourne, Australia: a telephone 

survey of hospital and agency managers. J Adv Nurs. 

Dec 2002;40(5):504-512. Not eligible target 

population. 

2104. Penticuff JH, Arheart KL. Effectiveness of an 

intervention to improve parent-professional 

collaboration in neonatal intensive care. J Perinat 

Neonatal Nurs. Apr-Jun 2005;19(2):187-202. Not 

eligible outcomes. 

2105. Pepper GA. Errors in drug administration by nurses. 

Am J Health Syst Pharm. Feb 15 1995;52(4):390-395. 

No association tested. 

2106. Pereira LJ, Lee GM, Wade KJ. An evaluation of five 

protocols for surgical handwashing in relation to skin 

condition and microbial counts. J Hosp Infect. May 

1997;36(1):49-65. Not eligible exposure. 

2107. Perez PG, Herrick LM. Doulas: exploring their roles 

with parents, hospitals, & nurses. AWHONN 

Lifelines. Apr 1998;2(2):54-55. Comment. 

2108. Perkins L. Support grows for Massachusetts RN 

staffing bill. Revolution. Oct-Nov 2003;4(5):5. News.

2109. Perlow M, Rudolth LG. Registered nurse perceptions 

of nursing practice. Kentucky nurse Oct-Dec 

1995;43(4):28-9. Not peer reviewed. 

2110. Perras ST, Mattern M. A practical approach to TQI. 

Anna J. Apr 1994;21(2):129-136, 143. Not eligible 

outcomes. 

2111. Perry K. The problem-free assignment. Nursing. Jun 

1998;28(6):86-87. Not eligible target population. 

2112. Perry K. Time to try travel nurses? Nurs Manage. Feb 

1999;30(2):39-40. No association tested. 

2113. Perry L. Screening swallowing function of patients 

with acute stroke. Part one: Identification, 

implementation and initial evaluation of a screening 

tool for use by nurses. J Clin Nurs. Jul 

2001;10(4):463-473. Not eligible target population. 

2114. Persuhn PG. Job sharing: two who made it work. Am 

J Nurs. Sep 1992;92(9):75-80. Comment. 

2115. Peters N, Cox J. Could a process improvement 

program improve your quality assurance. Case 

Manager. Mar-Apr 2000;11(2):78-81. No association 

tested. 

2116. Petersen MF, Cohen J, Parsons V. Family-centered 

care: do we practice what we preach? J Obstet 

Gynecol Neonatal Nurs. Jul-Aug 2004;33(4):421-427. 

Not eligible exposure. 

2117. Petroff J. Registered nurses: do you have a right to 

overtime pay? Ohio Nurses Rev. Aug 1996;71(7):13. 

Comment. 

2118. Petty DS. ECT in the PACU? It's possible. Nurs 

Manage. Nov 2000;31(11):42-44. Comment. 

2119. Phillips CY. Postdischarge follow-up care: effect on 

patient outcomes. J Nurs Care Qual. Jul 1993;7(4):64-

72. Not eligible exposure. 

2120. Phillips H, Brunke L. Self scheduling helps nurses 

balance their personal & professional lives. RNABC 

News. Jul-Aug 1990;22(4):15-16. No association 

tested. 

2121. Phillips M. Telemedicine in the neonatal intensive 

care unit. Pediatr Nurs. Mar-Apr 1999;25(2):185-186, 

189. Not eligible exposure. 

2122. Phipps W, Honghong W, Min Y, Burgess J, Pellico L, 

Watkins CW, Guoping H, Williams A. Risk of 

medical sharps injuries among Chinese nurses. Am J 

Infect Control. Aug 2002;30(5):277-282. Not eligible 

target population. 

2123. Picton CE. An exploration of family-centred care in 

Neuman's model with regard to the care of the 

critically ill adult in an accident and emergency 

setting. Accid Emerg Nurs. Jan 1995;3(1):33-37. 

Comment. 

2124. Pieper B, Mattern JC. Critical care nurses' knowledge 

of pressure ulcer prevention, staging and description. 

Ostomy Wound Manage. Mar 1997;43(2):22-26, 28, 

30-21. Not eligible exposure. 

2125. Pillar B, Jarjoura D. Assessing the impact of 

reengineering on nursing. J Nurs Adm. May 

1999;29(5):57-64. Not eligible outcomes. 

2126. Piloian BB. Alternative staffing strategies for 

community hospital-based diabetes education 

programs. Diabetes Educ. Jul-Aug 1992;18(4):293, 

295-296. Not eligible exposure. 

2127. Piltz-Kirkby M. The nursing assignment pattern study 

in clinical practice. Nurs Manage. May 

1991;22(5):96HH, 96LL, 96NN. No association 

tested. 

2128. Pink GH, Hall LM, Leatt P. Canadian-trained nurses 

in North Carolina. Healthcare Quarterly 2004;7(3): 

Longwoods Review, Volume 2, Number 2):2-11. Not 

relevant. 

2129. Pinkerton S. Payoffs from investments: improving, 

transforming, and building skills. Nurs Econ. Sep-Oct 

2002;20(5):244, 248. Comment. 

2130. Pinnock D. Experience of being a shift co-ordinator. 

Nurs Crit Care. Sep-Oct 1998;3(5):227-236. Not 

eligible target population. 

2131. Pioro MH, Landefeld CS, Brennan PF, Daly B, 

Fortinsky RH, Kim U, Rosenthal GE. Outcomesbased trial of an inpatient nurse practitioner service 

for general medical patients. J Eval Clin Pract. Feb 

2001;7(1):21-33. Not eligible exposure. 

2132. Pirret AM. Utilizing TISS to differentiate between 

intensive care and high-dependency patients and to 

identify nursing skill requirements. Intensive Crit 

Care Nurs. Feb 2002;18(1):19-26. Not eligible target 

population. 

2133. Pisarski A, Bohle P. Effects of supervisor support and 

coping on shiftwork tolerance. J Hum Ergol (Tokyo). 

Dec 2001;30(1-2):363-368. Not eligible target 

population. 

2134. Pisarski A, Bohle P, Callan VJ. Effects of coping 

strategies, social support and work-nonwork conflict 

on shift worker's health. Scand J Work Environ 

Health. 1998;24 Suppl 3:141-145. Not eligible target 

population. 

2135. Pitt HA, Murray KP, Bowman HM, Coleman J, 

Gordon TA, Yeo CJ, Lillemoe KD, Cameron JL. 

Clinical pathway implementation improves outcomes 

for complex biliary surgery. Surgery. Oct 

1999;126(4):751-756; discussion 756-758. Not 

eligible exposure. 
B-63 

2136. Pizer CM, Collard AF, Bishop CE, James SM, 

Bonaparte B. Recruiting and employing foreign nurse 

graduates in a large public hospital system. Hosp 

Health Serv Adm. Spring 1994;39(1):31-46. Not 

eligible exposure. 

2137. Place B, Cornock M. Critical timing. Nurs Times. Jun 

25-Jul 1 1997;93(26):26-28. Not eligible target 

population. 

2138. Plant ML, Plant MA, Foster J. Stress, alcohol, 

tobacco and illicit drug use amongst nurses: a Scottish 

study. J Adv Nurs. Sep 1992;17(9):1057-1067. Not 

eligible target population. 

2139. Plati C, Lanara VA, Katostaras T, Mantas J. Nursing 

absenteeism--one determining factor for the staffing 

plan. Scand J Caring Sci. 1994;8(3):143-148. Not 

eligible outcomes. 

2140. Plowright C. Auditing quality of nursing care. 

Intensive Crit Care Nurs. Dec 1995;11(6):354-359. 

No association tested. 

2141. Plowright C, O'Riordan B, Scott G. The perception of 

ward-based nurses seconded into an Outreach 

Service. Nurs Crit Care. May-Jun 2005;10(3):143-

149. Not eligible target population. 

2142. Plum SD. Three Denver nurses may face prison in a 

case that bodes ill for the profession. Revolution. 

Summer 1997;7(2):11-12. Comment. 

2143. Plum SD. Medication error--nurses indicated. 

Nursing. Jul 1997;27(7):34-35. Comment. 

2144. Poirrier GP, Granger M, Todaro M. ACE--Alliance 

for Clinical Enhancement: a collaborative model. 

Nursingconnections. Fall 1993;6(3):53-61. Not 

eligible exposure. 

2145. Poissonnet CM, Iwatsubo Y, Cosquer M, Quera Salva 

MA, Caillard JF, Veron M. A cross-sectional study of 

the health effects of work schedules on 3212 hospital 

workers in France: implications for the new French 

work schedules policy. J Hum Ergol (Tokyo). Dec 

2001;30(1-2):387-391. Not eligible target population. 

2146. Polkki T, Vehvilainen-Julkunen K, Pietila AM. 

Nonpharmacological methods in relieving children's 

postoperative pain: a survey on hospital nurses in 

Finland. J Adv Nurs. May 2001;34(4):483-492. Not 

eligible target population. 

2147. Pongsatha S, Morakote N, Sribanditmongkol N, 

Chaovisitsaree S. Symptoms of estrogen deficiency in 

nursing personnel in Maharaj Nakorn Chiang Mai 

Hospital. J Med Assoc Thai. Apr 2004;87(4):405-409. 

Not eligible target population. 

2148. Pope BB. The Synergy match-up. Nurs Manage. May 

2002;33(5):38-41. Comment. 

2149. Pope M. A mix-up of tubes. Medication administered 

through the wrong access line. Am J Nurs. Apr 

2002;102(4):23. Case Reports. 

2150. Poroch D, McIntosh W. Barriers to assertive skills in 

nurses. Aust N Z J Ment Health Nurs. Sep 

1995;4(3):113-123. Not eligible target population.

2151. Poquette MC, Platte J, Casey K. Meeting the staffing 

challenge: development of a voluntary on-call system. 

Critical care nursing quarterly Nov 1992;15(3):29-36. 

Not relevant.

2152. Porter-O'Grady T. Mission with a margin. Nurs 

Manage. Jun 2000;31(6):8. Editorial. 

2153. Potter P, Boxerman S, Wolf L, Marshall J, Grayson 

D, Sledge J, Evanoff B. Mapping the nursing process: 

a new approach for understanding the work of 

nursing. J Nurs Adm. Feb 2004;34(2):101-109. Not 

eligible exposure. 

2154. Potter P, Wolf L, Boxerman S, et al. Understanding 

the cognitive work of nursing in the acute care 

environment. Journal of Nursing Administration JulAug 2005;35(7/8):327-35. Not relevant 

2155. Powell C, Walker J, Christie M, Mitchell-Pedersen L, 

Rauscher C. The unexpected relocation of elderly inpatients in response to a threatened strike. J Adv 

Nurs. Apr 1990;15(4):423-429. Not eligible exposure.

2156. Powers BA. Everyday ethics in assisted living 

facilitites: a framework for assessing resident-focused 

issues. J Gerontol Nurs. Jan 2005;31(1):31-37. Case 

Reports. 

2157. Powers J, Daniels D. Turning points: implementing 

kinetic therapy in the ICU. Nurs Manage. May 

2004;35(5):suppl 1-7; quiz 8. Not eligible exposure.

2158. Powers JL. Accepting and refusing assignments. Nurs 

Manage. Sep 1993;24(9):64-66, 68. Comment. 

2159. Pownall M. Shifting ground. Nurs Times. Oct 31-Nov 

6 1990;86(44):19. Comment. 

2160. Prater M. Victory for Youngstown nurses. New 

contract ensures safe hours, safe staffing and quality 

patient care for RNs. Ohio Nurses Rev. Aug 

2001;76(7):1. Comment. 

2161. Pratt R, Burr G, Leelarthaepin B, Blizard P, Walsh S. 

The effects of All-RN and RN-EN staffing on the 

quality and cost of patient care. Aust J Adv Nurs. 

Mar-May 1993;10(3):27-39. Case Reports. 

2162. Prescott PA, Soeken KL. Measuring nursing intensity 

in ambulatory care. Part II: Developing and testing 

PINAC. Nurs Econ. Mar-Apr 1996;14(2):86-91, 116. 

Not eligible target population. 

2163. Prescott PA, Soeken KL, Ryan JW. Measuring patient 

intensity. A reliability study. Eval Health Prof. Sep 

1989;12(3):255-269. Not eligible year. 

2164. Price C. A national uprising. United actions push 

mandatory overtime, inadequate staffing to forefront. 

Am J Nurs. Dec 2000;100(12):75-76. Review. 

2165. Pringle D. What do nursing and the law have in 

common: retention. Can J Nurs Leadersh. Mar 

2004;17(1):1-2, 4. Editorial. 

2166. Procter S. It all depends. Health Serv J. Jan 21 

1993;103(5336):27. Not eligible target population.

2167. Proctor M. Medicalisation of life: are nurses 

involved? Contemp Nurse. Sep-Dec 2000;9(3-4):263-

264. Case Reports.

2168. Proehl JA. Developing emergency nursing 

competence. Nurs Clin North Am. Mar 

2002;37(1):89-96, vii. Not eligible exposure. 

2169. Pronger L. Floating: sink or swim. Can Nurse. Dec 

1995;91(11):28-32. No association tested. 

2170. Pronitis-Ruotolo D. Surviving the night shift. Am J 

Nurs. Jul 2001;101(7):63-65, 67-68. Comment.

2171. Pronovost P, Wu AW, Dorman T, Morlock L. 

Building safety into ICU care. J Crit Care. Jun 

2002;17(2):78-85. Case Reports. 
B-64 

2172. Puckett F. Medication-management component of a 

point-of-care information system. Am J Health Syst 

Pharm. Jun 15 1995;52(12):1305-1309. Not eligible 

exposure. 

2173. Pullenayegum S, Fielding B, Du Plessis E, Peate I. 

The value of the role of the rehabilitation assistant. Br 

J Nurs. Jul 28-Aug 10 2005;14(14):778-784. Not 

eligible target population. 

2174. Pumford S, Pettigrew C, Sargent J. Revising routines. 

Nurs Times. Aug 28-Sep 3 1991;87(35):31-33. 

Comment. 

2175. Puntillo K, Neighbor M, O'Neil N, Nixon R. 

Accuracy of emergency nurses in assessment of 

patients' pain. Pain Manag Nurs. Dec 2003;4(4):171-

175. Not eligible exposure. 

2176. Purnell LD. A survey of emergency department triage 

in 185 hospitals: physical facilities, fast-track 

systems, patient-classification systems, waiting times, 

and qualification, training, and skills of triage 

personnel. J Emerg Nurs. Dec 1991;17(6):402-407. 

Not eligible outcomes. 

2177. Quigley P, Janzen SK, King I, Goucher E. Nurse 

staffing and patient outcomes from one acute care 

setting within the Department of Veterans' Affairs. 

Fla Nurse. Jun 1999;47(2):34. No association tested. 

2178. Quinn S. Making a nonsense of training. RCM 

Midwives. Jul 2004;7(7):312. Not eligible target 

population. 

2179. Rae CP, Gallagher G, Watson S, Kinsella J. An audit 

of patient perception compared with medical and 

nursing staff estimation of pain during burn dressing 

changes. Eur J Anaesthesiol. Jan 2000;17(1):43-45. 

Not eligible target population. 

2180. Rainer SR. Ratio bill gains support. N J Nurse. SepOct 2003;33(7):1, 12. News.

2181. Raines DA. Choices of neonatal nurses in ambiguous 

clinical situations. Neonatal Netw. Feb 

1996;15(1):17-25. Not eligible exposure.

2182. Ralston R. Clinical governance. One year on: Part 2. 

Pract Midwife. Jun 2001;4(6):33-34. Not eligible 

target population. 

2183. Rambur B, McIntosh B, Palumbo MV, Reinier K. 

Education as a determinant of career retention and job 

satisfaction among registered nurses. J Nurs 

Scholarsh. 2005;37(2):185-192. Not Eligible 

Exposure. 

2184. Ramritu P, Courtney M, Stanley T, Finlayson K. 

Experiences of the generalist nurse caring for 

adolescents with mental health problems. J Child 

Health Care. Dec 2002;6(4):229-244. Not eligible 

target population. 

2185. Ramsey P, Cathelyn J, Gugliotta B, Glenn LL. 

Restricted versus open ICUs. Nurs Manage. Jan 

2000;31(1):42-44. Not eligible exposure. 

2186. Ramudu L, Bellet B, Higgs J, Latimer C, Smith R. 

How effectively do we use double staff time? Aust J 

Adv Nurs. Mar-May 1994;11(3):5-10. Not eligible 

target population. 

2187. Randolph AG, Zollo MB, Wigton RS, Yeh TS. 

Factors explaining variability among caregivers in the 

intent to restrict life-support interventions in a 

pediatric intensive care unit. Crit Care Med. Mar 

1997;25(3):435-439. Not eligible exposure. 

2188. Rankin JM. 'Patient satisfaction': knowledge for 

ruling hospital reform--an institutional ethnography. 

Nurs Inq. Mar 2003;10(1):57-65. Comment. 

2189. Rapala K. Mentoring staff members as patient safety 

leaders: the Clarian Safe Passage Program. Crit Care 

Nurs Clin North Am. Jun 2005;17(2):121-126, ix. No 

association tested. 

2190. Rasmussen BH, Sandman PO. Nurses' work in a 

hospice and in an oncological unit in Sweden. Hosp J. 

2000;15(1):53-75. Not eligible target population. 

2191. Rauhala A, Fagerstrom L. Determining optimal 

nursing intensity: the RAFAELA method. J Adv 

Nurs. Feb 2004;45(4):351-359. Not eligible target 

population. 

2192. Rawal N, Das G, Kishen M. Assessment of 

contraceptive services in a maternity unit of a district 

general hospital in the UK. J Obstet Gynaecol. Feb 

2005;25(2):179-181. Not eligible target population.

2193. Rawlinson D. Audit of nutritional practice and 

knowledge. Prof Nurse. Feb 1998;13(5):291-294. Not 

eligible target population. 

2194. Rawnsley MM. Response to Kim's human living 

concept as a unifying perspective for nursing. Nurs 

Sci Q. Jan 2000;13(1):41-44. Comment. 

2195. Ray CE, Jagim M, Agnew J, McKay JI, Sheehy S. 

ENA's new guidelines for determining emergency 

department nurse staffing. J Emerg Nurs. Jun 

2003;29(3):245-253. Guidelines. 

2196. Rayens MK, Svavarsdottir EK. A new 

methodological approach in nursing research: an 

actor, partner, and interaction effect model for family 

outcomes. Res Nurs Health. Oct 2003;26(5):409-419. 

Not eligible exposure.

2197. Ream KA. California to mandate nurse-patient 

staffing ratio. J Emerg Nurs. Dec 2000;26(6):29A. 

News. 

2198. Redfern S, Norman I. Quality of nursing care 

perceived by patients and their nurses: an application 

of the critical incident technique. Part 2. J Clin Nurs. 

Jul 1999;8(4):414-421. Not eligible target population. 

2199. Redfern S, Norman I. Quality of nursing care 

perceived by patients and their nurses: an application 

of the critical incident technique. Part 1. J Clin Nurs. 

Jul 1999;8(4):407-413. Not eligible target population. 

2200. Redshaw ME, Harris A. Nursing skill mix in neonatal 

care. J Nurs Manag. Jan 1994;2(1):15-23. Not eligible 

target population. 

2201. Redshaw ME, Harris A, Ingram JC. Nursing and 

medical staffing in neonatal units. J Nurs Manag. Sep 

1993;1(5):221-228. Not eligible target population. 

2202. Reed J, Morgan D. Discharging older people from 

hospital to care homes: implications for nursing. J 

Adv Nurs. Apr 1999;29(4):819-825. Not eligible 

target population. 
B-65 

2203. Reed JL, Lyne M. Inpatient care of mentally ill 

people in prison: results of a year's programme of 

semistructured inspections. Bmj. Apr 15 

2000;320(7241):1031-1034. Not eligible target 

population. 

2204. Reed L, Blegen MA, Goode CS. Adverse patient 

occurrences as a measure of nursing care quality. J 

Nurs Adm. May 1998;28(5):62-69. Not eligible 

exposure. 

2205. Reed P, Smith P, Fletcher M, Bradding A. Promoting 

the dignity of the child in hospital. Nurs Ethics. Jan 

2003;10(1):67-76. Not eligible target population. 

2206. Reeder L. "Coopetition," perks and price tags: stakes 

grow higher as the workforce crisis worsens. Healthc 

Leadersh Manag Rep. Mar 2002;10(3):1-9. Review. 

2207. Reedy JE. Transfer of a patient with a ventricular 

assist device to a non-critical care area. Heart Lung. 

Jan-Feb 1993;22(1):71-76. Case Reports. 

2208. Rees C, Lehane M. Witnessing violence to staff: a 

study of nurses' experiences. Nurs Stand. Dec 18 

1996;11(13-15):45-47. Not eligible target population.

2209. Reeve K, Calabro K, AdamsMcNeill J. Tobacco 

cessation intervention in a nurse practitioner managed 

clinic. Journal of the American Academy of Nurse 

Practitioners May 2000;12(5):163-9. Not relevant. 

2210. Regan S. Fewer graduates able to find full-time 

employment. Nursing BC Dec 2004;36(5):14-5. Not 

peer reviewed.

2211. Reichelt PA, Larson PA. Preimplementation financial 

evaluation of a structural work change: cost analysis 

of an innovative staffing schedule. Nurs Adm Q. 

Spring 1994;18(3):68-73. No association tested. 

2212. Reid C. Developing a tissue viability nursing assistant 

role. Nurs Stand. Apr 21-27 2004;18(32):68-72. Not 

eligible target population. 

2213. Reid N, Robinson G, Todd C. The 12-hour shift: the 

views of nurse educators and students. J Adv Nurs. 

May 1994;19(5):938-946. Not eligible target 

population. 

2214. Reid N, Todd C, Robinson G. Educational activities 

on wards under 12 hour shifts. Int J Nurs Stud. 

1991;28(1):47-54. Not eligible target population. 

2215. Reid T. Work well campaign. A suitable case for 

treatment. Nurs Times. Jun 14-20 1995;91(24):28-30. 

Case Reports. 

2216. Reilly P. A case for more nurses. JAMA study: 

chance of dying increases with more patients under 

nurse's care. Mod Healthc. Oct 28 2002;32(43):14. 

News. 

2217. Reilly P. In need of nurses. Illinois hospital makes 

name for itself through RN retention, recruitment. 

Mod Healthc. Nov 24 2003;33(47):S19-20. Comment. 

2218. Reilly P. Importing controversy. U.S. hospitals' 

recruitment of foreign nurses stirs debate as poorer 

countries struggle with staffing shortages of their 

own. Mod Healthc. Mar 31 2003;33(13):20-24. 

Comment. 

2219. Reilly P. Foreign certification. AHA seeks delay on 

regs for immigrant nurses. Mod Healthc. Feb 23 

2004;34(8):17. News. 

2220. Reis Miranda D, Moreno R, Iapichino G. Nine 

equivalents of nursing manpower use score (NEMS). 

Intensive Care Med. Jul 1997;23(7):760-765. Not 

eligible target population. 

2221. Reisdorfer JT. Building a patient-focused care unit. 

Nurs Manage. Oct 1996;27(10):38, 40, 42 passim. No 

association tested. 

2222. Renaud M. Mandatory overtime: whose right is right? 

Revolution. Jul-Aug 2000;1(4):31. Comment. 

2223. Render ML, Kim HM, Welsh DE, Timmons S, 

Johnston J, Hui S, Connors AF, Jr., Wagner D, Daley 

J, Hofer TP. Automated intensive care unit risk 

adjustment: results from a National Veterans Affairs 

study. Crit Care Med. Jun 2003;31(6):1638-1646. Not 

eligible exposure. 

2224. Retsas A, Pinikahana J. Manual handling activities 

and injuries among nurses: an Australian hospital 

study. J Adv Nurs. Apr 2000;31(4):875-883. Not 

eligible target population. 

2225. Reynolds M, Thomsen C, Black L, Moody R. The 

nuts and bolts of organizing and initiating a pediatric 

transport team. The Sutter Memorial experience. Crit 

Care Clin. Jul 1992;8(3):465-480. No association 

tested. 

2226. Ricci M, Goldman AP, de Leval MR, Cohen GA, 

Devaney F, Carthey J. Pitfalls of adverse event 

reporting in paediatric cardiac intensive care. Arch 

Dis Child. Sep 2004;89(9):856-859. Not eligible 

exposure. 

2227. Rich K. Inhospital cardiac arrest: pre-event variables 

and nursing response. Clin Nurse Spec. May 

1999;13(3):147-153; quiz 154-146. Not eligible 

exposure. 

2228. Richardson A, Burnand V, Colley H, Coulter C. Ward 

nurses' evaluation of critical care outreach. Nurs Crit 

Care. Jan-Feb 2004;9(1):28-33. Not eligible target 

population. 

2229. Richardson A, Dabner N, Curtis S. Twelve-hour shift 

on ITU: a nursing evaluation. Nurs Crit Care. MayJun 2003;8(3):103-108. Not eligible target 

population.

2230. Richardson JR, Braitberg G, Yeoh MJ. 

Multidisciplinary assessment at triage: a new way 

forward. Emerg Med Australas. Feb 2004;16(1):41-

46. Not eligible target population. 

2231. Richardson T. Patient focused care: consultants, 

foundations, educational programs. Revolution. 

Spring 1996;6(1):35-38. Comment. 

2232. Richie K, Peeler C. Plug into success with centralized 

flex staffing. Nurs Manage. Feb 2005;36(2):18. 

Review. 

2233. Ricketts T. General satisfaction and satisfaction with 

nursing communication on an adult psychiatric ward. 

J Adv Nurs. Sep 1996;24(3):479-487. Not eligible 

target population. 

2234. Riddell AM, Charig MJ. A survey of current practice 

in out of hours percutaneous nephrostomy insertion in 

the United Kingdom. Clin Radiol. Dec 

2002;57(12):1067-1069. Not eligible target 

population. 
B-66 

2235. Ridge KW, Jenkins DB, Noyce PR, Barber ND. 

Medication errors during hospital drug rounds. Qual 

Health Care. Dec 1995;4(4):240-243. Not eligible 

target population. 

2236. Ridley S, Biggam M, Stone P. Cost of intensive 

therapy. A description of methodology and initial 

results. Anaesthesia. Jul 1991;46(7):523-530. Not 

eligible target population. 

2237. Riley J. Cross-training: maximizing staffing 

flexibility. Nurs Manage. Jun 1990;21(6):48I-48J. No 

association tested. 

2238. Riley V. Dangerous liaison. Nurs Times. Nov 11-17 

1998;94(45):30-31. Case Reports. 

2239. Ringerman ES, Ventura S. An outcomes approach to 

skill mix change in critical care. Nurs Manage. Oct 

2000;31(10):42-46. No association tested. 

2240. Ritter-Teitel J. Registered nurse hours worked per 

patient day: the key to assessing staffing effectiveness 

and ensuring patient safety. J Nurs Adm. Apr 

2004;34(4):167-169. No association tested. 

2241. Ritz DA, Dugan MF. 12-hour shifts. A scheduling 

alternative for ORs. Aorn J. Mar 1990;51(3):810-811, 

813, 815. No association tested. 

2242. Rivares AV, Navarrete IG, Pueyo CG, Torrent AM, 

Duran MM, Gatius JR, Mussol LR, Solano M. 

Evaluation of relationships between haemodialysis 

unit professionals. Edtna Erca J. Jan-Mar 

2004;30(1):27-30. Not eligible target population.

2243. Rivers FM, Lavallee SM, Nenninger KM, Nichols D. 

Evaluation of a bed utilization system in a surgical 

nursing section. Mil Med. Dec 1998;163(12):839-

843. Not eligible exposure. 

2244. Robb EA, Determan AC, Lampat LR, Scherbring MJ, 

Slifka RM, Smith NA. Self-scheduling: satisfaction 

guaranteed? Nurs Manage. Jul 2003;34(7):16-18. 

Comment. 

2245. Roberts D. Competence increases comfort for float 

nurses. Medsurg Nurs. Jun 2004;13(3):142. Editorial. 

2246. Roberts G, Fielding P. No vacancies. Nurs Stand. Jan 

13-19 1999;13(17):16. News. 

2247. Roberts M, Potter J, McColl J, Reilly J. Can 

prescription of sip-feed supplements increase energy 

intake in hospitalised older people with medical 

problems? Br J Nutr. Aug 2003;90(2):425-429. Not 

eligible exposure. 

2248. Robertson MA, Molyneux EM. Triage in the 

developing world--can it be done? Arch Dis Child. 

Sep 2001;85(3):208-213. Not eligible target 

population. 

2249. Robertson MS, Cade JF, Clancy RL. Helicobacter 

pylori infection in intensive care: increased 

prevalence and a new nosocomial infection. Crit Care 

Med. Jul 1999;27(7):1276-1280. Not eligible target 

population. 

2250. Robertson RH, Dowd SB, Hassan M. Skill-specific 

staffing intensity and the cost of hospital care. Health 

Care Manage Rev. Fall 1997;22(4):61-71. Not 

eligible outcomes. 

2251. Robinson A, Street A. Improving networks between 

acute care nurses and an aged care assessment team. J 

Clin Nurs. May 2004;13(4):486-496. Not eligible 

exposure. 

2252. Robinson CA. Magnet nursing services recognition: 

transforming the critical care environment. AACN 

Clin Issues. Aug 2001;12(3):411-423. Not eligible 

exposure. 

2253. Robinson J. Education. Think pink. Nurs Stand. Nov 

14-20 1990;5(8):43. No association tested. 

2254. Robinson K. Nursing's perfect storm--staff shortages 

and patient ratios. J Emerg Nurs. Jun 2003;29(3):199-

200. Review. 

2255. Robinson S. Florence of Arabia. Nurs Times. Oct 18-

24 1995;91(42):46-47. Comment. 

2256. Robinson SE, Roth SL, Keim J, et al. Nurse burnout: 

work related and demographic factors as culprits. 

Research in nursing & health Jun 1991;14(3):223-8. 

Not relevant. 

2257. Robinson SE, Roth SL, Keim J, Levenson M, Flentje 

JR, Bashor K. Nurse burnout: work related and 

demographic factors as culprits. Res Nurs Health. Jun 

1991;14(3):223-228. Not eligible outcomes.

2258. Rocker G, Cook D, Sjokvist P, Weaver B, Finfer S, 

McDonald E, Marshall J, Kirby A, Levy M, Dodek P, 

Heyland D, Guyatt G. Clinician predictions of 

intensive care unit mortality. Crit Care Med. May 

2004;32(5):1149-1154. Not eligible exposure. 

2259. Rodriguez L. Recruitment and retention. Four ways to 

make a difference. Nurs Staff Dev Insid. Jan-Feb 

1992;1(1):4, 7. Comment.

2260. Rodriguez RM, Dresden GM, Young JC. Patient and 

provider attitudes toward commercial television film 

crews in the emergency department. Acad Emerg 

Med. Jul 2001;8(7):740-745. Not eligible exposure. 

2261. Rogers AE, Hwang WT, Scott LD, Aiken LH, Dinges 

DF. The working hours of hospital staff nurses and 

patient safety. Health Aff (Millwood). Jul-Aug 

2004;23(4):202-212. Not eligible outcomes. 

2262. Rogers AE, Hwang W, Scott LD. The effects of work 

breaks on staff nurse performance. Journal of Nursing 

Administration Nov 2004;34(11):512-9. Not relevant. 

2263. Rogers R. The Beverly Allitt case. Qualified in 

caring? Nurs Stand. Feb 23-Mar 1 1994;8(22):21-22. 

Not eligible target population. 

2264. Rohland P. N.J. passes bill to end mandatory 

overtime. Revolution. Jul-Aug 2000;1(4):10-11. 

News.

2265. Rollins D. Study side notes. Nurs Manage. Sep 

2003;34(9):10. Comment. 

2266. Rollins G. Workforce. Who's exempt? New overtime 

rules still getting scrutiny from nurse unions and 

lawmakers. Hosp Health Netw. Apr 2005;79(4):30. 

News. 

2267. Romea S, Alkiza ME, Ramon JM, Oromi J. Risk for 

occupational transmission of HIV infection among 

health care workers. Study in a Spanish hospital. Eur 

J Epidemiol. Apr 1995;11(2):225-229. Not eligible 

target population. 

2268. Ronsmans C, Etard JF, Walraven G, Hoj L, Dumont 

A, de Bernis L, Kodio B. Maternal mortality and 

access to obstetric services in West Africa. Trop Med 

Int Health. Oct 2003;8(10):940-948. Not eligible 

target population. 

2269. Roscoe J, Haig N. Shift work. Planning shift patterns. 

Nurs Times. Sep 19-25 1990;86(38):31-33. Comment. 
B-67 

2270. Roseman C, Booker JM. Workload and 

environmental factors in hospital medication errors. 

Nurs Res. Jul-Aug 1995;44(4):226-230. Not eligible 

outcomes. 

2271. Rosen LF. The changing face of staffing--UAPs. 

Todays Surg Nurse. May-Jun 1999;21(3):39-40. 

Comment. 

2272. Rosenbach ML. CRNA vacancy rates in US hospitals. 

Nurse anesthesia Jun 1990;1(2):61-70. Not relevant. 

2273. Rosenfeld P, Harrington C. Hospital care for elderly. 

Am J Nurs. May 2003;103(5):115. Review. 

2274. Rosenstein AH, O'Daniel M. Study links disruptive 

behavior to negative patient outcomes. OR Manager. 

Mar 2005;21(3):1, 20, 22. Comment. 

2275. Rosenthal VD, Guzman S, Safdar N. Effect of 

education and performance feedback on rates of 

catheter-associated urinary tract infection in intensive 

care units in Argentina. Infect Control Hosp 

Epidemiol. Jan 2004;25(1):47-50. Not eligible 

exposure. 

2276. Rothberg MB, Abraham I, Lindenauer PK, Rose DN. 

Improving nurse-to-patient staffing ratios as a costeffective safety intervention. Med Care. Aug 

2005;43(8):785-791. Review. 

2277. Rothman LW. Implementing patient-focused care: 

success indicators for measuring satisfaction. Recruit 

Retent Restruct Rep. Sep 1995;8(9):1-6. No 

association tested. 

2278. Rothrock JC, Smith DA. Selecting the perioperative 

patient focused model. Aorn J. May 2000;71(5):1030-

1034, 1036-1037. Not eligible exposure. 

2279. Routh BA, Stafford R. Implementing a patientfocused care delivery model. J Nurs Staff Dev. JulAug 1996;12(4):208-212. No association tested. 

2280. Rowe J. Making oneself at home? Examining the 

nurse-parent relationship. Contemp Nurse. Sep 

1996;5(3):101-106. Not eligible target population. 

2281. Rowen L, Raymond R, Thomas K. The patient care 

delivery mode at Mercy Medical Center: a licensed 

caregiver model. Aspens Advis Nurse Exec. Dec 

1998;14(3):1, 3-6. Not eligible exposure. 

2282. Rowland W. Patients' perceptions of nurse uniforms. 

Nurs Stand. Feb 2-8 1994;8(19):32-36. Not eligible 

exposure. 

2283. Ruane-Morris M, Thompson G, Lawton S. Designing 

a nursing model for dermatology. Prof Nurse. Jun 

1995;10(9):565-566. Comment.

2284. Rudy EB, Lucke JF, Whitman GR, Davidson LJ. 

Benchmarking patient outcomes. J Nurs Scholarsh. 

2001;33(2):185-189. Not eligible outcomes. 

2285. Rudy S, Sions J. Floating: managing a recruitment 

and retention issue. J Nurs Adm. Apr 2003;33(4):196-

198. No association tested. 

2286. Ruflin P, Matlack R, Holy C, Sorbello S, Nadzan L, 

Selden T. Closed-unit staffing speaks volumes. Nurs 

Manage. Jun 1999;30(6):37-39; quiz 40. Comment.

2287. Ruland CM, Ravn IH. Usefulness and effects on costs 

and staff management of a nursing resource 

management information system. Journal of nursing 

management May 2003;11(3):208-15. Not relevant. 

2288. Runeson I, Hallstrom I, Elander G, Hermeren G. 

Children's participation in the decision-making 

process during hospitalization: an observational 

study. Nurs Ethics. Nov 2002;9(6):583-598. Not 

eligible target population. 

2289. Runy LA. The health care workforce. State-by-state 

numbers and initiatives. Hosp Health Netw. Aug 

2002;76(8):41-46. Comment. 

2290. Rusch LM. Supporting clinical nursing leadership and 

professional practice at the unit level. Nurs Leadersh 

Forum. Winter 2004;9(2):61-66. No association 

tested. 

2291. Rush J, Fiorino-Chiovitti R, Kaufman K, Mitchell A. 

A randomized controlled trial of a nursery ritual: 

wearing cover gowns to care for healthy newborns. 

Birth. Mar 1990;17(1):25-30. Not eligible exposure. 

2292. Rushforth K. A randomised controlled trial of 

weaning from mechanical ventilation in paediatric 

intensive care (PIC). Methodological and practical 

issues. Intensive Crit Care Nurs. Apr 2005;21(2):76-

86. Not eligible target population. 

2293. Russell D. Changing public health nursing practice. 

Nurs N Z. Dec-2000 Jan 1999;5(11):18-19. Comment. 

2294. Russell LJ, Reynolds TM. How accurate are pressure 

ulcer grades? An image-based survey of nurse 

performance. J Tissue Viability. Apr 2001;11(2):67, 

70-65. Not eligible target population.

2295. Russell S. Reducing readmissions to the intensive 

care unit. Heart Lung. Sep-Oct 1999;28(5):365-372. 

Not eligible target population. 

2296. Ruth M, Locsin R. The effect of music listening on 

acute confusion and delirium in elders undergoing 

elective hip and knee surgery. J Clin Nurs. Sep 

2004;13(6B):91-96. Not eligible exposure. 

2297. Ryan CA, Clark LM, Malone A, Ahmed S. The effect 

of a structured neonatal resuscitation program on 

delivery room practices. Neonatal Netw. Feb 

1999;18(1):25-30. Not eligible target population. 

2298. Ryan DW, Bayly PJ, Weldon OG, Jingree M. A 

prospective two-month audit of the lack of provision 

of a high-dependency unit and its impact on intensive 

care. Anaesthesia. Mar 1997;52(3):265-270. Legal 

cases. 

2299. Ryan M. On the record. Nurs Stand. Mar 18-24 

1998;12(26):23. Comment.

2300. Ryan M. A buddy program for international nurses. J 

Nurs Adm. Jun 2003;33(6):350-352. News. 

2301. Ryan T, Hills B, Webb L. Nurse staffing levels and 

budgeted expenditure in acute mental health wards: a 

benchmarking study. J Psychiatr Ment Health Nurs. 

Feb 2004;11(1):73-81. Not eligible target population. 

2302. Ryrie I, McGowan J. Staff perceptions of substance 

use among acute psychiatry inpatients. J Psychiatr 

Ment Health Nurs. Apr 1998;5(2):137-142. Not 

eligible target population. 

2303. Sadaba JR, Wheatley GH. Surgical assistants and 

working time directives. Eur J Cardiothorac Surg. Jun 

2004;25(6):1130-1131; author reply 1131-1132. 

Comment. 
B-68 

2304. Safdar N, Kluger DM, Maki DG. A review of risk 

factors for catheter-related bloodstream infection 

caused by percutaneously inserted, noncuffed central 

venous catheters: implications for preventive 

strategies. Medicine (Baltimore). Nov 

2002;81(6):466-479. Review. 

2305. Saigal S, Stoskopf BL, Feeny D, Furlong W, Burrows 

E, Rosenbaum PL, Hoult L. Differences in 

preferences for neonatal outcomes among health care 

professionals, parents, and adolescents. Jama. Jun 2 

1999;281(21):1991-1997. Not eligible exposure.

2306. Salamon L, Lennon M. Decreasing companion usage 

without negatively affecting patient outcomes: a 

performance improvement project. MEDSURG 

Nursing Aug 2003;12(4):230-7. Not relevant. 

2307. Sales A, Lurie N, Moscovice I, Goes J. Is quality in 

the eye of the beholder? Jt Comm J Qual Improv. 

May 1995;21(5):219-225. Not eligible exposure. 

2308. Salluzzo RF, Bartfield JM, Freed H, Graber M, Peters 

T. Attitude of emergency department patients toward 

HIV-infected health care workers. Am J Emerg Med. 

Mar 1997;15(2):141-144. Not eligible exposure. 

2309. Salt P, Clancy M. Implementation of the Ottawa 

Ankle Rules by nurses working in an accident and 

emergency department. J Accid Emerg Med. Nov 

1997;14(6):363-365. Not eligible target population. 

2310. Salvage D. Drug administration and professional 

accountability. Prof Nurse. Aug 1997;12(11):827. 

Comment. 

2311. Salyer J. Environmental turbulence. Impact on nurse 

performance. J Nurs Adm. Apr 1995;25(4):12-20. Not 

eligible exposure. 

2312. Sanchez-Sweatman L. The law, nurses and coffee 

breaks. Can Nurse. Dec 1995;91(11):39-40. Legal 

cases. 

2313. Sandall J. Choice, continuity and control: changing 

midwifery, towards a sociological perspective. 

Midwifery. Dec 1995;11(4):201-209. Not eligible 

target population. 

2314. Sanderson D. Research shows nursing agencies in a 

positive light. Br J Nurs. Jun 24-Jul 7 

2004;13(12):690. Not eligible target population. 

2315. Sandford DA, Elzinga RH, Iversen R. A quantitative 

study of nursing staff interactions in psychiatric 

wards. Acta Psychiatr Scand. Jan 1990;81(1):46-51. 

Not eligible target population. 

2316. Sandiford R. 'I call it the rock and roll of nursing'. 

Nurs Times. Aug 3-9 2004;100(31):28-29. Comment. 

2317. Sandlin D. Take a bite out of high employee turnover. 

J Perianesth Nurs. Apr 2001;16(2):109-111. 

Comment. 

2318. Sanford K. Nurses, let's support each other more. 

Nursing. Jan 1990;20(1):109-118. Not eligible 

exposure. 

2319. Santamaria N. The relationship between nurses' 

personality and stress levels reported when caring for 

interpersonally difficult patients. Aust J Adv Nurs. 

Dec-2001 Feb 2000;18(2):20-26. Not eligible 

exposure. 

2320. Santamaria N, O'Sullivan S. Stress in perioperative 

nursing: sources, frequency and correlations to 

personality factors. Collegian. Jul 1998;5(3):10-15. 

Not eligible target population. 

2321. Sanz C, Sunol R, Abello C, Blanc A. Design and 

results of the nursing quality assurance program in 

Hospital de la Santa Creu i Sant Pau: an integrated 

effort. Qual Assur Health Care. Sep 1993;5(3):267-

273. Not eligible target population. 

2322. Sartain SA, Clarke CL, Heyman R. Hearing the 

voices of children with chronic illness. J Adv Nurs. 

Oct 2000;32(4):913-921. Not eligible target 

population. 

2323. Sasichay-Akkadechanunt T, Scalzi CC, Jawad AF. 

The relationship between nurse staffing and patient 

outcomes. J Nurs Adm. Sep 2003;33(9):478-485. Not 

eligible target population. 

2324. Saver C. Nursing gets an "A". Nurs Spectr (Wash D 

C). Aug 11 1997;7(16):3. Editorial. 

2325. Sawaki Y, Parker RK, White PF. Patient and nurse 

evaluation of patient-controlled analgesia delivery 

systems for postoperative pain management. J Pain 

Symptom Manage. Nov 1992;7(8):443-453. Not 

eligible exposure. 

2326. Saxena AK, Panhotra BR. The impact of nurse 

understaffing on the transmission of hepatitis C virus 

in a hospital-based hemodialysis unit. Med Princ 

Pract. May-Jun 2004;13(3):129-135. Not eligible 

target population. 

2327. Saxena AK, Panhotra BR, Sundaram DS, Naguib M, 

Venkateshappa CK, Uzzaman W, Mulhim KA. 

Impact of dedicated space, dialysis equipment, and 

nursing staff on the transmission of hepatitis C virus 

in a hemodialysis unit of the middle east. Am J Infect 

Control. Feb 2003;31(1):26-33. Not eligible target 

population. 

2328. Sayers M, Marando R, Fisher S, Aquila A, Morrison 

B, Dailey T. No need for pain. J Healthc Qual. MayJun 2000;22(3):10-15. Not eligible exposure. 

2329. Scarbrough ML, Landis SE. A pilot study for the 

development of a hospital-based immunization 

program. Clin Nurse Spec. Mar 1997;11(2):70-75. 

Not eligible exposure. 

2330. Schaffner A, Costa L, Propotnik T. Nurse sabbatical: 

reflections on professionalism. Nurs Manage. Sep 

1992;23(9):118. Comment. 

2331. Schaffner JW, Alleman S, Ludwig-Beymer P, 

Muzynski J, King DJ, Pacura LJ. Developing a 

patient care model for an integrated delivery system. J 

Nurs Adm. Sep 1999;29(9):43-50. Review. 

2332. Schaffner M. Fighting fatigue. More than just a 

resident issue? Gastroenterol Nurs. Mar-Apr 

2003;26(2):82-83. Comment. 

2333. Scharer K. Nurse-parent relationship building in child 

psychiatric units. J Child Adolesc Psychiatr Nurs. 

Oct-Dec 1999;12(4):153-167. Not eligible exposure. 

2334. Scharer K. Admission: a crucial point in relationship 

building between parents and staff in child psychiatric 

units. Issues Ment Health Nurs. Dec 2000;21(8):723-

744. Not eligible exposure. 
B-69 

2335. Scharf L, Caley L. Patients', nurses', and physicians' 

perceptions of nurses' caring behaviors. 

Nursingconnections. Spring 1993;6(1):3-12. Not 

eligible outcomes. 

2336. Scheerle PK. P. K. Scheerle. Interview by Marietta 

Lee. Am J Nurs. Jul 1994;94(7):38-40. Interview. 

2337. Scherer YK, Haughey BP, Wu YW, Miller CM. A 

longitudinal study of nurses' attitudes toward caring 

for patients with AIDS in Erie County. J N Y State 

Nurses Assoc. Sep 1992;23(3):10-15. Not eligible 

exposure. 

2338. Schildmeier D. Brockton nurses end 103-day strike. 

Contract includes staffing/mandatory OT protections. 

Revolution. Sep-Oct 2001;2(5):5. News. 

2339. Schildmeier D. Massachusetts safe staffing: time runs 

out for bill this year but final hurdle on horizon. 

Revolution. Jul-Aug 2004;5(4):9. News. 

2340. Schildmeier D. MNA blows whistle on hospitals 

using paramedics in RN roles. Revolution. Jan-Feb 

2004;5(1):8-9. Review. 

2341. Schmidt CE, Bottoni T. Improving medication safety 

and patient care in the emergency department. J 

Emerg Nurs. Feb 2003;29(1):12-16. Comment. 

2342. Schmidt LA. Patients' perceptions of nurse staffing, 

nursing care, adverse events, and overall satisfaction 

with the hospital experience. Nurs Econ. Nov-Dec 

2004;22(6):295-306, 291. Not eligible exposure.

2343. Schmieder RA, Smith CS. Moderating effects of 

social support in shiftworking and non-shiftworking 

nurses. Work & Stress Apr-Jun 1996;10(2):128-40. 

Not relevant. 

2344. Schneider MP, Cotting J, Pannatier A. Evaluation of 

nurses' errors associated in the preparation and 

administration of medication in a pediatric intensive 

care unit. Pharm World Sci. Aug 1998;20(4):178-182. 

Not eligible target population. 

2345. Schnelle JF, Simmons SF, Harrington C, et al. 

Relationship of nursing home staffing to quality of 

care. Health services research Apr 2004;39(2):225-50. 

Nursing home. 

2346. Schoenfeld PS, Baker MD. Documentation in the 

pediatric emergency department: a review of 

resuscitation cases. Ann Emerg Med. Jun 

1991;20(6):641-643. Not eligible exposure.

2347. Scholz DA. Establishing and monitoring an endemic 

medication error rate. J Nurs Qual Assur. Feb 

1990;4(2):71-74. Not eligible outcomes. 

2348. Scholz JA. Issue: how do you tell your patients that 

you are short-staffed? Ohio Nurses Rev. Feb 

1997;72(2):16. Comment. 

2349. Scholz JA. Issue: what guidelines does the Joint 

Commission on Accreditation of Healthcare 

Organizations use to determine if a hospital has 

adequate staffing for patient care? Ohio Nurses Rev. 

May 1998;73(5):16. Comment. 

2350. Schraeder M, Friedman LH. Collective bargaining in 

the nursing profession: salient issues and recent 

developments in healthcare reform. Hosp Top. 

Summer 2002;80(3):21-24. Review. 

2351. Schroder PJ, Washington WP. Administrative 

decision making: staff-patient ratios (a patient 

classification system for a psychiatric setting). 

Perspect Psychiatr Care. Jul-Sep 1982;20(3):111-123. 

Not eligible year. 

2352. Schulmeister L. Chemotherapy medication errors: 

descriptions, severity, and contributing factors. Oncol 

Nurs Forum. Jul 1999;26(6):1033-1042. Not eligible 

outcomes. 

2353. Schumacher KL. Reconceptualizing family 

caregiving: family-based illness care during 

chemotherapy. Res Nurs Health. Aug 

1996;19(4):261-271. Not eligible exposure.

2354. Schwarz HO, Brodowy BA. Implementation and 

evaluation of an automated dispensing system. Am J 

Health Syst Pharm. Apr 15 1995;52(8):823-828. Not 

eligible exposure. 

2355. Sciabarra C, Kronawetter N, Jacob M, Ruelo V, 

Falero Y, Quigley PA. Implementing practice 

innovations to improve nurse-client relationships. 

Rehabil Nurs. Mar-Apr 1999;24(2):51-54. Not 

eligible outcomes. 

2356. Scott CA, Fish TR, Allen PJ. Design of an intensive 

epilepsy monitoring unit. Epilepsia. 2000;41 Suppl 

5:S3-8. Not eligible target population. 

2357. Scott LD, Hwang W, Rogers AE. The impact of 

multiple care giving roles on fatigue, stress, and work 

performance among hospital staff nurses. Journal of 

Nursing Administration Feb 2006;36(2):86-95. Not 

relevant. 

2358. Scott H. Putting patient-centred care at the heart of 

nursing. Br J Nurs. Sep 9-22 2004;13(16):937. 

Editorial. 

2359. Scott J. The closing down of a hospital is deeply 

traumatic for patients and staff. Nurs Times. Dec 1-7 

1999;95(48):21. Not eligible target population. 

2360. Scott RA. Multi-site coverage gives new meaning to 

"beyond the walls". Clin Nurse Spec. Mar 

2000;14(2):51-53. News. 

2361. Seaberg DC, MacLeod BA. Correlation between 

triage nurse and physician ordering of ED tests. Am J 

Emerg Med. Jan 1998;16(1):8-11. Not eligible 

exposure. 

2362. Seago JA. Registered nurses, unlicensed assistive 

personnel, and organizational culture in hospitals. J 

Nurs Adm. May 2000;30(5):278-286. Not eligible 

outcomes. 

2363. Seago JA. A comparison of two patient classification 

instruments in an acute care hospital. J Nurs Adm. 

May 2002;32(5):243-249. Not eligible exposure. 

2364. Seccombe I. Right to nurse. Pay special: a bit 

excessive. Nurs Stand. Mar 8-14 1995;9(24):45. Not 

eligible target population. 

2365. Sefton G, Farrell M, Noyes J. The perceived learning 

needs of paediatric intensive care nurses caring for 

children requiring haemofiltration. Intensive Crit Care 

Nurs. Feb 2001;17(1):40-50. Not eligible target 

population. 

2366. Segesten K, Lundgren S, Lindstrom I. Versatility--

consequence of changing from mixed to all registered 

nurse staffing on a surgical ward. J Nurs Manag. Jul 

1998;6(4):223-230. Not eligible target population. 
B-70 

2365. Seigerst EG. East Liverpool City Hospital nurses 

make sweeping improvements. Ohio Nurses Rev. 

Aug 2000;75(7):15. Not eligible target population. 

2366. Seigerst EG. Geneva negotiations. Ohio Nurses Rev. 

Feb 2000;75(2):12. News. 

2367. Selbst SM, Fein JA, Osterhoudt K, Ho W. Medication 

errors in a pediatric emergency department. Pediatr 

Emerg Care. Feb 1999;15(1):1-4. Not eligible 

exposure. 

2368. Selekman J, Snyder B. Nursing perceptions of using 

physical restraints on hospitalized children. Pediatr 

Nurs. Sep-Oct 1995;21(5):460-464. Not eligible 

exposure. 

2369. Sella S, MacLeod JA. One year later: evaluating a 

changing delivery system. Nurs Forum. 1991;26(2):5-

11. Not eligible outcomes. 

2370. Sellick KJ, Russell S, Beckmann JL. Primary nursing: 

an evaluation of its effects on patient perception of 

care and staff satisfaction. International Journal of 

Nursing Studies (1983), 20, 265-273. Int J Nurs Stud. 

Jul 2003;40(5):545-551; discussion 553-544. Not 

eligible target population. 

2371. Selvam A. The state of the health care workforce. 

Hosp Health Netw. Aug 2001;75(8):41, 43-46, 48. 

Comment.

2372. Seo Y, Ko J, Price JL. The determinants of job 

satisfaction among hospital nurses: a model 

estimation in Korea. Int J Nurs Stud. May 

2004;41(4):437-446. Not eligible target population. 

2373. Sermeus W, Hoy D, Jodrell N, Hyslop A, Gypen T, 

Kinnunen J, Mantas J, Delesie L, Tansley J, Hofdijk 

J. The WISECARE Project and the impact of 

information technology on nursing knowledge. Stud 

Health Technol Inform. 1997;46:176-181. Not 

eligible target population. 

2374. Shader K, Broome ME, Broome CD, West ME, Nash 

M. Factors influencing satisfaction and anticipated 

turnover for nurses in an academic medical center. J 

Nurs Adm. Apr 2001;31(4):210-216. Not eligible 

outcomes. 

2375. Shah A, De T. The effect of an educational 

intervention package about aggressive behaviour 

directed at the nursing staff on a continuing care 

psychogeriatric ward. Int J Geriatr Psychiatry. Jan 

1998;13(1):35-40. Not eligible exposure. 

2376. Shaha SH, Bush C. Fixing acuity: a professional 

approach to patient classification and staffing. Nurs 

Econ. Nov-Dec 1996;14(6):346-356. No association 

tested. 

2377. Shahinpour N, Hollinger-Smith L, Perlia MA. The 

medical-psychiatric consultation liaison nurse. 

Meeting psychosocial needs of medical patients in the 

acute care setting. Nurs Clin North Am. Mar 

1995;30(1):77-86. Not eligible exposure.

2378. Shamian J. Skill mix and clinical outcomes. Can Oper 

Room Nurs J. Jun 1998;16(2):36-41. No association 

tested. 

2379. Shang E, Suchner U, Dormann A, Senkal M. 

Structure and organisation of 47 nutrition support 

teams in Germany: a prospective investigation in 

2000 German hospitals in 1999. Eur J Clin Nutr. Oct 

2003;57(10):1311-1316. Not eligible target 

population. 

2380. Sharma T, Carson J, Berry C. Patient voices. Health 

Serv J. Jan 16 1992;102(5285):20-21. Not eligible 

target population. 

2381. Sharu D. Attribution of blame for a child's disability. 

Prof Nurse. Sep 1996;11(12):790-792. Not eligible 

target population. 

2382. Shattell M. Nurse bait: strategies hospitalized patients 

use to entice nurses within the context of the 

interpersonal relationship. Issues Ment Health Nurs. 

Feb-Mar 2005;26(2):205-223. Not eligible exposure. 

2383. Shen HC, Cheng Y, Tsai PJ, Lee SH, Guo YL. 

Occupational stress in nurses in psychiatric 

institutions in Taiwan. J Occup Health. May 

2005;47(3):218-225. Not eligible target population. 

2384. Sherer JL. Next steps for nursing. Hosp Health Netw. 

Aug 20 1993;67(16):26-28. Comment. 

2385. Sheward L, Hunt J, Hagen S, Macleod M, Ball J. The 

relationship between UK hospital nurse staffing and 

emotional exhaustion and job dissatisfaction. J Nurs 

Manag. Jan 2005;13(1):51-60. Not eligible target 

population. 

2386. Shields L, Hunter J, Hall J. Parents' and staff's 

perceptions of parental needs during a child's 

admission to hospital: an English perspective. J Child 

Health Care. Mar 2004;8(1):9-33. Not eligible target 

population. 

2387. Shields L, King S. Qualitative analysis of the care of 

children in hospital in four countries-Part 2. J Pediatr 

Nurs. Jun 2001;16(3):206-213. Not eligible target 

population. 

2388. Shields L, Tanner A. Pilot study of a tool to 

investigate perceptions of family-centered care in 

different care settings. Pediatr Nurs. May-Jun 

2004;30(3):189-197. Not eligible target population. 

2389. Shih FJ, Liao YC, Chan SM, Duh BR, Gau ML. The 

impact of the 9-21 earthquake experiences of 

Taiwanese nurses as rescuers. Soc Sci Med. Aug 

2002;55(4):659-672. Not eligible target population. 

2390. Shindul-Rothschild J. Patient care. How good is it 

where you work? Am J Nurs. Mar 1996;96(3):22-24. 

Comment. 

2391. Shindul-Rothschild J, Long-Middleton E, Berry D. 10 

keys to quality care. Am J Nurs. Nov 1997;97(11):35-

43. No association tested. 

2392. Shinkman R. Hasta la vista for Calif. nursing ratios? 

Healthc Leadersh Manag Rep. Nov 2003;11(11):1, 7-

11, 13. Comment. 

2393. Shinkman R. Calif. hospitals move to comply with 

nurse ratios despite litigation. Healthc Leadersh Rep. 

Jan 2004;12(1):10-11. News. 

2394. Shuldham CM. Commentary. Nursing skill mix and 

staffing. J Nurs Manag. Nov 2004;12(6):385-387. Not 

eligible target population. 
B-71 

2395. Shullanberger G. Nurse staffing decisions: an 

integrative review of the literature. Nursing 

Economics May-Jun 2000;18(3):124-32, 46-8. 

Integrative review. 

2396. Shusterman C. How immigration laws affect 

hospitals. Hosp Top. Summer 1993;71(3):38-40. 

Comment. 

2397. Sibbald B. Getting an early start on early discharge. 

Can Nurse. Mar 1997;93(3):18. Comment.

2398. Siders AM, Peterson M. Increasing patient 

satisfaction and nursing productivity through 

implementation of an automated nursing discharge 

summary. Proc Annu Symp Comput Appl Med Care. 

1991:136-140. Not eligible outcomes. 

2399. Silber JH, Williams SV, Krakauer H, Schwartz JS. 

Hospital and patient characteristics associated with 

death after surgery. A study of adverse occurrence 

and failure to rescue. Med Care. Jul 1992;30(7):615-

629. Not eligible exposure. 

2400. Silva N, Aderholdt B. Monitoring nursing 

productivity: a unique approach integrating an on-line 

kardex with workload measurement. Comput Nurs. 

Nov-Dec 1992;10(6):232-234. Comment. 

2401. Silverman HJ, Tuma P, Schaeffer MH, Singh B. 

Implementation of the patient self-determination act 

in a hospital setting. An initial evaluation. Arch Intern 

Med. Mar 13 1995;155(5):502-510. Not eligible 

exposure. 

2402. Silvestro R, Silvestro C. An evaluation of nurse 

rostering practices in the National Health Service. J 

Adv Nurs. Sep 2000;32(3):525-535. Not eligible 

target population. 

2403. Simmer TL, Nerenz DR, Rutt WM, Newcomb CS, 

Benfer DW. A randomized, controlled trial of an 

attending staff service in general internal medicine. 

Med Care. Jul 1991;29(7 Suppl):JS31-40. Not eligible 

exposure. 

2404. Simmons BL, Nelson DL. Eustress at work: the 

relationship between hope and health in hospital 

nurses. Health Care Manage Rev. Fall 2001;26(4):7-

18. Not eligible outcomes. 

2405. Simmons M. Implementation of a patient falls riskmanagement strategy. Prof Nurse. Nov 

2001;17(3):168-171. Not eligible target population. 

2406. Simon HK, McLario D, Daily R, Lanese C, Castillo J, 

Wright J. "Fast tracking" patients in an urban 

pediatric emergency department. Am J Emerg Med. 

May 1996;14(3):242-244. Not eligible exposure. 

2407. Simons J, Roberson E. Poor communication and 

knowledge deficits: obstacles to effective 

management of children's postoperative pain. J Adv 

Nurs. Oct 2002;40(1):78-86. Not eligible target 

population. 

2408. Simons JM, Macdonald LM. Pain assessment tools: 

children's nurses' views. J Child Health Care. Dec 

2004;8(4):264-278. Not eligible target population. 

2409. Simpson RG, Scothern G, Vincent M. Survey of carer 

satisfaction with the quality of care delivered to inpatients suffering from dementia. J Adv Nurs. Sep 

1995;22(3):517-527. Not eligible target population. 

2410. Simpson RL. IT takes a village. Improving health 

care in the 21st century. Nurs Adm Q. Apr-Jun 

2003;27(2):180-183. Review. 

2411. Simpson RL. In direct proportion: ratios, IT, and 

trust. Nurs Manage. Feb 2005;36(2):14-16. Comment. 

2412. Sims CE. Increasing clinical, satisfaction, and 

financial performance through nurse-driven process 

improvement. J Nurs Adm. Feb 2003;33(2):68-75. 

Not eligible exposure. 

2413. Sims L, Kippenbrock TA. Psychiatric nurses' 

satisfaction with a patient classification system for 

staffing. Issues Ment Health Nurs. Jul-Aug 

1994;15(4):409-417. Not eligible exposure. 

2414. Sinclair BP. Mandatory staffing ratios: a dilemma. 

AWHONN Lifelines. Apr-May 2002;6(2):91-92. 

Editorial. 

2415. Sinclair K, Collins D, Potokar J. Drug misuse by 

patients in an inner-city hospital. Nurs Stand. Jun 25-

Jul 1 2003;17(41):33-37. Not eligible target 

population. 

2416. Sincox AK. Mandatory overtime can hurt a hospital's 

financial status. Mich Nurse. Nov 2004;77(9):9. 

Comment. 

2417. Sincox AK, Harris E, Bissonnette T, Stevenson T. 

Safe patient care: a crisis in nursing. Mich Nurse. Aug 

2004:4, 16. Comment. 

2418. Siviter B, Scullion J, Jebb P, Humm C. Safety in 

numbers? Nurs Stand. Sep 25-Oct 1 2002;17(2):22. 

Not eligible target population. 

2419. Skeie B, Mishra V, Vaaler S, Amlie E. A comparison 

of actual cost, DRG-based cost, and hospital 

reimbursement for liver transplant patients. Transpl 

Int. Oct 2002;15(9-10):439-445. Not eligible target 

population. 

2420. Sklar J. Pain-less floating. Nurs Manage. Jul 

1992;23(7):104. Comment. 

2421. Slaughter J. Up against a giant. Nurses quash Tenet's 

demand for 16-hour shifts, win 'slam-dunk'. 

Revolution. May-Jun 2000;1(3):5. News. 

2422. Slaughter J. Beyond outrage. Revolution. Jan-Feb 

2000;1(1):28-35. Comment. 

2423. Slomka J, Hoffman-Hogg L, Mion LC, Bair N, Bobek 

MB, Arroliga AC. Influence of clinicians' values and 

perceptions on use of clinical practice guidelines for 

sedation and neuromuscular blockade in patients 

receiving mechanical ventilation. Am J Crit Care. 

Nov 2000;9(6):412-418. Not eligible exposure. 

2424. Slota MC, Balas-Stevens S. Implementing and 

evaluating a change to 12-hour shifts. Neonatal Netw. 

Jun 1990;8(6):51-56. Not eligible outcomes. 

2425. Smedbold HT, Ahlen C, Unimed S, Nilsen AM, 

Norback D, Hilt B. Relationships between indoor 

environments and nasal inflammation in nursing 

personnel. Arch Environ Health. Mar-Apr 

2002;57(2):155-161. Not eligible target population.

2426. Smedley J, Egger P, Cooper C, Coggon D. 

Prospective cohort study of predictors of incident low 

back pain in nurses. Bmj. Apr 26 

1997;314(7089):1225-1228. Not eligible target 

population. 
B-72 

2427. Smedley J, Inskip H, Buckle P, Cooper C, Coggon D. 

Epidemiological differences between back pain of 

sudden and gradual onset. J Rheumatol. Mar 

2005;32(3):528-532. Not eligible target population. 

2428. Smedley J, Inskip H, Cooper C, Coggon D. Natural 

history of low back pain. A longitudinal study in 

nurses. Spine. Nov 15 1998;23(22):2422-2426. Not 

eligible target population. 

2429. Smedley J, Inskip H, Trevelyan F, Buckle P, Cooper 

C, Coggon D. Risk factors for incident neck and 

shoulder pain in hospital nurses. Occup Environ Med. 

Nov 2003;60(11):864-869. Not eligible target 

population. 

2430. Smedley J, Trevelyan F, Inskip H, Buckle P, Cooper 

C, Coggon D. Impact of ergonomic intervention on 

back pain among nurses. Scand J Work Environ 

Health. Apr 2003;29(2):117-123. Not eligible target 

population. 

2431. Smeltzer CH. The Chicago plan: innovative strategies 

to change nurses' work patterns. J Nurs Adm. Sep 

1990;20(9):3-5. Editorial.

2432. Smetzer JL. Lesson from Colorado. Beyond blaming 

individuals. Nurs Manage. Jun 1998;29(6):49-51. 

Legal Cases. 

2433. Smith AM, Ortiguera SA, Laskowski ER, Hartman 

AD, Mullenbach DM, Gaines KA, Larson DR, Fisher 

W. A preliminary analysis of psychophysiological 

variables and nursing performance in situations of 

increasing criticality. Mayo Clin Proc. Mar 

2001;76(3):275-284. Not eligible exposure. 

2434. Smith AP. Saving nurses, saving patients: responses 

to the labor crisis. J Med Pract Manage. Jan-Feb 

2004;19(4):193-197. Review. 

2435. Smith DM, Gow P. Towards excellence in quality 

patient care: a clinical pathway for myocardial 

infarction. J Qual Clin Pract. Jun 1999;19(2):103-105. 

Not eligible target population. 

2436. Smith DR, Ohmura K, Yamagata Z. Prevalence and 

correlates of hand dermatitis among nurses in a 

Japanese teaching hospital. J Epidemiol. May 

2003;13(3):157-161. Not eligible target population. 

2437. Smith F, Valentine F. Value added decisions. Paediatr 

Nurs. Sep 1999;11(7):9-10. Not eligible target 

population. 

2438. Smith GB. Shifts in attitudes about self-esteem in the 

recovering chemically dependent nurse. Addictions 

Nursing Network Summer 1993;5(2):60-3. Not peer 

reviewed. 

2439. Smith J, Crawford L. Medication errors and difficulty 

in first patient assignments of newly licensed nurses. 

JONAS Healthc Law Ethics Regul. Sep 2003;5(3):65-

67. Not eligible outcomes. 

2440. Smith J, Gamroth LM. The resident: the heart of it. 

Geriatr Nurs. May-Jun 1995;16(3):113-116. Case 

Reports. 

2441. Smith K, Uphoff ME. Uncharted terrain: dilemmas 

born in the NICU grow up in the PICU. J Clin Ethics. 

Fall 2001;12(3):231-238. Case Reports. 

2442. Smith LW, Mills JV. Psychometric evaluation of 

pharmacology calculation test for hospital staff 

nurses. J Healthc Educ Train. 1993;7(2):1-6. Not 

eligible exposure. 

2443. Smith M, Doctor M, Boulter T. Unique 

considerations in caring for a pediatric burn patient: a 

developmental approach. Crit Care Nurs Clin North 

Am. Mar 2004;16(1):99-108. Case reports. 

2444. Smith M, Specht J, Buckwalter KC. Geropsychiatric 

inpatient care: what is state of the art? Issues Ment 

Health Nurs. Jan 2005;26(1):11-22. No association 

tested. 

2445. Smith MK, Janzen SK, Schaefer S, Hixon AK. 

Administrative support for addressing staff nurses' 

ethical concerns regarding staffing. J Nurs Adm. Mar 

2001;31(3):103-104. Letter. 

2446. Smith P. The effectiveness of a preceptorship model 

in postgraduate education for rural nurses. Aust J 

Rural Health. Aug 1997;5(3):147-152. Not eligible 

target population. 

2447. Smith P, Adams D, Bersante S, Kalma S. Planning for 

patient care redesign: success through continuous 

quality improvement. J Nurs Care Qual. Jan 

1994;8(2):73-80. Comment. 

2448. Smith S. Understanding the experience of training for 

overseas nurses. Nurs Times. Oct 5-11 

2004;100(40):40-42. Not eligible target population. 

2449. Smith SA. RNs and UAPs: not much difference? Rn. 

Jul 1998;61(7):37-38. Comment. 

2450. Smith SP. Nurses on the move. Saudi Arabia: land of 

adventure & opportunity. Revolution. Spring 

1995;5(1):39-42. Not eligible target population.

2451. SmithBattle L, Diekemper M, Leander S. Getting 

your feet wet: becoming a public health nurse, part 1. 

Public Health Nursing Jan-Feb 2004;21(1):3-11. Not 

relevant. 

2452. Sneed NV, Hollerbach AD. Accuracy of heart rate 

assessment in atrial fibrillation. Heart Lung. Sep-Oct 

1992;21(5):427-433. Case Reports. 

2453. Snow T. Too few to care. Nurs Stand. Sep 8-14 

2004;18(52):12-13. Comment. 

2454. Snowdon AW. Personal Construct Theory: a strategy 

for the study of multidimensional phenomena in 

nursing. Can J Nurs Res. Sep 2004;36(3):131-145. 

Not eligible exposure. 

2455. Soar J, McKay U. A revised role for the hospital 

cardiac arrest team? Resuscitation. Sep 

1998;38(3):145-149. Not eligible target population. 

2456. Sobo EJ. Pediatric nurses may misjudge parent 

communication preferences. J Nurs Care Qual. JulSep 2004;19(3):253-262. Not eligible exposure. 

2457. Sochalski J, Estabrooks CA, Humphrey CK. Nurse 

staffing and patient outcomes: evolution of an 

international study. Can J Nurs Res. Dec 

1999;31(3):69-88. Review. 

2458. Soderberg A, Gilje F, Norberg A. Dignity in 

situations of ethical difficulty in intensive care. 

Intensive Crit Care Nurs. Jun 1997;13(3):135-144. 

Not eligible target population. 

2459. Soliman F. Improving resource utilization through 

patient dependency systems. J Med Syst. Oct 

1997;21(5):291-302. Not eligible target population. 

2460. Soliman F. Patient Dependency Knowledge-Based 

Systems. J Med Syst. Oct 1998;22(5):357-370. Not 

eligible target population. 
B-73 

2461. Soliman F. Automation of patient dependency 

systems. J Med Syst. Aug 1998;22(4):225-236. Not 

eligible target population. 

2462. Soltani H, Dickinson F, Tanner J. Developing a 

maternity unit visiting policy. Pract Midwife. Oct 

2004;7(9):27-30. Not eligible exposure. 

2463. Somers A, Petrovic M, Robays H, Bogaert M. 

Reporting adverse drug reactions on a geriatric ward: 

a pilot project. Eur J Clin Pharmacol. Feb 

2003;58(10):707-714. Not eligible target population.

2464 Sorrentino EA, Simunek LA. Nurses' perceptions of 

temporary nursing service agencies. Health Care 

Supervisor Apr 1991;9(3):55-62. Inadequate data 

presentation. 

2465. Souder E, O'Sullivan P. Disruptive behaviors of older 

adults in an institutional setting. Staff time required to 

manage disruptions. J Gerontol Nurs. Aug 

2003;29(8):31-36. Not eligible target population. 

2466. Souhrada L. Bumpy junction may lie between 

supplies and nursing models. Mater Manag Health 

Care. Jun 1995;4(6):34, 36, 38. Comment. 

2467. Sourial R, McCusker J, Cole M, Abrahamowicz M. 

Agitation in demented patients in an acute care 

hospital: prevalence, disruptiveness, and staff burden. 

Int Psychogeriatr. Jun 2001;13(2):183-197. Not 

eligible target population. 

2468. Southard-Ritter M. Patient-focused care: what it is--

what it is not. Pa Nurse. May 1995;50(5):6-7. 

Comment. 

2469. Spangler Z. Culture care of Philippine and AngloAmerican nurses in a hospital context. Culture care 

diversity and universality: a theory of nursing 

National League for Nursing 1991(Leininger 

MM):119-46. (57 ref) (Pamhet #15-2402). Not 

relevant. 

2470. Spangler Z. Transcultural care values and nursing 

practices of Philippine-American nurses. Journal of 

Transcultural Nursing Winter 1992;3(2):28-37. Not 

relevant. 

2471. Speas J. A shift in staff relationships. Holist Nurs 

Pract. Sep-Oct 2004;18(5):235-237. Review. 

2472. Spetz J. Public policy and nurse staffing: what 

approach is best? J Nurs Adm. Jan 2005;35(1):14-16. 

Review. 

2473. Spetz J, Adams S. How can employment-based 

benefits help the nurse shortage? Health Aff 

(Millwood). Jan-Feb 2006;25(1):212-218. No 

association tested. 

2474. Spiegel R, Brunner C, Ermini-Funfschilling D, 

Monsch A, Notter M, Puxty J, Tremmel L. A new 

behavioral assessment scale for geriatric out- and inpatients: the NOSGER (Nurses' Observation Scale for 

Geriatric Patients). J Am Geriatr Soc. Apr 

1991;39(4):339-347. Not eligible target population. 

2475. Spiegel T. Flexible sigmoidoscopy training for 

nurses. Gastroenterol Nurs. Nov-Dec 1995;18(6):206-

209. Not eligible exposure.

2476. Spilsbury K, Meyer J. Use, misuse and non-use of 

health care assistants: understanding the work of 

health care assistants in a hospital setting. J Nurs 

Manag. Nov 2004;12(6):411-418. Not eligible target 

population. 

2477. Sproat LJ, Inglis TJ. A multicentre survey of hand 

hygiene practice in intensive care units. J Hosp Infect. 

Feb 1994;26(2):137-148. Not eligible target 

population. 

2478. Squires A. New graduate orientation in the rural 

community hospital. Journal of continuing education 

in nursing Sep-Oct 2002;33(5):203-9. Not relevant. 

2479. Stabenow D. A prescription for addressing 

Michigan's nursing shortage. Mich Nurse. Sep 

2005;78(7):11. Comment. 

2480. Stacchini J. Does your staffing agency have JCAHO's 

stamp of approval? Nurs Manage. Apr 2005;36(4):65-

67. Review. 

2481. Stahl M. What makes the ideal dialysis setting? 

Nephrol News Issues. Oct 1998;12(10):39-40. 

Comment. 

2482. Stamouli MA, Mantas J. Development and evaluation 

of a nursing service management and administration 

information system at district hospital. Medinfo. 

2001;10(Pt 1):759-763. Not eligible target 

population.

2483. Standing T, Anthony MK, Hertz JE. Nurses' 

narratives of outcomes after delegation to unlicensed 

assistive personnel. Outcomes Manag Nurs Pract. 

Jan-Mar 2001;5(1):18-23. Not eligible exposure. 

2484. Stanford D. Who is accountable for inadequate 

staffing? Nurs N Z. Sep 2001;7(8):4. Letter. 

2485. Stannard D. The Synergy Model in practice. Being a 

good dance partner. Crit Care Nurse. Dec 

1999;19(6):86-87. Case Reports. 

2486. Staring SL. Addressing the educational needs of 

shiftworkers: should shift be a consideration? J 

Contin Educ Nurs. Mar-Apr 1995;26(2):79-83. Not 

eligible outcomes. 

2487. Stead L. Practice makes perfect. Nurs Times. Jan 20-

26 2000;96(3):41. Comment. 

2488. Stearley HE. Stat nursing--alive and well. Nurs Econ. 

Mar-Apr 1994;12(2):96-99, 105. Comment. 

2489. Stechmiller JK, Yarandi HN. Job satisfaction among 

critical care nurses. Am J Crit Care. Nov 

1992;1(3):37-44. Not eligible outcomes. 

2490. Stechmiller JK, Yarandi HN. Predictors of burnout in 

critical care nurses. Heart Lung. Nov-Dec 

1993;22(6):534-541. Not eligible outcomes. 

2491. Steele D. Mother country. Nurs Stand. Jul 1-7 

1998;12(41):24-25. Comment. 

2492. Steele L. Shifting patterns. Nurs Stand. Nov 20 

1996;11(9):14. Comment. 

2493. Steenkamp WC, van der Merwe AE. The 

psychosocial functioning of nurses in a burn unit. 

Burns. May 1998;24(3):253-258. Not eligible 

exposure. 

2494. Steinbrook R. Nursing in the crossfire. N Engl J Med. 

May 30 2002;346(22):1757-1766. Comment. 

2495. Steinhauser KE, Maddox GL, Person JL, Tulsky JA. 

The evolution of volunteerism and professional staff 

within hospice care in North Carolina. Hosp J. 

2000;15(1):35-51. Not eligible target population. 

2496. Stelling J. But is it nursing? Nurs Que. Jul-Aug 

1991;11(4):25-30, 64-29. No association tested. 
B-74 

2497. Stelling J, Milne-Smith J. Breakpoints and 

continuities: a case study of reactive change. Nurs 

Adm Q. Spring 1994;18(3):43-50. No association 

tested. 

2498. Stephen H. Yellow card for violent patients. Nurs 

Stand. Sep 16-22 1998;12(52):14. News. 

2499. Stewart M. New nursing shortage hits; causes 

complex. Am Nurse. Mar-Apr 1998;30(2):32. 

Comment. 

2500. Stimler C. A pressure ulcer toolbox for facilitating 

hospital-wide quality. Adv Wound Care. May-Jun 

1998;11(3 Suppl):13. Comment. 

2501. Stodart K. Flash point in Nelson. N Z Nurs J. Jul 

1990;83(6):16-18. Not eligible target population. 

2502. Stolman CJ, Gregory JJ, Dunn D, Levine JL. 

Evaluation of patient, physician, nurse, and family 

attitudes toward do not resuscitate orders. Arch Intern 

Med. Mar 1990;150(3):653-658. Not eligible 

outcomes. 

2503. Stopfkuchen H. Impact of national health system 

financing on quality of care in the intensive care unit: 

the German experience. Crit Care Med. Sep 

1993;21(9 Suppl):S406-407. Not eligible target 

population. 

2504. Stotka JL, Wong ES, Williams DS, Stuart CG, 

Markowitz SM. An analysis of blood and body fluid 

exposures sustained by house officers, medical 

students, and nursing personnel on acute-care general 

medical wards: a prospective study. Infect Control 

Hosp Epidemiol. Oct 1991;12(10):583-590. Not 

eligible exposure. 

2505. Stratton KM, Blegen MA, Pepper G, Vaughn T. 

Reporting of medication errors by pediatric nurses. J 

Pediatr Nurs. Dec 2004;19(6):385-392. Not eligible 

outcomes. 

2506. Street A, Cuddihy L, Best D, Wilks D, Geladas D, 

Chew S. Rostering: placing the nurse in the picture. 

Contemp Nurse. Dec 1997;6(3-4):145-151. Not 

eligible target population. 

2507. Street K, Ashcroft R, Henderson J, Campbell AV. 

The decision making process regarding the 

withdrawal or withholding of potential life-saving 

treatments in a children's hospital. J Med Ethics. Oct 

2000;26(5):346-352. Not eligible target population. 

2508. Strzalka A, Havens DS. Nursing care quality: 

comparison of unit-hired, hospital float pool, and 

agency nurses. J Nurs Care Qual. Jul 1996;10(4):59-

65. Not eligible exposure. 

2509. Stumpf LR. A comparison of governance types and 

patient satisfaction outcomes. J Nurs Adm. Apr 

2001;31(4):196-202. Not eligible association 

presentation. 

2510. Sugrue NM. Public policy initiatives and the nursing 

shortage: a disconnect. J Nurs Adm. Jan 

2005;35(1):19-22. Review. 

2511. Suhonen R, Valimaki M, Leino-Kilpi H, Katajisto J. 

Testing the individualized care model. Scand J Caring 

Sci. Mar 2004;18(1):27-36. Not eligible target 

population. 

2512. Sujijantararat R, Booth RZ, Davis LL. Nosocomial 

urinary tract infection: nursing-sensitive quality 

indicator in a Thai hospital. J Nurs Care Qual. AprJun 2005;20(2):134-139. Not eligible target 

population. 

2513. Sullivan J, Howland-Gradman J, Schell M, Goldsmith 

J. Reducing costs and improving processes for the 

interventional cardiology patient. J Cardiovasc Nurs. 

Jan 1997;11(2):22-36. Not eligible exposure.

2514. Sullivan RJ, Menapace LW, White RM. Truth-telling 

and patient diagnoses. J Med Ethics. Jun 

2001;27(3):192-197. Not eligible outcomes.

2515. Suominen T, Leino-Kilpi H, Laippala P. Nurses' role 

in informing breast cancer patients: a comparison 

between patients' and nurses' opinions. J Adv Nurs. 

Jan 1994;19(1):6-11. Not eligible target population. 

2516. Suominen T, Leino-Kilpi H, Merja M, Doran DI, 

Puukka P. Staff empowerment in Finnish intensive 

care units. Intensive Crit Care Nurs. Dec 

2001;17(6):341-347. Not eligible target population. 

2517. Sutherland K, Morgan J, Semple S. Selfadministration. QMC study methodology. Nurs 

Times. Jun 7-13 1995;91(23):30-31. Comment. 

2518. Sutherland K, Morgan J, Semple S. Selfadministration. Education and accountability. Nurs 

Times. Jun 7-13 1995;91(23):32-33. Comment. 

2519. Sutton J, Standen P, Wallace A. Incidence and 

documentation of patient accidents in hospital. Nurs 

Times. Aug 17-23 1994;90(33):29-35. Not eligible 

target population. 

2520. Svenson J, Besinger B, Stapczynski JS. Critical care 

of medical and surgical patients in the ED: length of 

stay and initiation of intensive care procedures. Am J 

Emerg Med. Nov 1997;15(7):654-657. Not eligible 

exposure. 

2521. Swain S. Serving suggestions. The ward sister's view. 

Nurs Times. Aug 12-18 1998;94(32):27. Not eligible 

target population. 

2522. Sweeney YT, Whitaker C. Successful change: 

renaissance without revolution. Semin Nurse Manag. 

Dec 1994;2(4):196-202. Not eligible exposure. 

2523. Sznajder M, Leleu G, Buonamico G, Auvert B, 

Aegerter P, Merliere Y, Dutheil M, Guidet B, Le Gall 

JR. Estimation of direct cost and resource allocation 

in intensive care: correlation with Omega system. 

Intensive Care Med. Jun 1998;24(6):582-589. Not 

eligible target population. 

2524. Tabet N, Hudson S, Sweeney V, Sauer J, Bryant C, 

Macdonald A, Howard R. An educational 

intervention can prevent delirium on acute medical 

wards. Age Ageing. Mar 2005;34(2):152-156. Not 

eligible target population. 

2525. Tabone S. Unsung nursing heroes. Tex Nurs. Jun-Jul 

1997;71(6):7. Comment. 

2526. Tabone S. Don't get mad--get help. Tex Nurs. Feb 

1997;71(2):11. Comment. 

2527. Tabone S. Staff models for the next millennium. Tex 

Nurs. May 1999;73(5):6-7, 10. Comment. 

2528. Tabone S. Staff nurse participation is key. Tex Nurs. 

Mar 2001;75(3):7, 10. Comment. 

2529. Tabone S. Nurse fatigue: the human factor. Tex Nurs. 

Jun-Jul 2004;78(5):8-10. Review. 
B-75 

2530. Tahan HA. Essentials of advocacy in case 

management. Lippincotts Case Manag. May-Jun 

2005;10(3):136-145; quiz 146-137. Review. 

2531. Takenouchi J. When no news isn't good news. How 

hospital ties with a newspaper put a story on the 

spike. Revolution. Sep-Oct 2001;2(5):18-19. 

Comment. 

2532. Tamblyn S. High risk nursing in Los Angeles. Aust 

Nurses J. Feb 1990;19(7):18-20. Comment. 

2533. Tamburri LM, DiBrienza R, Zozula R, Redeker NS. 

Nocturnal care interactions with patients in critical 

care units. Am J Crit Care. Mar 2004;13(2):102-112; 

quiz 114-105. Not eligible exposure.

2534. Tammelleo AD. Legal case briefs for nurses. IL: 

failure to diagnose pt.'s TB: attending nurse sues: 

N.H.: the school nurse: a professional engaged in 

teaching? Regan Rep Nurs Law. Mar 1991;31(10):3. 

Case Reports. 

2535. Tammelleo AD. Mystery nurse reports child's 

sexually transmitted disease in error. Case in point: 

Perez v. Bay Area Hospital (829 P. Rptr. 2d 700--OR 

[1992]). Regan Rep Nurs Law. Jul 1992;33(2):4. 

Case Reports. 

2536. Tammelleo AD. Legal case briefs for nurses. IL.: 

"medication dosage misadventure" triggers libel suit: 

privileged communication; IL.: spinal meningitis 

misdiagnosed: "patient dumping" charged. Regan Rep 

Nurs Law. Feb 1992;32(9):3. Case Reports. 

2537. Tammelleo AD. Court upholds nurse's refusal to 

float. Case in point: Winkleman v. Beloit Memorial 

Hosp. (483 N.W. 2d 211--WI [1992]). Regan Rep 

Nurs Law. Jul 1992;33(2):2. Legal Cases. 

2538. Tammelleo AD. Nurse denied pay differential for 

unscheduled work. Regan Rep Nurs Law. Jun 

1992;33(1):1. Legal Cases. 

2539. Tammelleo AD. Care allegedly provided without 

proper supervision. Case in point: Raicevich v. Plum 

Creek Medical P.C. 918 F. Supp. 2d 929--CO (1993). 

Regan Rep Nurs Law. Nov 1993;34(6):4. Case 

Reports. 

2540. Tammelleo AD. Failure to follow orders: patient 

arrests--coma results. Case in point: Sullivan v. 

Sumrall By Ritchley 618 So. 2d 1274--MS (1993). 

Regan Rep Nurs Law. Aug 1993;34(3):4. Case 

Reports. 

2541. Tammelleo AD. Legal case briefs for nurses. OK: 

Slip and fall of "medicated" patient: nurse abandons 

patient in shower. NY: Failure to diagnose fetal 

distress: suit for prolongation of distress. Regan Rep 

Nurs Law. May 1993;33(12):3. Case Reports. 

2542. Tammelleo AD. Death after E.R. treatment: 

proximate cause issue. Case in point: Godeaux v. 

Rayne Branch Hosp. (606 So. 2d 948--LA [1992]). 

Regan Rep Nurs Law. Feb 1993;33(9):4. Case 

Reports. 

2543. Tammelleo AD. Legal case briefs for nurses. IA: 

unattended pt. falls in bathroom: "routine 

nonmedicale care" standard applied; OR: nurses state 

"all sponges ... removed": court rejects "captain of 

ship" doctrine. Regan Rep Nurs Law. Nov 

1993;34(6):3. Case Reports. 

2544. Tammelleo AD. Legal case briefs for nurses. NY: 

refusal to stay for additional shift: "abandonment" 

charged--suspension results. AL: substance abuse--

licence revocation: highly qualified and talented 

nurse. Regan Rep Nurs Law. Mar 1993;33(10):3. 

Case Reports. 

2545. Tammelleo AD. Legal case briefs for nurses. GA: 

"non-life-threatening" assessment: four hour delay--

patient leaves E.R. and dies; LA: nurse gives I.M. 

instead of I.V.: pharmacy failure to give directions. 

Regan Rep Nurs Law. May 1994;34(12):3. Case 

Reports. 

2546. Tammelleo AD. Legal case briefs for nurses. NY: 

overworked nurse falls asleep at wheel: auto accident-

-workers' comp. issue; NY: working outside of job 

description: union contract and civil service 

violations. Regan Rep Nurs Law. Jul 1994;35(2):3. 

Legal Cases. 

2547. Tammelleo AD. Failure to follow protocols: hospital 

vulnerability. Case in point: Romo v. Union 

Memorial Hospital, Inc. 878 F. Supp. 837--NC 

(1995). Regan Rep Nurs Law. May 1995;35(12):2. 

Case Reports. 

2548. Tammelleo AD. OH: "LifeFlight" nurse & pilot to 

marry: hospital's nepotism policy mandates transfer. 

Regan Rep Nurs Law. Sep 1995;36(4):3. Legal 

Cases. 

2549. Tammelleo AD. Arbitrator's award of E.R. job to 

existing employee upheld. Regan Rep Nurs Law. Sep 

1995;36(4):2. Legal Cases. 

2550. Tammelleo AD. Nurse risk manager alleges 

"retaliatory transfer". Regan Rep Nurs Law. Sep 

1995;36(4):1. Legal Cases. 

2551. Tammelleo AD. FL: did physician prescribe excess 

dosage?: did nurse err in administering meds.? Regan 

Rep Nurs Law. Dec 1997;38(7):3. Legal Cases. 

2552. Tammelleo AD. Refusal to be party to 'trumped-up' 

charges--retaliatory termination. Case on point: 

Gerard v. Camden Cnty. Health Srvcs. Ctr., N.J. 

Supr.App.Div. 3/6/2002-NJ. Nurs Law Regan Rep. 

Mar 2002;42(10):4. Legal Cases. 

2553. Tan SG, Lim SH, Malathi I. Does routine gowning 

reduce nosocomial infection and mortality rates in a 

neonatal nursery? A Singapore experience. Int J Nurs 

Pract. Nov 1995;1(1):52-58. Not eligible target 

population. 

2554. Tanabe P, Gimbel R, Yarnold PR, Kyriacou DN, 

Adams JG. Reliability and validity of scores on The 

Emergency Severity Index version 3. Acad Emerg 

Med. Jan 2004;11(1):59-65. Not eligible exposure. 

2555. Tanner CA. Living in the midst of a paradigm shift. J 

Nurs Educ. Feb 1995;34(2):51-52. Editorial. 

2556. Tarnow-Mordi WO, Hau C, Warden A, Shearer AJ. 

Hospital mortality in relation to staff workload: a 4-

year study in an adult intensive-care unit. Lancet. Jul 

15 2000;356(9225):185-189. Not eligible target 

population. 

2557. Tate ET, Lund CH, Smart R. A Flex-Ability Nurse 

(FAN) program. Nurs Manage. May 1998;29(5):46. 

Comment. 

2558. Tattam A. The sun the moon & the stars. Aust Nurs J. 

Mar 1995;2(8):21-22. Comment. 
B-76 

2559. Taunton RL, Kleinbeck SVM, Stafford R, et al. 

Patient outcomes: are they linked to registered nurse 

absenteeism, separation, or work load? Journal of 

Nursing Administration Apr 1994;24(4S): Suppl):48-

55. Not relevant; patient outcomes. 

2560. Taxis K, Barber N. Ethnographic study of incidence 

and severity of intravenous drug errors. Bmj. Mar 29 

2003;326(7391):684. Not eligible target population. 

2561. Taxis K, Barber N. Incidence and severity of 

intravenous drug errors in a German hospital. Eur J 

Clin Pharmacol. Jan 2004;59(11):815-817. Not 

eligible target population. 

2562. Taylor C, Gardner B, Heslop L, Lowe E, Habner M, 

Athan D. Identification of factors contributing to 

increased length of stay in two diagnosis related 

groups. Aust Health Rev. 2001;24(4):81-90. Not 

eligible target population. 

2564. Taylor C, Ogle KR, Olivieri D, English R, Dennis M. 

Taking on the student role: how can we improve the 

experience of registered nurses returning to study? 

Aust Crit Care. Sep 1999;12(3):98-102. Not eligible 

target population. 

2565. Taylor CB, Houston-Miller N, Killen JD, DeBusk RF. 

Smoking cessation after acute myocardial infarction: 

effects of a nurse-managed intervention. Ann Intern 

Med. Jul 15 1990;113(2):118-123. Not eligible 

exposure. 

2566. Taylor JA, Brownstein D, Christakis DA, Blackburn 

S, Strandjord TP, Klein EJ, Shafii J. Use of incident 

reports by physicians and nurses to document medical 

errors in pediatric patients. Pediatrics. Sep 

2004;114(3):729-735. Not eligible exposure. 

2567. Taylor M, Keighron K. Healing is who we are ... and 

who are we? Nurs Adm Q. Oct-Dec 2004;28(4):241-

248. Comment. 

2568. Taylor ME. SWAT team: aggressive approach to the 

'90s. Nurs Econ. Nov-Dec 1991;9(6):431-433. Not 

eligible outcomes. 

2569. Taylor NT. The Magnetic pull. Nurs Manage. Jan 

2004;35(1):38-44. Review. 

2570. Teahan B. Implementation of a self-scheduling 

system: a solution to more than just schedules! J Nurs 

Manag. Nov 1998;6(6):361-368. Not eligible target 

population. 

2571. Ter Maat M. An appropriate nursing skill mix: survey 

of acuity systems in rehabilitation hospitals. Rehabil 

Nurs. Jul-Aug 1993;18(4):244-248. No association 

tested. 

2572. Teresi JA, Grant LA, Holmes D, Ory MG. Staffing in 

traditional and special dementia care units. 

Preliminary findings from the National Institute on 

Aging Collaborative Studies. J Gerontol Nurs. Jan 

1998;24(1):49-53. Review. 

2573. Terris J, Leman P, O'Connor N, Wood R. Making an 

IMPACT on emergency department flow: improving 

patient processing assisted by consultant at triage. 

Emerg Med J. Sep 2004;21(5):537-541. Not eligible 

target population. 

2574. Thanasa G, Afthentopoulos IE. The patient with 

diabetic nephropathy in the hospital. Edtna Erca J. 

Oct-Dec 1999;25(4):28-31. Not eligible target 

population. 

2575. Theelen B, Rorive G, Krzesinski JM, Collart F. 

Belgian peer review experience on the Achille's Heel 

in haemodialysis care: vascular access. Edtna Erca J. 

Oct-Dec 2002;28(4):164-166. Not eligible target 

population. 

2576. Thomas EJ, Sexton JB, Helmreich RL. Discrepant 

attitudes about teamwork among critical care nurses 

and physicians. Crit Care Med. Mar 2003;31(3):956-

959. Not eligible exposure. 

2577. Thomas L. Attractive force of nursing. Nurs Stand. 

Mar 8-14 2000;14(25):3. Editorial. 

2578. Thomas LH. A comparison of the verbal interactions 

of qualified nurses and nursing auxiliaries in primary, 

team and functional nursing wards. Int J Nurs Stud. 

Jun 1994;31(3):231-244. Not eligible exposure.

2579. Thomas MB. Study examines working hours and 

feelings of fatigue by reported nurses. Texas Board of 

Nursing Bulletin Oct 2005;36(4):2-3. Not peer 

reviewed. 

2580. Thomas N. Pain control: patient and staff perceptions 

of PCA. Nurs Stand. Mar 31-Apr 6 1993;7(28):37-39. 

Not eligible target population. 

2581. Thompson CR. When your patient doesn't want to 

leave. Am J Nurs. Mar 1998;98(3):40-41. Comment. 

2582. Thompson DG. Critical pathways in the intensive 

care & intermediate care nurseries. MCN Am J 

Matern Child Nurs. Jan-Feb 1994;19(1):29-32. Not 

eligible exposure. 

2583. Thompson DM, Kozak SE, Sheps S. Insulin 

adjustment by a diabetes nurse educator improves 

glucose control in insulin-requiring diabetic patients: 

a randomized trial. Cmaj. Oct 19 1999;161(8):959-

962. Not eligible exposure. 

2584. Thompson DN, Wolf GA, Spear SJ. Driving 

improvement in patient care: lessons from Toyota. J 

Nurs Adm. Nov 2003;33(11):585-595. Not eligible 

target population. 

2585. Thompson J, Irvine T, Grathwohl K, Roth B. Misuse 

of metered-dose inhalers in hospitalized patients. 

Chest. Mar 1994;105(3):715-717. Not eligible 

exposure. 

2586. Thompson K, Melby V, Parahoo K, Ridley T, 

Humphreys WG. Information provided to patients 

undergoing gastroscopy procedures. J Clin Nurs. Nov 

2003;12(6):899-911. Not eligible target population. 

2587. Thompson S. After the volcano. Interview by Lynne 

Wallis. Nurs Stand. Sep 8-14 2004;18(52):20-21. 

Interview. 

2588. Thompson TM. Can medical error self-reporting be 

easily implemented? Counterpoint. Nurs Leadersh 

Forum. Fall 2001;6(1):5-8. Not eligible outcomes. 

2589. Thompson W. Don't scapegoat temporary nurses. 

Nurs Stand. Jan 15 1997;11(17):16. News. 

2590. Thomson D. Outcomes of hospital staffing research 

project: a preliminary report. Concern. Feb 

1999;28(1):9. Comment. 

2591. Thomson PJ. Cancelled operations. A current 

problem in oral and maxillofacial surgery. Br Dent J. 

Oct 19 1991;171(8):244-245. Not eligible exposure. 
B-77 

2592. Thornton L. The Model of Whole-Person Caring: 

creating and sustaining a healing environment. Holist 

Nurs Pract. May-Jun 2005;19(3):106-115. Not 

eligible exposure. 

2593. Thrall TH. Workforce. Tightening ratios. Hosp Health 

Netw. Jan 2004;78(1):24, 26. News.

2594. Thrall TH. Workforce. Creative recruiting in southern 

Ohio. Cincinnati-area hospitals get serious--and a 

little silly--to cut nurse vacancy rate. Hosp Health 

Netw. Apr 2005;79(4):20, 22. News. 

2595. Thurston J, Field S. Should accident and emergency 

nurses request radiographs? Results of a multicentre 

evaluation. J Accid Emerg Med. Mar 1996;13(2):86-

89. Not eligible exposure. 

2596. Thurtle V. Why do nurses enter community and 

public health practice? Community Pract. Apr 

2005;78(4):140-145. Not eligible target population. 

2597. Thyer GL. Dare to be different: transformational 

leadership may hold the key to reducing the nursing 

shortage. J Nurs Manag. Mar 2003;11(2):73-79. Not 

eligible target population. 

2598. Tibby SM, Correa-West J, Durward A, Ferguson L, 

Murdoch IA. Adverse events in a paediatric intensive 

care unit: relationship to workload, skill mix and staff 

supervision. Intensive Care Med. Jun 

2004;30(6):1160-1166. Not eligible target population. 

2599. Tieman J. Registered nurses key to good patient 

outcomes, study finds. But national nursing groups 

disagree over ratio laws and how best to recruit and 

retain quality nurses. Mod Healthc. Jun 3 

2002;32(22):10-11. News. 

2600. Tieman J. Nursing the nurse shortage. As feds 

collaborate, states and localities act on own. Mod 

Healthc. May 20 2002;32(20):20-21. News.

2601. Tieman J. Double standards. Amid push for nurse 

ratio laws, the nation's hospitals also face new 

JCAHO requirements for measuring staffing 

effectiveness. Mod Healthc. Apr 8 2002;32(14):30-

32. Review.

2602. Tien SF. Nurses' knowledge of traditional Chinese 

postpartum customs. West J Nurs Res. Nov 

2004;26(7):722-732. Not eligible target population. 

2603. Tierney AJ, Taylor J. Research in practice: an 

'experiment' in researcher-practitioner collaboration. J 

Adv Nurs. May 1991;16(5):506-510. Not eligible 

target population. 

2604. Tierney MJ, Lavelle M. An investigation into 

modification of personality hardiness in staff nurses. J 

Nurs Staff Dev. Jul-Aug 1997;13(4):212-217. Not 

eligible exposure. 

2605. Tigert JA, Laschinger HK. Critical care nurses' 

perceptions of workplace empowerment, magnet 

hospital traits and mental health. Dynamics. Winter 

2004;15(4):19-23. Not eligible exposure. 

2606. Tillman HJ, Salyer J, Corley MC, Mark BA. 

Environmental turbulence: staff nurse perspectives. J 

Nurs Adm. Nov 1997;27(11):15-22. No association 

tested. 

2607. Timmins F, Kaliszer M. Information needs of 

myocardial infarction patients. Eur J Cardiovasc 

Nurs. Apr 2003;2(1):57-65. Not eligible target 

population. 

2608. Timmons S, Tanner J. Operating theatre nurses: 

emotional labour and the hostess role. Int J Nurs 

Pract. Apr 2005;11(2):85-91. Not eligible target 

population. 

2609. Tippett J. Nurses' acquisition and retention of 

knowledge after trauma training. Accid Emerg Nurs. 

Jan 2004;12(1):39-46. Not eligible target population. 

2610. Titone NJ, Cross R, Sileo M, Martin G. Taking 

family-centered care to a higher level on the heart and 

kidney unit. Pediatr Nurs. Nov-Dec 2004;30(6):495-

497. Not eligible exposure. 

2611. Todd C, Robinson G, Reid N. 12-hour shifts: job 

satisfaction of nurses. J Nurs Manag. Sep 

1993;1(5):215-220. Not eligible target population. 

2612. Todd V, Van Rosendaal G, Duregon K, Verhoef M. 

Percutaneous endoscopic gastrostomy (PEG): the role 

and perspective of nurses. J Clin Nurs. Feb 

2005;14(2):187-194. Not eligible exposure. 

2613. Tokarski C. Government eases up on foreign nurses. 

Mod Healthc. Dec 10 1990;20(49):2. News.

2614. Tomlinson PS, Kirschbaum M, Tomczyk B, Peterson 

J. The relationship of child acuity, maternal 

responses, nurse attitudes and contextual factors in 

the bone marrow transplant unit. Am J Crit Care. May 

1993;2(3):246-252. Not eligible outcomes. 

2615. Tomlinson PS, Swiggum P, Harbaugh BL. 

Identification of nurse-family intervention sites to 

decrease health-related family boundary ambiguity in 

PICU. Issues Compr Pediatr Nurs. Jan-Mar 

1999;22(1):27-47. Not eligible exposure. 

2616. Tonges MC. Job design for nurse case managers. 

Intended and unintended effects on satisfaction and 

well-being. Nurs Case Manag. Jan-Feb 1998;3(1):11-

23; quiz 24-15. Not eligible exposure. 

2617. Tonges MC, Baloga-Altieri B, Atzori M. Amplifying 

nursing's voice through a staff-management 

partnership. J Nurs Adm. Mar 2004;34(3):134-139. 

Review. 

2618. Tonuma M, Winbolt M. From rituals to reason: 

creating an environment that allows nurses to nurse. 

Int J Nurs Pract. Aug 2000;6(4):214-218. Not eligible 

target population. 

2619. Torkelson DJ, Dobal MT. Constant observation in 

medical-surgical settings: a multihospital study. Nurs 

Econ. May-Jun 1999;17(3):149-155. Not eligible 

exposure. 

2620. Tornabeni J. Care 2000--a patient-focused care 

model. Calif Hosp. Jul-Aug 1994;8(4):12-13. 

Comment. 

2621. Tourangeau AE, White P, Scott J, McAllister M, 

Giles L. Evaluation of a partnership model of care 

delivery involving registered nurses and unlicensed 

assistive personnel. Can J Nurs Leadersh. May-Jun 

1999;12(2):4-20. Not eligible exposure.

2622. Toyry E, Herve R, Mutka R, Savolainen P, Seppanen 

M. Ethics in health care management: developing an 

instrument to assess humane caring. Nurs Ethics. May 

1998;5(3):228-235. Not eligible target population. 

2623. Trafford A. The nursing shortage--a Washington Post 

columnist's perspective. Interview by Iris C. Frank. J 

Emerg Nurs. Aug 2001;27(4):391-393. Interview.
B-78 

2624. Trammell TR, Fisher D, Brueckmann FR, Haines N. 

Closed-wound drainage systems. The Solcotrans Plus 

versus the Stryker-CBC ConstaVAC. Orthop Rev. 

Jun 1991;20(6):536-542. Not eligible exposure. 

2625. Tranmer JE, Lochhaus-Gerlach J, Lam M. The effect 

of staff nurse participation in a clinical nursing 

research project on attitude towards, access to, 

support of and use of research in the acute care 

setting. Can J Nurs Leadersh. Jan-Feb 2002;15(1):18-

26. Not eligible exposure. 

2626. Travers D. Triage: how long does it take? how long 

should it take? J Emerg Nurs. Jun 1999;25(3):238-

240. Not eligible exposure. 

2627. Travis M. Cash in the bank. Nurs Times. Feb 12-18 

1997;93(7):27. Not eligible target population. 

2628. Treloar AJ, Macdonald AJ. Recognition of cognitive 

impairment by day and night nursing staff among 

acute geriatric patients. J R Soc Med. Apr 

1995;88(4):196-198. Not eligible target population. 

2629. Trossman S. Fighting the clock: nurses take on 

mandatory overtime. Am Nurse. May-Jun 

1998;30(3):1, 12. Comment. 

2630. Trossman S. ANA, MNA support Dana-Farber nurses 

facing disciplinary action. Am Nurse. Mar-Apr 

1999;31(2):1, 10. Comment. 

2631. Trossman S. Working 'round the clock. Am Nurse. 

Sep-Oct 1999;31(5):1-2. Comment. 

2632. Trossman S. Staffing smart: a difficult proposition. 

Am Nurse. Jan-Feb 1999;31(1):1-2. News. 

2633. Trossman S. The global reach of the nursing shortage. 

Am J Nurs. Mar 2002;102(3):85, 87, 89. Comment. 

2634. Trossman S. Nurses' Rx for medication errors. Am 

Nurse. May-Jun 2003;35(3):1-2, 12. Comment. 

2635. Trossman S. Have RN, will travel? Nurs Manage. Jul 

2003;34 Suppl 4:15-16. Comment. 

2636. Trossman S. Increased hours, more errors. Am Nurse. 

Jul-Aug 2004;36(4):1, 3-4. Comment. 

2637. Trossman S. Move over eBay? A potential trend 

involving bidding for shifts online. Am Nurse. MayJun 2004;36(3):1, 8, 12. Comment. 

2638. Trundle CM, Farrington M, Anderson L, Redpath 

CK. GRASPing infection: a workload measurement 

tool for infection control nurses. J Hosp Infect. Nov 

2001;49(3):215-221. Not eligible target population. 

2639. Tsai SL, Tsai WW, Chai SK, Sung WH, Doong JL, 

Fung CP. Evaluation of computer-assisted multimedia 

instruction in intravenous injection. Int J Nurs Stud. 

Feb 2004;41(2):191-198. Not eligible target 

population. 

2640. Tschannen D. The effect of individual characteristics 

on perceptions of collaboration in the work 

environment. Medsurg Nurs. Oct 2004;13(5):312-

318. Not eligible exposure. 

2641. Tselebis A, Moulou A, Ilias I. Burnout versus 

depression and sense of coherence: study of Greek 

nursing staff. Nurs Health Sci. Jun 2001;3(2):69-71. 

Not eligible target population. 

2642. Tselikis P. It's a hard knocks life for providers ... and 

getting harder! State Health Care Am. 2001:40-43. 

Review. 

2643. Tsuru S, Shindob S, Takatanic Y, Seod A. A 

conception of a support system for optimising the 

organisation of nursing staff from the viewpoint of 

the nursing care needs structure. Stud Health Technol 

Inform. 1997;46:275-278. Not eligible target 

population. 

2644. Tucker D, Dirico L. Managing costly Medicare 

patients in the hospital. Geriatr Nurs. Sep-Oct 

2003;24(5):294-297. No association tested.

2645. Tucker J. Patient volume, staffing, and workload in 

relation to risk-adjusted outcomes in a random 

stratified sample of UK neonatal intensive care units: 

a prospective evaluation. Lancet. Jan 12 

2002;359(9301):99-107. Not eligible target 

population. 

2646. Turk M, Davas A, Ciceklioglu M, Sacaklioglu F, 

Mercan T. Knowledge, attitude and safe behaviour of 

nurses handling cytotoxic anticancer drugs in Ege 

University Hospital. Asian Pac J Cancer Prev. AprJun 2004;5(2):164-168. Not eligible target 

population. 

2647. Turley S. Development of the 'Euro Rota' in A & E. 

Accid Emerg Nurs. Oct 1997;5(4):178-180. Not 

eligible target population. 

2648. Turnbull GB. Office of Inspector General (OIG) 

issues draft compliance program for pharmaceutical 

manufacturers. Ostomy Wound Manage. Dec 

2002;48(12):12-13. Comment. 

2649. Turner G. Parents' experiences of ambulatory care. 

Paediatr Nurs. Oct 1998;10(8):12-13, 16. Not eligible 

target population. 

2650. Turner JT, Lee V, Fletcher K, Hudson K, Barton D. 

Measuring quality of care with an inpatient elderly 

population. The geriatric resource nurse model. J 

Gerontol Nurs. Mar 2001;27(3):8-18. Not eligible 

exposure. 

2651. Turner M. Shiftwork strategies. Can Nurse. Dec 

1995;91(11):41-42. Not eligible exposure. 

2652. Turnock C, Gibson V. Validity in action research: a 

discussion on theoretical and practice issues 

encountered whilst using observation to collect data. J 

Adv Nurs. Nov 2001;36(3):471-477. Not eligible 

target population. 

2653. Turrill S. Interpreting family-centred care within 

neonatal nursing. Paediatr Nurs. May 1999;11(4):22-

24. Not eligible target population. 

2654 Turrittin J, Hagey R, Guruge S, et al. The experiences 

of professional nurses who have migrated to Canada: 

cosmopolitan citizenship or democratic racism? 

International journal of nursing studies Aug 

2002;39(6):655-67. Not relevant. 

2655. Tuttas CA. Decreasing nurse staffing costs in a 

hospital setting: development and support of core 

staff stability. J Nurs Care Qual. Jul-Sep 

2003;18(3):226-240. Review. 

2656. Tuttle DM. A "transfer fair" approach to staffing. 

Nurs Manage. Dec 1992;23(12):72-74. Comment. 

2657. Tutuarima JA, de Haan RJ, Limburg M. Number of 

nursing staff and falls: a case-control study on falls by 

stroke patients in acute-care settings. J Adv Nurs. Jul 

1993;18(7):1101-1105. Not eligible target population. 
B-79 

2658. Tyson PD, Pongruengphant R. Five-year follow-up 

study of stress among nurses in public and private 

hospitals in Thailand. Int J Nurs Stud. Mar 

2004;41(3):247-254. Not eligible target population. 

2659. Tzeng HM. Demand and supply for nursing 

competencies in Taiwan's hospital industry. Nurs 

Econ. May-Jun 2003;21(3):130-139. Not eligible 

target population. 

2660. Tzeng HM. Nurses' self-assessment of their nursing 

competencies, job demands and job performance in 

the Taiwan hospital system. Int J Nurs Stud. Jul 

2004;41(5):487-496. Not eligible target population. 

2661. Tzeng HM, Ketefian S. Demand for nursing 

competencies: an exploratory study in Taiwan's 

hospital system. J Clin Nurs. Jul 2003;12(4):509-518. 

Not eligible target population.

2662. Tzeng HM, Ketefian S, Redman RW. Relationship of 

nurses' assessment of organizational culture, job 

satisfaction, and patient satisfaction with nursing care. 

Int J Nurs Stud. Jan 2002;39(1):79-84. Not eligible 

target population. 

2663. Uchal M, Tjugum J, Martinsen E, Qiu X, 

Bergamaschi R. The impact of sleep deprivation on 

product quality and procedure effectiveness in a 

laparoscopic physical simulator: a randomized 

controlled trial. Am J Surg. Jun 2005;189(6):753-757. 

Not eligible exposure. 

2664. Ugrovics A, Wright J. 12-hour shifts: does fatigue 

undermine ICU nursing judgments? Nursing 

management Jan 1990;21(1): Crit Care Manage 

Ed):64A, F-G. Inadequate data presentation. 

2665. Uitterhoeve R, Duijnhouwer E, Ambaum B, van 

Achterberg T. Turning toward the psychosocial 

domain of oncology nursing: a main problem analysis 

in the Netherlands. Cancer Nurs. Feb 2003;26(1):18-

27. Not eligible target population.

2666. Ullmer D. Legislative protection against mandatory 

overtime. Gastroenterol Nurs. Jul-Aug 

2002;25(4):165-166. Comment. 

2667. Ulrich BT, Buerhaus PI, Donelan K, Norman L, 

Dittus R. How RNs view the work environment: 

results of a national survey of registered nurses. J 

Nurs Adm. Sep 2005;35(9):389-396. Not eligible 

exposure. 

2668. Umansky PW. Management during the off-shifts. 

Nurs Spectr (Wash D C). Sep 9 1996;6(19):6-7. 

Comment. 

2669. Unruh L. Trends in adverse events in hospitalized 

patients. J Healthc Qual. Sep-Oct 2002;24(5):4-10; 

quiz 10, 18. Not eligible exposure. 

2670. Unruh LY, Fottler. Projections and trends in RN 

supply: what do they tell us about the nursing 

shortage? Policy, Politics, & Nursing Practice Aug 

2005;6(3):171-82. Not relevant. 

2671. Upenieks VV. Assessing differences in job 

satisfaction of nurses in magnet and nonmagnet 

hospitals. J Nurs Adm. Nov 2002;32(11):564-576. 

Not eligible exposure. 

2672. Upenieks VV. What constitutes effective leadership? 

Perceptions of magnet and nonmagnet nurse leaders. J 

Nurs Adm. Sep 2003;33(9):456-467. Not eligible 

exposure. 

2673. Urden LD. Development of a nurse executive 

decision support database. A model for outcomes 

evaluation. J Nurs Adm. Oct 1996;26(10):15-21. No 

association tested. 

2674. Vail JD, Morton DA, Rieder KA. Workload 

management system highlights staffing needs. Nurs 

Health Care. May 1987;8(5):289-293. Not eligible 

year. 

2675. Vale MJ, Jelinek MV, Best JD, Dart AM, Grigg LE, 

Hare DL, Ho BP, Newman RW, McNeil JJ. Coaching 

patients On Achieving Cardiovascular Health 

(COACH): a multicenter randomized trial in patients 

with coronary heart disease. Arch Intern Med. Dec 8-

22 2003;163(22):2775-2783. Not eligible target 

population. 

2676. Valouxis C, Housos E. Hybrid optimization 

techniques for the workshift and rest assignment of 

nursing personnel. Artif Intell Med. Oct 

2000;20(2):155-175. Not eligible target population.

2677. van den Bemt PM, Egberts AC, Lenderink AW, 

Verzijl JM, Simons KA, van der Pol WS, Leufkens 

HG. Adverse drug events in hospitalized patients. A 

comparison of doctors, nurses and patients as sources 

of reports. Eur J Clin Pharmacol. Apr 

1999;55(2):155-158. Not eligible target population. 

2678. Van der Geest S, Sarkodie S. The fake patient: a 

research experiment in a Ghanaian hospital. Soc Sci 

Med. Nov 1998;47(9):1373-1381. Not eligible target 

population. 

2679. van der Voort PH, van der Hulst RW, Zandstra DF, 

van der Ende A, Kesecioglu J, Geraedts AA, Tytgat 

GN. Gut decontamination of critically ill patients 

reduces Helicobacter pylori acquisition by intensive 

care nurses. J Hosp Infect. Jan 2001;47(1):41-45. Not 

eligible exposure. 

2680. Van Der Zwet WC, Parlevliet GA, Savelkoul PH, 

Stoof J, Kaiser AM, Van Furth AM, VandenbrouckeGrauls CM. Outbreak of Bacillus cereus infections in 

a neonatal intensive care unit traced to balloons used 

in manual ventilation. J Clin Microbiol. Nov 

2000;38(11):4131-4136. Not eligible target 

population. 

2681. van Servellen G, Leake B. Emotional exhaustion and 

distress among nurses: how important are AIDS-care 

specific factors? Journal of the Association of Nurses 

in AIDS Care Mar-Apr 1994;5(2):11-9. Not relevant. 

2682. van Servellen G, Schultz MA. Demystifying the 

influence of hospital characteristics on inpatient 

mortality rates. J Nurs Adm. Apr 1999;29(4):39-47. 

Review. 

2683. Van Slyck A. A systems approach to the management 

of nursing services. Part III: Staffing system. Nurs 

Manage. May 1991;22(5):30, 32, 34. Comment.

2684. van Wissen K, Woodman K. Nurses' attitudes and 

concerns to HIV/AIDS: a focus group approach. J 

Adv Nurs. Dec 1994;20(6):1141-1147. Not eligible 

target population. 

2685. Vanderschueren S, Van Renterghem L, Plum J, 

Verhofstede C, Mak R, Vincke J. Hepatitis C among 

risk groups for HIV and hepatitis B. Int J STD AIDS. 

May-Jun 1991;2(3):185-187. Not eligible target 

population. 
B-80 

2686. Vanderslott J. A study of incidents of violence 

towards staff by patients in an NHS Trust hospital. J 

Psychiatr Ment Health Nurs. Aug 1998;5(4):291-298. 

Not eligible target population. 

2687. Vaughan CA, Reeds LB, Percifull D. A strategic 

nursing assistance program--SNAP. Nurs Econ. NovDec 1990;8(6):426-427. No association tested. 

2688. Vejlgaard T, Addington-Hall JM. Attitudes of Danish 

doctors and nurses to palliative and terminal care. 

Palliat Med. Mar 2005;19(2):119-127. Not eligible 

target population. 

2689. Velianoff GD. Establishing a 10-hour schedule. Nurs 

Manage. Sep 1991;22(9):36-38. No association 

tested. 

2690. Verghese C, Prior-Willeard PF, Baskett PJ. 

Immediate management of the airway during 

cardiopulmonary resuscitation in a hospital without a 

resident anaesthesiologist. Eur J Emerg Med. Sep 

1994;1(3):123-125. Not eligible target population.

2691. Veyckemans F. Patient-controlled analgesia in 

children. Acta Anaesthesiol Belg. 1992;43(1):57-61. 

Not eligible target population. 

2692. Vicca AF. Nursing staff workload as a determinant of 

methicillin-resistant Staphylococcus aureus spread in 

an adult intensive therapy unit. J Hosp Infect. Oct 

1999;43(2):109-113. Not eligible target population. 

2693. Vieira AM. Caught short-staffed. Am J Nurs. Jun 

1996;96(6):63. Comment. 

2694. Viney C, Poxon I, Jordan C, Winter B. Does the 

APACHE II scoring system equate with the 

Nottingham Patient Dependency System? Can these 

systems be used to determine nursing workload and 

skill mix? Nurs Crit Care. Mar-Apr 1997;2(2):59, 62-

53. Not eligible target population.

2695. Vinh DT, Johnson CW, Phelps CL. Rigorously 

assessing whether the data backs the back school. 

AMIA Annu Symp Proc. 2003:1041. Comment. 

2696. Violante FS, Fiori M, Fiorentini C, Risi A, Garagnani 

G, Bonfiglioli R, Mattioli S. Associations of 

psychosocial and individual factors with three 

different categories of back disorder among nursing 

staff. J Occup Health. Mar 2004;46(2):100-108. Not 

eligible target population. 

2697. Visina CE, Chen J, Gerthoffer TD, Biggs R, Ting D. 

Community hospital physician and nurse attitudes 

about pain management. J Pain Palliat Care 

Pharmacother. 2003;17(2):51-62. Not eligible 

exposure. 

2698. Vitacca M, Clini E, Porta R, Ambrosino N. 

Preliminary results on nursing workload in a 

dedicated weaning center. Intensive Care Med. Jun 

2000;26(6):796-799. Not eligible target population. 

2699. von Essen L, Sjoden PO. The importance of nurse 

caring behaviors as perceived by Swedish hospital 

patients and nursing staff. Int J Nurs Stud. 

1991;28(3):267-281. Not eligible target population. 

2700. von Essen L, Sjoden PO. Patient and staff perceptions 

of caring: review and replication. J Adv Nurs. Nov 

1991;16(11):1363-1374. Not eligible target 

population. 

2701. von Essen L, Sjoden PO. Perceived importance of 

caring behaviors to Swedish psychiatric inpatients 

and staff, with comparisons to somatically-ill 

samples. Res Nurs Health. Aug 1993;16(4):293-303. 

Not eligible target population. 

2702. von Essen L, Sjoden PO. Perceived occurrence and 

importance of caring behaviours among patients and 

staff in psychiatric, medical and surgical care. J Adv 

Nurs. Feb 1995;21(2):266-276. Not eligible target 

population. 

2703. von Essen L, Sjoden PO. The importance of nurse 

caring behaviors as perceived by Swedish hospital 

patients and nursing staff. International Journal of 

Nursing Studies (1991), 28, 267-281. Int J Nurs Stud. 

Jul 2003;40(5):487-497; discussion 499-502. Not 

eligible target population. 

2703. Vonfrolio LG. Staffing ratios are the answer. Rn. Jun 

2004;67(6):80. Comment. 

2704. Vore AL. Enhancing verbal communication skills and 

promoting effective socialization of newly hired 

Spanish-speaking registered nurses. J Nurs Staff Dev. 

Nov-Dec 1991;7(6):286-289. Not eligible outcomes. 

2705. Vyas A, Pickering CA, Oldham LA, Francis HC, 

Fletcher AM, Merrett T, Niven RM. Survey of 

symptoms, respiratory function, and immunology and 

their relation to glutaraldehyde and other occupational 

exposures among endoscopy nursing staff. Occup 

Environ Med. Nov 2000;57(11):752-759. Not eligible 

target population. 

2706. Waid EO. Job sharing meets nurses' needs. Ohio 

Nurses Rev. Jul 1996;71(6):10-11. Comment. 

2707. Wainwright TA. The perceived function of health 

care assistants in intensive care: nurses views. 

Intensive Crit Care Nurs. Jun 2002;18(3):171-180. 

Not eligible target population.

2708. Wakefield BJ, Blegen MA, Uden-Holman T, Vaughn 

T, Chrischilles E, Wakefield DS. Organizational 

culture, continuous quality improvement, and 

medication administration error reporting. Am J Med 

Qual. Jul-Aug 2001;16(4):128-134. Not eligible 

outcomes (medication error reporting perception). 

2709. Wakefield BJ, Wakefield DS, Uden-Holman T, 

Blegen MA. Nurses' perceptions of why medication 

administration errors occur. Medsurg Nurs. Feb 

1998;7(1):39-44. Not eligible exposure. 

2710. Wakefield DS, Wakefield BJ, Borders T, UdenHolman T, Blegen M, Vaughn T. Understanding and 

comparing differences in reported medication 

administration error rates. Am J Med Qual. Mar-Apr 

1999;14(2):73-80. Not eligible exposure.

2711. Wakefield DS, Wakefield BJ, Uden-Holman T, 

Blegen MA. Perceived barriers in reporting 

medication administration errors. Best Pract 

Benchmarking Healthc. Jul-Aug 1996;1(4):191-197. 

Not eligible exposure. 

2712. Wakefield DS, Wakefield BJ, Uden-Holman T, 

Borders T, Blegen M, Vaughn T. Understanding why 

medication administration errors may not be reported. 

Am J Med Qual. Mar-Apr 1999;14(2):81-88. Not 

eligible exposure. 
B-81 

2713. Walczak JR, McGuire DB, Haisfield ME, Beezley A. 

A survey of research-related activities and perceived 

barriers to research utilization among professional 

oncology nurses. Oncol Nurs Forum. May 

1994;21(4):710-715. Not eligible outcomes. 

2714. Waldenstrom U. Continuity of carer and satisfaction. 

Midwifery. Dec 1998;14(4):207-213. Not eligible 

target population. 

2715. Walder B, Francioli D, Meyer JJ, Lancon M, Romand 

JA. Effects of guidelines implementation in a surgical 

intensive care unit to control nighttime light and noise 

levels. Crit Care Med. Jul 2000;28(7):2242-2247. Not 

eligible target population. 

2716. Walker AC. Safety and comfort work of nurses 

glimpsed through patient narratives. Int J Nurs Pract. 

Feb 2002;8(1):42-48. Not eligible target population. 

2717. Walker CA. STAR Day: one hospital's solution to 

educational challenges. J Nurses Staff Dev. Nov-Dec 

2002;18(6):293-296. Not eligible exposure. 

2718. Walker DD, Jones SL, Yamauchi SS, Lima C, Archer 

S, Mathews BP, Harris M, Kamikawa C, Irvine N, 

Lanier J, et al. The Queen's Medical Center Honolulu, 

Hawaii. Nurs Adm Q. Fall 1994;19(1):33-65. Not 

eligible target population. 

2719. Walker EK. Staffing accommodations to hospital unit 

admissions. Nursing Economics Sep-Oct 

1990;8(5):314-8. Not relevant. 

2720. Walker J, Brooksby A, McInerny J, Taylor A. Patient 

perceptions of hospital care: building confidence, 

faith and trust. J Nurs Manag. Jul 1998;6(4):193-200. 

Not eligible target population. 

2721. Walker JK. Nurse managers making a difference: 

creating a healing place. Semin Nurse Manag. Dec 

1994;2(4):234-238. Review. 

2722. Walker R, Adam J. Changing time in an operating 

suite. Int J Nurs Stud. Feb 2001;38(1):25-35. Not 

eligible target population. 

2723. Walker SB, Lowe MJ. Nurses' views on reporting 

medication incidents. Int J Nurs Pract. Jun 

1998;4(2):97-102. Not eligible target population. 

2724. Wallace SA, Gullan RW, Byrne PO, Bennett J, PerezAvila CA. Use of a pro forma for head injuries in the 

accident and emergency department--the way 

forward. J Accid Emerg Med. Mar 1994;11(1):33-42. 

Not eligible target population. 

2725. Walrath JM, Tomallo-Bowman R, Maguire JM. 

Emergency department: improving patient 

satisfaction. Nurs Econ. Mar-Apr 2004;22(2):71-74, 

55. Not eligible exposure.

2726. Walsh B, Steiner A, Warr J, Sheron L, Pickering R. 

Nurse-led inpatient care: opening the 'black box'. Int J 

Nurs Stud. Mar 2003;40(3):307-319. Not eligible 

target population. 

2727. Walsh C. A measurable framework for improving 

quality. Prof Nurse. Nov 1999;15(2):80-84. Not 

eligible target population. 

2728. Walters AJ. A hermeneutic study of the concept of 

'focusing' in critical care nursing practice. Nurs Inq. 

Nov 1994;1(1):23-30. No association tested. 

2729. Walters JA. Nurses' perceptions of reportable 

medication errors and factors that contribute to their 

occurrence. Appl Nurs Res. May 1992;5(2):86-88. 

Not eligible outcomes. 

2730. Walther SM, Jonasson U, Karlsson S, Nordlund P, 

Johansson A, Malstam J. Multicentre study of validity 

and interrater reliability of the modified Nursing Care 

Recording System (NCR11) for assessment of 

workload in the ICU. Acta Anaesthesiol Scand. Jul 

2004;48(6):690-696. Not eligible target population.

2731. Wang CE. Knowing and approaching hope as human 

experience: implications for the medical-surgical 

nurse. Medsurg Nurs. Aug 2000;9(4):189-192. Case 

reports. 

2732. Ward D. Infection control: reducing the psychological 

effects of isolation. Br J Nurs. Feb 10-23 

2000;9(3):162-170. Not eligible exposure. 

2733. Ward D, Berkowitz B. Arching the flood: how to 

bridge the gap between nursing schools and hospitals. 

Health Aff (Millwood). Sep-Oct 2002;21(5):42-52. 

Review. 

2734. Ward KG. A TEAM approach to NICU care. Rn. Feb 

1999;62(2):47-49. Comment. 

2735. Warminger P. Staff and patient communications--

trends and technologies. Health Estate J. Jul 

1990;44(6):2-8. Not eligible target population. 

2736. Warren DK, Zack JE, Cox MJ, Cohen MM, Fraser 

VJ. An educational intervention to prevent catheterassociated bloodstream infections in a nonteaching, 

community medical center. Crit Care Med. Jul 

2003;31(7):1959-1963. Not eligible exposure. 

2737. Warren IB, Rozell BR. Supplemental staffing. Nurse 

manager views of costs, benefits, and quality of care. 

J Nurs Adm. Jun 1995;25(6):51-57. Not eligible 

outcomes. 

2738. Washburn M. Fatigue and critical thinking on eightand twelve-hour shifts. Nursing management Sep 

1991;22(9): Crit Care Manage Ed):80A- F-H. 

Inadequate data presentation. 

2739. Washington GT, Macnee CL. Evaluation of 

outcomes: the effects of continuous lateral rotational 

therapy. J Nurs Care Qual. Jul-Sep 2005;20(3):273-

282. Not eligible exposure. 

2740. Watanakunakorn C, Wang C, Hazy J. An 

observational study of hand washing and infection 

control practices by healthcare workers. Infection 

Control and Hospital Epidemiology Nov 

1998;19(11):858-60. Not relevant. 

2741. Waters A. A matter of life and death. Nurs Stand. Jun 

30-Jul 6 1999;13(41):12-13. Comment. 

2742. Waters A. It's all in the mix. Nurs Stand. Feb 19-25 

2003;17(23):14-17. Not eligible target population. 

2743. Watson LD, Quinn DA. Stages of stroke: a model for 

stroke rehabilitation. Br J Nurs. Jun 25-Jul 8 

1998;7(12):suppl 8p. Not eligible exposure. 

2744. Weaver J. Many American nurses are having trouble 

finding jobs. Nurs Spectr (Wash D C). Jun 17 

1996;6(13):5. News. 
B-82 

2745. Webb AA, Bower DA, Gill S. Satisfaction with 

nursing care: a comparison of patients with 

HIV/AIDS, non-HIV/AIDS infectious diseases, and 

medical diagnoses. J Assoc Nurses AIDS Care. MarApr 1997;8(2):39-46. Not eligible exposure. 

2746. Webb D, Tour C, Hurt R, van Kammen DP. 

Recognizing excellence. Giving your AWE. J Nurs 

Adm. Sep 1992;22(9):54-56. Not eligible exposure. 

2747. Webb SS, Price SA, Coeling HE. Valuing 

authority/responsibility relationships. The essence of 

professional practice. J Nurs Adm. Feb 

1996;26(2):28-33. Not eligible exposure. 

2748. Webber S. Cluster staffing: cooperation, competence, 

and caring. Todays OR Nurse. Mar-Apr 

1993;15(2):5-7. No association tested. 

2749. Weber DO. Harrison Memorial in Bremerton, 

Washington records satisfaction all around from 2-

year-old "private practice" unit nursing experiment. 

Strateg Healthc Excell. Dec 1992;5(12):1-10. Not 

eligible exposure. 

2750. Weber S, Herwaldt LA, McNutt LA, Rhomberg P, 

Vaudaux P, Pfaller MA, Perl TM. An outbreak of 

Staphylococcus aureus in a pediatric cardiothoracic 

surgery unit. Infect Control Hosp Epidemiol. Feb 

2002;23(2):77-81. Not eligible exposure. 

2751. Webster DC, Vaughn K, Martinez R. Introducing 

solution-focused approaches to staff in inpatient 

psychiatric settings. Arch Psychiatr Nurs. Aug 

1994;8(4):254-261. Not eligible exposure.

2752. Webster J, Cowart P. An innovative professional 

nursing practice model. Nurs Adm Q. Spring 

1999;23(3):11-16. Comment. 

2753. Wedge C, Gosney M. Pressure-relieving equipment: 

promoting its correct use amongst nurses via differing 

modes of educational delivery. J Clin Nurs. Apr 

2005;14(4):473-478. Not eligible target population. 

2754. Weetch RM. Patient satisfaction with information 

received after a diagnosis of angina. Prof Nurse. Nov 

2003;19(3):150-153. Not eligible exposure. 

2755. Wehby D, Brenner PS. Perceived learning needs of 

patients with heart failure. Heart Lung. Jan-Feb 

1999;28(1):31-40. Not eligible exposure. 

2756. Weinberg AD, Lesene AJ, Richards CL, et al. Quality 

care indicators and staffing levels in a nursing facility 

subacute unit. Journal of the American Medical 

Directors Association Jan-Feb 2002;3(1):1-4. Not 

relevant. 

2757. Weinstein SM, Antonova S, Goryunova M. 

Enhancing nurse-physician collaboration: a staffing 

innovation. J Nurs Adm. Apr 2003;33(4):193-195. 

Review. 

2758. Weir R, Stewart L, Browne G, Roberts J, Gafni A, 

Easton S, Seymour L. The efficacy and effectiveness 

of process consultation in improving staff morale and 

absenteeism. Med Care. Apr 1997;35(4):334-353. Not 

eligible exposure. 

2759. Weisman CS, Gordon DL, Cassard SD, Bergner M, 

Wong R. The effects of unit self-management on 

hospital nurses' work process, work satisfaction, and 

retention. Med Care. May 1993;31(5):381-393. Not 

eligible outcomes. 

2760. Weiss JP. Using the nurse practitioner in the acute 

care setting. Aspens Advis Nurse Exec. Aug 

1994;9(11):4-6. Comment. 

2761. Welford M. Night shifts: light-headed night staff. 

Nurs Stand. Aug 5-11 1992;6(46):44-45. Not eligible 

exposure. 

2762. Wells B. Taking charge of your practice. Nurs BC. 

Jan-Feb 1998;30(1):16-17. Comment. 

2763. Wells N, Johnson R, Salyer S. Interdisciplinary 

collaboration. Clin Nurse Spec. Jul 1998;12(4):161-

168. Not eligible exposure. 

2764. Weltman AC, Short LJ, Mendelson MH, Lilienfeld 

DE, Rodriguez M. Disposal-related sharps injuries at 

a New York City Teaching Hospital. Infect Control 

Hosp Epidemiol. May 1995;16(5):268-274. Not 

eligible exposure. 

2765. Wenzel K, Miller M, Falco J. Differentiated practice 

in Colorado--what's happening? Colo Nurse. Dec 

1996;96(4):17-18. Comment. 

2766. Werab B, Alexander C, Brunt B, Wester F. The use of 

medication modules for medication administration 

problems. J Nurs Staff Dev. Jan-Feb 1994;10(1):16-

21. Not eligible exposure. 

2767. Wermers MA, Dagnillo R, Glenn R, Macfarlane R, St 

Clair V, Scott D. Planning and assessing a crosstraining initiative with multi-skilled employees. Jt 

Comm J Qual Improv. Jun 1996;22(6):412-426. Not 

eligible exposure. 

2768. West JC. Agency not liable for actions of nurse 

supplied by agency. Hansen v. Caring Professionals, 

Inc. J Healthc Risk Manag. Fall 1997;17(4):51-53. 

Comment. 

2769. Westera D. A profile of part-time faculty in Canadian 

university nursing programmes. Canadian Journal of 

Nursing Research Winter 1992;24(4):47-59. Not 

relevant. 

2770. Western H. New, but hardly improved. Nurs Times. 

Oct 13-19 1999;95(41):49. Not eligible target 

population. 

2771. Westfall NL, Burrow CM. Are daily bed linen 

changes necessary? Nurs Manage. Nov 

1997;28(11):90-92. Comment. 

2772. Wetzel K, Soloshy DE, Gallagher DG. The work 

attitudes of full-time and part-time registered nurses. 

Health Care Manage Rev. Summer 1990;15(3):79-85. 

Not eligible outcomes. 

2773. Wheaton M. Cross-training: meeting staffing needs in 

the ICU. Nurs Manage. Nov 1996;27(11):32B. Not 

eligible exposure. 

2774. Wheeler EC. The CNS's impact on process and 

outcome of patients with total knee replacement. Clin 

Nurse Spec. Jul 2000;14(4):159-169; quiz 170-152. 

Not eligible exposure. 

2775. Wheeler J. How to delegate your way to a better 

working life. Nurs Times. Sep 6-12 2001;97(36):34-

35. Not eligible target population.

2776. Whelchel C. Patients first when budgeting. Nurs 

Manage. Mar 2004;35(3):16. Review. 

2777. Whiley K. The nurse manager's role in creating a 

healthy work environment. AACN Clin Issues. Aug 

2001;12(3):356-365. Comment. 
B-83 

2778. Whitby RM, McLaws ML. Hollow-bore needlestick 

injuries in a tertiary teaching hospital: epidemiology, 

education and engineering. Med J Aust. Oct 21 

2002;177(8):418-422. Not eligible target population. 

2779. White C. Pique practice. Nurs Times. Jun 18-24 

2002;98(25):24-25. Comment. 

2780. White CL. Changing pain management practice and 

impacting on patient outcomes. Clin Nurse Spec. Jul 

1999;13(4):166-172. Not eligible exposure. 

2781. White F, Buswell C, Scullion J, Baldwin M. Doctor's 

orders. Nurs Stand. Feb 19-25 2003;17(23):21. Not 

eligible target population. 

2782. White RJ. Cost-cutters eliminate skilled nurses. 

Revolution. Summer 1997;7(2):2. Editorial. 

2783. Whitehead E. Staff shortages would be a thing of the 

past with a return to ward-based training. Nurs Times. 

Dec 1-7 1999;95(48):43. Not eligible target 

population. 

2784. Whitman GR, Kim Y, Davidson LJ, Wolf GA, Wang 

SL. Measuring nurse-sensitive patient outcomes 

across specialty units. Outcomes Manag. Oct-Dec 

2002;6(4):152-158; quiz 159-160. Not eligible 

exposure. 

2785. Whittington R, Wykes T. Violence in psychiatric 

hospitals: are certain staff prone to being assaulted? J 

Adv Nurs. Feb 1994;19(2):219-225. Not eligible 

target population. 

2786. Whittington R, Wykes T. An evaluation of staff 

training in psychological techniques for the 

management of patient aggression. J Clin Nurs. Jul 

1996;5(4):257-261. Not eligible exposure.

2787. Wichowski HC, Kubsch SM, Ladwig J, Torres C. 

Patients' and nurses' perceptions of quality nursing 

activities. Br J Nurs. Oct 23-Nov 12 

2003;12(19):1122-1129. Not eligible exposure. 

2788. Widmark-Petersson V, von Essen L, Lindman E, 

Sjoden PO. Cancer patient and staff perceptions of 

caring vs clinical care. Scand J Caring Sci. 

1996;10(4):227-233. Not eligible target population.

2789. Widmark-Petersson V, von Essen L, Sjoden PO. 

Perceptions of caring among patients with cancer and 

their staff. Differences and disagreements. Cancer 

Nurs. Feb 2000;23(1):32-39. Not eligible exposure. 

2790. Wiesner G, Harth M, Szulc R, Jurczyk W, 

Sobczynski P, Hoerauf KH, Hobbhahn J, Taeger K. A 

follow-up study on occupational exposure to inhaled 

anaesthetics in Eastern European surgeons and 

circulating nurses. Int Arch Occup Environ Health. 

Jan 2001;74(1):16-20. Not eligible target population. 

2791. Wiklander M, Samuelsson M, Asberg M. Shame 

reactions after suicide attempt. Scand J Caring Sci. 

Sep 2003;17(3):293-300. Not eligible target 

population. 

2792. Wild D, Bradley EH. The gap between nurses and 

residents in a community hospital's error-reporting 

system. Jt Comm J Qual Patient Saf. Jan 

2005;31(1):13-20. Not eligible exposure. 

2793. Wild D, Nawaz H, Chan W, Katz DL. Effects of 

interdisciplinary rounds on length of stay in a 

telemetry unit. J Public Health Manag Pract. Jan-Feb 

2004;10(1):63-69. Not eligible exposure. 

2794. Wiles R, Postle K, Steiner A, Walsh B. Nurse-led 

intermediate care: patients' perceptions. Int J Nurs 

Stud. Jan 2003;40(1):61-71. Not eligible target 

population. 

2795. Wilhoite SL, Ferguson DA, Jr., Soike DR, 

Kalbfleisch JH, Thomas E. Increased prevalence of 

Helicobacter pylori antibodies among nurses. Arch 

Intern Med. Mar 22 1993;153(6):708-712. Not 

eligible exposure. 

2796. Wilkinson CL. An evaluation of an educational 

program on the management of assaultive behaviors. 

J Gerontol Nurs. Apr 1999;25(4):6-11. Not eligible 

outcomes. 

2797. Wilkinson R. Safe practice: machine age killers. Nurs 

Stand. Jul 15-21 1992;6(43):44-45. Comment. 

2798. Williams AM, Irurita VF. Therapeutically conducive 

relationships between nurses and patients: an 

important component of quality nursing care. Aust J 

Adv Nurs. Dec-1999 Feb 1998;16(2):36-44. Not 

eligible target population. 

2799. Williams AM, Irurita VF. Therapeutic and nontherapeutic interpersonal interactions: the patient's 

perspective. J Clin Nurs. Oct 2004;13(7):806-815. 

Not eligible target population.

2800. Williams AM, Irurita VF. Enhancing the therapeutic 

potential of hospital environments by increasing the 

personal control and emotional comfort of 

hospitalized patients. Appl Nurs Res. Feb 

2005;18(1):22-28. Not eligible exposure. 

2801. Williams C, George L, Lowry M. A framework for 

patient assessment. Nurs Stand. Jun 15-21 

1994;8(38):29-33. No association tested. 

2802. Williams G, Slater K. Absenteeism and the impact of 

a 38-hour week, rostered day off option. Aust Health 

Rev. 2000;23(4):89-96. Not eligible target 

population. 

2803. Williams KA, Stotts RC, Jacob SR, et al. Inactive 

nurses: a source for alleviating the nursing shortage? 

Journal of Nursing Administration Apr 

2006;36(4):205-10. Not relevant. 

2804. Williams J. Orienting foreign nurse graduates through 

preceptors. J Nurs Staff Dev. Jul-Aug 1992;8(4):155-

158. Comment. 

2805. Williams R. Happy together. Nurs Stand. Aug 23-29 

2000;14(49):18-19. Comment. 

2806. Williams R. It all adds up. Nurs Stand. Apr 19-25 

2000;14(31):12-13. Review. 

2807. Williams RP. Nurse leaders' perceptions of quality 

nursing: an analysis from academe. Nurs Outlook. 

Nov-Dec 1998;46(6):262-267. Review. 

2808. Williams S. Missing RN would threaten safety in OR. 

Revolution. Jul-Aug 2000;1(4):9. News. 

2809. Williams S, McGowan S. Professional autonomy: a 

pilot study to determine the effects of a professional 

development program on nurses' attitudes. J Nurs 

Staff Dev. May-Jun 1995;11(3):150-155. Not eligible 

outcomes. 

2810. Williams S, Whelan A, Weindling AM, Cooke RW. 

Nursing staff requirements for neonatal intensive 

care. Arch Dis Child. May 1993;68(5 Spec No):534-

538. Not eligible target population. 
B-84 

2811. Williams SA. The relationship of patients' perceptions 

of holistic nurse caring to satisfaction with nursing 

care. J Nurs Care Qual. Jun 1997;11(5):15-29. Not 

eligible exposure. 

2812. Willis E. Benchmarking working time in health care: 

the case of Excelcare. Aust Health Rev. 

2002;25(3):134-140. Not eligible target population. 

2813. Willis J. Unpalatable options. Nurs Times. Aug 12-18 

1998;94(32):28-29. Case Reports. 

2814. Willson B. Floating to another worksite. Can I say 

no? Nurs BC. Apr 2002;34(2):23. Comment.

2815. Wilson CK. Getting results with integrity. Aspens 

Advis Nurse Exec. Oct 1998;14(1):2-3. Editorial. 

2816. Wilson M. Client centred approach to community 

child and family care: a descriptive account of social 

support services provided by Plunket nurses in the 

central region. Nurs Prax N Z. Mar 1996;11(1):12-18. 

Not eligible target population.

2817. Wilson N. I can see clearly now. Interview by Debbie 

Smith. Nurs Stand. Jun 28-Jul 4 2000;14(41):18-19. 

Interview. 

2818. Wilson TA, Jenkins EL. Development of a women's 

wellness center in Almaty, Kazakhstan. J Obstet 

Gynecol Neonatal Nurs. Mar-Apr 2001;30(2):231-

239. Not eligible target population.

2819. Windsor K. Temporary assignments: a new process. 

Nurs Manage. Nov 1997;28(11):84-86. Comment. 

2820. Wing KT. When flex comes to shove: staffing and 

hospital census. Nurs Manage. Jan 2001;32(1):43-46. 

Case Reports.

2821. Winkleman L. Nursing in Texas--a personal account. 

AARN News Lett. Mar 1993;49(3):10-11. Comment. 

2822. Winnefeld M, Richard MA, Drancourt M, Grob JJ. 

Skin tolerance and effectiveness of two hand 

decontamination procedures in everyday hospital use. 

Br J Dermatol. Sep 2000;143(3):546-550. Not eligible 

target population. 

2823. Winstead-Fry P, Bormolini S, Keech RR. Clinical 

care coordination program: a working partnership. J 

Nurs Adm. Jul-Aug 1995;25(7-8):46-51. No 

association tested. 

2824. Wintle JM, Pattrin L, Crutchfield JE, Allgeier PJ, 

Gaston-Johansson F. Job satisfaction and the 12-hour 

shift. Nurs Manage. Feb 1995;26(2):54. Comment. 

2825. Wirt GL. Causes of institutionalism: patient and staff 

perspectives. Issues Ment Health Nurs. May-Jun 

1999;20(3):259-274. Not eligible target population. 

2826. Wise LC. The erosion of nursing resources: employee 

withdrawal behaviors. Res Nurs Health. Feb 

1993;16(1):67-75. Not eligible outcomes. 

2827. Witchell L. Managing international recruits. Nurs 

Manag (Harrow). Jun 2002;9(3):10-14. Not eligible 

target population. 

2828. Wolf G, Gabriel VH, Omachonu VK. Using 

simulation to project staffing levels. Nurs Manage. 

Aug 1992;23(8):64A, 64D, 64F passim. Not eligible 

outcomes. 

2829. Wolf ZR, Colahan M, Costello A. Relationship 

between nurse caring and patient satisfaction. 

Medsurg Nurs. Apr 1998;7(2):99-105. Not eligible 

exposure. 

2830. Wolf ZR, Haakenson DA, Jablonski RA, McGoldrick 

TB. Nurses' perceptions of harmful outcomes from 

medication errors. Medsurg Nurs. Dec 1995;4(6):460-

467, 471. Not eligible outcomes. 

2831. Wolsieffer D. Retention and work environment. Nurs 

Econ. May-Jun 2004;22(3):165. Letter. 

2832. Wong DF, Leung SS, So CK. Differential impacts of 

coping strategies on trati the mental health of Chinese 

nurses in hospitals in Hong Kong. Int J Nurs Pract. 

Jun 2001;7(3):188-198. Not eligible target 

population. 

2833. Wong FK, Chow S, Chang K, Lee A, Liu J. Effects of 

nurse follow-up on emergency room revisits: a 

randomized controlled trial. Soc Sci Med. Dec 

2004;59(11):2207-2218. Not eligible target 

population. 

2834. Wood CJ. Can nurses safely assess the need for 

endotracheal suction in short-term ventilated patients, 

instead of using routine techniques? Intensive Crit 

Care Nurs. Aug 1998;14(4):170-178. Not eligible 

target population. 

2835. Wood D. Acting on complaints about mental health 

services. Implications of power imbalances. J Manag 

Med. 1996;10(3):31-38. Not eligible target 

population. 

2836. Wood D. Nurses receive bonuses for patient 

satisfaction. Pa Nurse. Jan-Feb 2004;59(1):4. News. 

2837. Wood L. Autotransfusion in the postanesthesia care 

unit. J Post Anesth Nurs. Apr 1991;6(2):98-101. Not 

eligible outcomes. 

2838. Woodcraft B. Shift work: benighted existence. Nurs 

Stand. Mar 18-24 1992;6(26):46. Comment. 

2839. Woodhouse AJ. A late shift in accident and 

emergency. Accid Emerg Nurs. Oct 1995;3(4):219-

220. Not eligible target population. 

2840. Woodward W. Preparing a new workforce. Nurs Adm 

Q. Jul-Sep 2003;27(3):215-222. Review. 

2841. Woogara J. Patients' rights to privacy and dignity in 

the NHS. Nurs Stand. Jan 12-18 2005;19(18):33-37. 

Not eligible target population.

2842. Woolliscroft JO, Howell JD, Patel BP, Swanson DB. 

Resident-patient interactions: the humanistic qualities 

of internal medicine residents assessed by patients, 

attending physicians, program supervisors, and 

nurses. Acad Med. Mar 1994;69(3):216-224. Not 

eligible exposure. 

2843. Wootten N. Evaluation of 12-hour shifts on a 

cardiology nursing development unit. Br J Nurs. Nov 

9-22 2000;9(20):2169-2174. Not eligible target 

population. 

2844. Worthington K. Reproductive hazards on the job. Am 

J Nurs. Oct 2001;101(10):104. Comment. 

2845. Wortley V, Grierson-Hill L. Developing a successful 

self-rostering shift system. Nurs Stand. Jul 2-8 

2003;17(42):40-42. Not eligible target population. 

2846. Wotton K, Gassner LA, Ingham E. Flushing an i.v. 

line: a simple but potentially costly procedure for 

both patient and health unit. Contemp Nurse. Oct 

2004;17(3):264-273. Not eligible target population. 

2847. Wright B. Nursing: an ageing population. Accid 

Emerg Nurs. Apr 1998;6(2):65. Editorial. 
B-85 

2848. Wright B. Can you work? Accid Emerg Nurs. Jul 

2000;8(3):127. Editorial. 

2849. Wright S. Standing up for Pink. Nurs Times. Oct 3-9 

1990;86(40):18. Comment. 

2850. Wright S. Eastern light. Nurs Stand. Nov 24-30 

2004;19(11):20-21. Comment. 

2851. Wright V. It just doesn't add up. Br J Perioper Nurs. 

Jul 2004;14(7):300. Not eligible target population. 

2852. Wrona-Sexton S. Patient classification systems: 

another perspective. Nurs Manage. Dec 

1992;23(12):38-39. Not eligible exposure. 

2853. Wu ML, Courtney M, Berger G. Models of nursing 

care: a comparative study of patient satisfaction on 

two orthopaedic wards in Brisbane. Aust J Adv Nurs. 

Jun-Aug 2000;17(4):29-34. Not eligible target 

population. 

2854. Wylie DM. Staffing to meet patient care needs. Can J 

Nurs Adm. Jan-Feb 1998;11(1):5-6. Editorial. 

2855. Wynd C. Leapfrog Group jumps over nursing. Nurs 

Manage. Dec 2002;33(12):20. News. 

2856. Wynd CA, Samstag DE, Lapp AM. Bacterial carriage 

on the fingernails of OR nurses. Aorn J. Nov 

1994;60(5):796, 799-805. Not eligible exposure. 

2857. Yang KP. Relationships between nurse staffing and 

patient outcomes. J Nurs Res. Sep 2003;11(3):149-

158. Not eligible target population. 

2858. Yang KP, Huang CK. The effects of staff nurses' 

morale on patient satisfaction. J Nurs Res. Jun 

2005;13(2):141-152. Not eligible exposure.

2859. Yang Y, Koh D, Ng V, Lee FC, Chan G, Dong F, 

Chia SE. Salivary cortisol levels and work-related 

stress among emergency department nurses. J Occup 

Environ Med. Dec 2001;43(12):1011-1018. Not 

eligible target population. 

2860. Yassi A, Tate R, Cooper J, Jenkins J, Trottier J. 

Causes of staff abuse in health care facilities. 

Implications for prevention. Aaohn J. Oct 

1998;46(10):484-491. Not eligible exposure. 

2861. Yeakel S, Maljanian R, Bohannon RW, Coulombe 

KH. Nurse caring behaviors and patient satisfaction: 

improvement after a multifaceted staff intervention. J 

Nurs Adm. Sep 2003;33(9):434-436. Not eligible 

exposure. 

2862. Yeh SH, Lee LN, Ho TH, Chiang MC, Lin LW. 

Implications of nursing care in the occurrence and 

consequences of unplanned extubation in adult 

intensive care units. Int J Nurs Stud. Mar 

2004;41(3):255-262. Not eligible target population. 

2863. Yeung SS, Genaidy A, Deddens J, Sauter S. The 

relationship between protective and risk 

characteristics of acting and experienced workload, 

and musculoskeletal disorder cases among nurses. J 

Safety Res. 2005;36(1):85-95. Not eligible target 

population. 

2864. Yi M, Jezewski MA. Korean nurses' adjustment to 

hospitals in the United States of America. J Adv Nurs. 

Sep 2000;32(3):721-729. Not eligible outcomes. 

2865. Yip VY. New low back pain in nurses: work 

activities, work stress and sedentary lifestyle. J Adv 

Nurs. May 2004;46(4):430-440. Not eligible 

outcomes. 

2866. Yip Y. A study of work stress, patient handling 

activities and the risk of low back pain among nurses 

in Hong Kong. J Adv Nurs. Dec 2001;36(6):794-804. 

Not eligible target population. 

2867. Yoder LH. Staff nurses' career development 

relationships and self-reports of professionalism, job 

satisfaction, and intent to stay. Nurs Res. Sep-Oct 

1995;44(5):290-297. Not eligible target population. 

2868. Young J. Changing attitudes towards families of 

hospitalized children from 1935 to 1975: a case study. 

J Adv Nurs. Dec 1992;17(12):1422-1429. Not eligible 

exposure. 

2869. Young WB, Lehrer EL, White WD. The effect of 

education on the practice of nursing. Image J Nurs 

Sch. Summer 1991;23(2):105-108. Not eligible 

outcomes. 

2870. Young WB, Minnick AF, Marcantonio R. How wide 

is the gap in defining quality care? Comparison of 

patient and nurse perceptions of important aspects of 

patient care. J Nurs Adm. May 1996;26(5):15-20. Not 

eligible exposure. 

2871. Yurugen B. Patient-centred care in Turkey. Edtna 

Erca J. Apr-Jun 2002;28(2):95-96. Not eligible target 

population. 

2872. Yuska C, Crabtree-Tonges M, Schaps MT. Staff 

nurse weekend program proves cost effective. Nurs 

Adm Q. Winter 1984;8(2):62-73. Not eligible year. 

2873. Zahr LK, William SG, el-Hadad A. Patient 

satisfaction with nursing care in Alexandria, Egypt. 

Int J Nurs Stud. 1991;28(4):337-342. Not eligible 

target population. 

2874. Zahourek RP. Intentionality: evolutionary 

development in healing: a grounded theory study for 

holistic nursing. Journal of Holistic Nursing Mar 

2005;23(1):89-109. Not relevant. 

2875. Zarich S, Pust-Marcone J, Amoateng-Adjepong Y, 

Manthous CA. Failure of a brief educational program 

to improve interpretation of pulmonary artery 

occlusion pressure tracings. Intensive Care Med. Jun 

2000;26(6):698-703. Not eligible exposure. 

2876. ZborilBenson LR. Why nurses are calling in sick: the 

impact of heath-care restructuring. Canadian Journal 

of Nursing Research Mar 2002;33(4):89-107. Not 

relevant. 

2877. Zeler KM, McPharlane TJ, Salamonsen RF. 

Effectiveness of nursing involvement in bedside 

monitoring and control of coagulation status after 

cardiac surgery. Am J Crit Care. Sep 1992;1(2):70-

75. Not eligible target population.

2878. Zeleznik J, Agard-Henriques B, Schnebel B, Smith 

DL. Terminology used by different health care 

providers to document skin ulcers: the blind men and 

the elephant. J Wound Ostomy Continence Nurs. Nov 

2003;30(6):324-333. Not eligible exposure. 

2879. Ziegler E, Mason HJ, Baxter PJ. Occupational 

exposure to cytotoxic drugs in two UK oncology 

wards. Occup Environ Med. Sep 2002;59(9):608-612. 

Not eligible target population. 

2880. Zimmermann PG. "On call" staffing. J Emerg Nurs. 

Dec 1993;19(6):529-531. Comment.
B-86 

2881. Zimmermann PG. Use of "stat" nurses in the 

emergency department. J Emerg Nurs. Aug 

1995;21(4):335-337. Comment.

2882. Zimmermann PG. Self-scheduling in the emergency 

department. J Emerg Nurs. Feb 1995;21(1):58-61. 

Comment. 

2883. Zimmermann PG, Will TL, Soules DM, Fiore T. 

Avoiding registered nurse layoffs: three hospitals 

share how it's done. J Emerg Nurs. Aug 

1996;22(4):323-327. Comment. 

2884. Zohar Z, Eitan A, Halperin P, Stolero J, Hadid S, 

Shemer J, Zveibel FR. Pain relief in major trauma 

patients: an Israeli perspective. J Trauma. Oct 

2001;51(4):767-772. Not eligible target population. 

2886. Zurbrugg HR, Piehler S, Weiss HM. How to run a 

heart surgical unit: experiences during the first year of 

the Department of Cardiothoracic and Vascular 

Surgery, University Clinic of Regensburg. J 

Cardiovasc Surg (Torino). Feb 1997;38(1):53-61. Not 

eligible target population. 
C-1 

Appendix C: Technical Expert Panel Members and Affiliation 

TEP Member Affiliation 

Sandra Edwardson, Ph.D., R.N. School of Nursing 

University of Minnesota 

Colleen Goode, R.N., Ph.D., F.A.A.N. Patient Care Services 

University of Colorado Hospital 

Christine Kovner, Ph.D., R.N. College of Nursing 

New York University 

Barbara Mark, R.N., Ph.D., F.A.A.N. School of Nursing 

University of North Carolina at Chapel Hill 

Jack Needleman, Ph.D. School of Public Health 

UCLA 

Pamela Thompson, M.S., R.N., F.A.A.N. Chief Executive Officer 

American Organization of Nurse Executives 

Peer reviewer comments on a preliminary draft of this report were considered by the EPC in 

preparation of this final report. Synthesis of the scientific literature presented here does not 

necessarily represent the views of individual reviewers. 
D-1 

Appendix D: Sample Abstraction Forms 

Nurse Staffing in North American Hospitals 

Staffing Ratios/Patient Outcomes Abstraction Form 

(Complete for each study) 

Number of the study 

First author 

Year of the publication 

Journal of the publication 

Database to identify the study 

Person to score the study 

Publication type (check one) 

 Published article 

 Administrative report 

 Dissertation 

 Abstract/Presentation 

 Book/book chapter 

Purpose/aim of study 

Design of the study (check one) 

 prospective cohort 

 retrospective cohort 

 cross-sectional 

 descriptive study 

 case-control 

 case-series 

 randomized controlled clinical trial 

 not randomized clinical interventions 

 ecologic 

Nurse staffing variables (independent variables) 

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

Data source for nurse staffing variables (define) 

Nurse to patient ratios: 

Registered nurse/patient ratio 

 Yes No 

If Yes, define 

Licensed nurse practitioner/patient ratio 

 Yes No 

If Yes, define 

Aid/patient ratio, number of patients/aid 

 Yes No 

If Yes, define 
D-2 

Proportion of RN among nursing personnel 

 Yes No 

If Yes, define 

Licensed nurses/patient ratio 

 Yes No 

If Yes, define 

Proportion of licensed nurses among nursing personnel 

 Yes No 

If Yes, define 

Measures of nurse work hours

Total hours of care/patient day 

 Yes No 

If Yes, define 

Registered nurse hours/patient day 

 Yes No 

If Yes, define 

Licensed nurse hours/patient day 

 Yes No 

If Yes, define 

Aid hours /patient day 

 Yes No 

If Yes, define 

Patient outcomes variables

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of the variable used in the article. 

Mortality 

 Yes No 

If Yes, define 

Data source to measure mortality : 

Time of follow up from the day of surgery to death, in days____________ 

Time of follow up from hospitalization to death , in days_______________ 
D-3 

Mortality rate in groups with different staffing levels 

 Yes No 

If yes, how reported (mark all applicable): 

 Number of events 

 Proportion in % 

 Relative risk 

Adverse drug events

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide the data source to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Source 

to 

measure 

Reporting 

number of 

events 

Proportion 

in % 

Relative 

risk 

 Yes No 

Adverse events 

Other 

 

Length of stay.

Length of stay in the unit, days 

 Yes No 

Length of stay in the hospital, days 

 Yes No 

Data source to measure LOS 

Data extraction table: Complete cells with values of LOS reported in the article 

Categories of 

independent staffing 

variable 

LOS 

Exposure variable Mean STD Median RR 

Lower 

95%CL 

Upper 

95%CL 

 

LOS in hospital in days 

LOS in units in days 
D-4 

Nurse quality outcomes

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide the data source to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Source 

to 

measure 

Reporting 

number 

of events 

Proportion 

in % 

Relative 

risk 

 Yes No 

Falls 

 

Injury 

Pressure ulcers 

Failure to rescue 

Patient satisfaction.

1. Mark Yes/No by assessment in the study. 

2. Mark how the outcome was reported 

Variable 

Assessment in 

the study 

Reporting 

scores 

% of favorable 

responses 

Relative 

risk 

 Yes No 

 

Satisfaction with nurse care 

Satisfaction with education 

Satisfaction with pain management 

Time from the hospitalization to the measurement of the patient satisfaction, in days __________ days 

Patient satisfaction scale (define)______________________________ 
D-5 

Quality Measures:

Patient related:

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide the data source to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Source 

to 

measure 

Reporting 

number of 

events 

Proportion 

in % 

Relative 

risk 

 Yes No 

 

Urinary tract infection 

Postoperative complications 

Gastrointestinal bleeding 

Hospital-acquired pneumonia 

Shock 

Atelectasis or pulmonal failure 

Accidental extubation 

Nosocomial infection 

Surgical wound infection 

Post surgical thrombosis 

Cardio-pulmonary arrest 

Any complication 

Any Medical complication 

Any surgical complication 

Sepsis 

Post surgical bleeding 

Other 
D-6 

Nurses related:

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide the data source to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Source 

to 

measure 

Reporting 

number of 

events 

Proportion 

in % 

Relative 

risk 

 Yes No 

 

Turnover rate 

Burnout 

Vacancy 

 

Nurse self-reported. 

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide scale to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Scale to 

measure 

Reporting 

scores 

% favorable 

responses 

Relative 

risk 

 Yes No 

 

Satisfaction with job 

 

Perception of adequacy of 

staffing 

Perception of quality care 

Autonomy of nurses 

Nurses Governance 

Stress 

 
D-7 

Patient characteristics.

Patient Eligibility criteria 

Complete the table with definitions used in the article: 

Inclusion criteria Exclusion criteria 

Age 

Sex 

Race 

Insurance 

Residency 

Hospitalization 

Availability of records 

Diagnosis (ICD code) 

Comorbidities 

Severity 

Acuity 

Other 

 

Patients 

 Medical % of the sample 

 Surgical % of the sample 

 Adults % of the sample 

 Pediatric % of the sample 

 combined 

Sample characteristics: 

Complete with values reported in the article and with page number in the article where the data was extracted: 

Page in 

the article 

Exposure 

categories 

Exposure : 

 

# Subjects 

Mean age 

Sex 

% of males 

Not reported 

Race (%) 

White 

Black 

Asian 

Other 

Not reported 

Ethnicity(%) 

Hispanic 

Not Hispanic 

Other 
D-8 

Not reported 

Socioeconomic status (Scores) 

Not reported 

Primary diagnosis 

% ICD codes 

Co morbidities (case-mix index) 

 

Severity 

 

Acuity 

 

DRG 

Nurse characteristics.

Nurse eligibility criteria 

Complete the table with definitions used in the article: 

 Inclusion criteria Exclusion criteria 

 

Age 

License 

Experience 

Gender 

Working status 

Self-selection 

Other 

 

Nurses sample characteristics:

Complete with values reported in the article and with page number in the article where the data was extracted: 

Page in 

the 

article 

Exposure categories 

Exposure : 

 

Mean age 

Gender 

% of males 

Not reported 

Race (%) 

White 

Black 

Asian 

Other 

Not reported 
D-9 

Ethnicity (%) 

Hispanic 

Not Hispanic 

Other 

Not reported 

Foreign graduates % 

Not reported 

 

Other nurse characteristics which may impact patients outcomes:

1. Mark Yes/No by assessment in the study. 

2. Provide the data source to measure the outcome. 

Nurse education 

 Yes No 

Data Source 

Nurse degree 

 Yes No 

Data Source 

Nursing degree Non nursing degree 

Associated degree 

Diploma 

BSN 

MS 

Doctorate 

Nurse experience in years (in nursing) 

 Yes No 

Data Source 

Proportion of nurses with temporary positions (pool nurses) 

 Yes No 

Data Source 

Nursing unions 

 Yes No 

Data Source 
D-10 

Organization characteristics which may impact patient outcomes.

Hospital eligibility criteria

Complete the table with definitions used in the article: 

Inclusion criteria Exclusion criteria 

Data source 

Location 

Size 

Care 

Teaching status 

Ownership 

Availability of information 

Self-selection 

Other 

Status of selected hospital(s) 

 Number of eligible hospitals 

 Number of enrolled hospitals 

 Number of analyzed hospitals 

if more than 1: 

 Teaching, % of the sample 

 Not teaching, % of the sample 

 Combined sample 

Location 

Size (number of beds) 

Ownership 

 profit, % of the sample 

 non profit, % of the sample 

 public, % of the sample 

 private, % of the sample 

Technology index 

 not reported 

Computerization of communication and records 

 not reported 

Central hospital support adequacy 

 not reported 

HMO penetrating 

 not reported 

Clinical units 

 Intensive care unit 

 Labor and delivery 

 Pre-natal 

 Post-natal 

 Nursery 

 Emergency 

 Trauma 

 Critical care 

 Visits 

 Hospital general 

 Medical 

 Surgical 

 Operating room 

 Pediatric 
D-11 

 Post-anesthesia 

 Psychiatry 

 Specialty 

 Step down units 

 Telemetry 

 Combined 

 Unknown 

Data extraction tables. 

/*Complete with values reported in the article with the page number in the articles the data was extracted for a quality 

control*/ 

/*Add as many lines for categories as necessary*/ 

/*Median is calculated when ranges only reported assuming normal distribution*/ 

/*Increment is analyzed when regression coefficients only reported*/ 

Staffing variables: 

Variable 

Categories 

defined by 

authors Mean STD 95%CL Median 

Page 

number 

Ratios 

Registered nurse/patient ratio 

 

Licensed nurse/patient ratio 

Aid/patient ratio, number of patients/aid 

Number of Patients/Licensed nurses 

Proportion of RN among total nursing personnel in % 

Proportion of licensed nurses /total nursing staff in % 

Hours 

Total hours of care/patient day 

 

Registered nurse hours/patient day 

Licensed nurse hours/patient day 

Aid hours /patient day 
D-12 

Patient outcomes. 

/*Add lines for interactions Exposure*Interaction factor*/ 

Outcomes 

Exposure 

categories 

(treatment 

groups) 

Rate 

in % 

Rate in 

% Events Subjects Page 

 Mean STD 95%CL Median 

Mortality 

 

Nurse quality outcomes 

Urinary tract infection 

Falls 

Injury 

Pressure ulcers 

 

Any complication 

Any Medical complication 

Any surgical complication 

Nosocomial infections 

Sepsis 

Surgical wound infection 

Postoperative complications 

Gastrointestinal bleeding 

Post surgical bleeding 

Hospital-acquired pneumonia 

Atelectasis or pulmonal failure 

Accidental extubation 

Post surgical Thrombosis 

Cardio-pulmonary arrest 

Failure to rescue 

Shock 

Continuation of the previous table: 

Outcomes 

Exposure 

categories 

Relative 

Risk 

(RR) 

Lower 

95%CL 

of RR Upper 95%CL of RR Page 

 

Mortality 

Nurse quality outcomes 

Falls 

Injury 

Pressure ulcers 

Urinary tract infection 

Any complication 

Any Medical complication 

Any surgical complication 
D-13 

Nosocomial infections 

Sepsis 

Surgical wound infection 

Postoperative complications 

Gastrointestinal bleeding 

Post surgical bleeding 

Hospital-acquired pneumonia 

Atelectasis or pulmonal failure 

Accidental extubation 

Post surgical Thrombosis 

Cardio-pulmonary arrest 

Failure to rescue 

Shock 

Patient Satisfaction

Outcomes Exposure 

Exposure 

categories 

(treatment 

groups) Mean STD 95%CL Median Page 

 

Satisfaction with nurse care 

Continuation of the previous table: 

Outcomes 

Exposure 

categories 

Relative 

Risk 

(RR) 

Lower 

95%CL 

of RR 

Upper 

95%CL 

of RR Page 

 

Satisfaction with nurse care 

Satisfaction with pain management 

Nurse characteristics:

Variable 

Categories 

defined by 

authors Mean STD 95%CL Median Page 

Nurses characteristics 

Nurse experience in years 

Nurses education (%) 

Associate degree 

BSN 

MS 

PhD 

Proportion of nurses with temporary positions (pool 

nurses) in % 

 

Organization characteristics 

Duration of shift in hours 

Proportion of nurses working full time 
D-14 

Variable 

Categories 

defined by 

authors Mean STD 95%CL Median Page 

Turnover rate 

 

Burnout, % 

Vacancy, % 

Nurses self-reported variables 

Satisfaction with job, % satisfied 

 

Perception of adequacy of staffing, % perceived as 

adequate 

Perception of quality care, % of satisfied 

Autonomy of nurses, % perceived as adequate 

Nurses Governance, % perceived as adequate 

Stress, % of perceived as significant 
D-15 

ASSESSMENT OF STUDY QUALITY 

OBSERVATIONAL STUDIES (based on “Systems to Rate the Strength Of Scientific Evidence, AHRQ Publication No. 

02-E016, April 2002) 

Score each domain on a scale of 0 (poor, not defined) to 5 (excellent, clearly defined) 

Observational Studies Quality Domains/Elements Score 

Study question clearly focused and appropriate 

Notes:

Sampling of Study Population 

Random 

Convenient 

Self-selected 

Notes: 

Clear definition of exposure 

Notes: 

Primary/secondary outcomes defined 

Notes: 

Statistical Analysis: Assessment of confounding attempted Did the analysis adjust for or examine 

the effects of various factors 

Patient characteristics 

Hospital characteristics 

Cluster of patients and hospitals 

Notes:

Statistical methods used to take into account the effect of more than one variable on the outcome 

such as multiple regression, multivariate analysis, regression modeling -see methods in paper 

Notes: 

Measure of effect for outcomes and appropriate measure of precision (SE, 95%CL) 

Notes:

Conclusions supported by results with possible bias and limitations taken into consideration 

Notes: 

Single versus Multi-site study (note one of the other) 

Notes:

Co morbidities mentioned 

Notes:

Co morbidities incorporated in the analyses 

Notes:

Total score 
D-16 

INTERVENTIONAL STUDIES. 

Intervention Studies Quality Domains/Elements Score 

Study question clearly focused and appropriate 

Notes: 

Sampling of Study Population 

Random 

Convenient 

Self-selected 

Notes: 

Clear definition of exposure 

Notes: 

Randomization used to allocate patients (units) into treatment groups 

Notes: 

Randomization allocation concealment method 

Clearly adequate: Centralized randomization by telephone, randomization scheme controlled by 

pharmacy, numbered or coded identical containers administered sequentially, on site computer 

system which can only be accessed after entering the characteristics of an enrolled participant, 

sequentially numbered sealed opaque envelopes. 

Clearly Inadequate: Alternation (consequent, odd-even, etc.), date of birth, date of week 

Sample size Justification of the sample size for each tested hypothesis 

Statistical Analysis: 

Assessment of adequacy of randomization - distribution of confounding factors at baseline in 

treatment groups: 

Patient characteristics 

Hospital characteristics 

Cluster of patients and hospitals 

Notes:

Intention to treat analysis. All eligible patients (units) included into analysis. 

Notes: 

For each primary and secondary outcome, a summary of results for each group, and the estimated 

effect size and its precision (SE, 95% confidence interval). 

Notes: 

Conclusions supported by results with clinical significance of effect size 

Notes: 

Single versus Multi-site study (note one of the other) 

Notes: 

Total score 
D-17 

Study design characteristics 

Adequacy of the sampling (random selection or not) (check one) 

 random sampling 

 convenience sampling 

 non-random sampling 

 single hospital study 

 self-selected 

 not specified 

 all sampled subjects were analyzed 

 sampled subjects were excluded from the analysis___________% 

95% CL as reported estimates of the association between exposure and outcomes 

 Yes No 

P value as reported estimates of the association between exposure and outcomes 

 Yes No 

Correlation coefficient reported between exposure and outcomes 

 Yes No 

Propensity scores used for nonrandom unequal distribution of confounding factors among treatment groups 

 Yes No 

Adjustment for confounding factors: 

Adjustment for age of the patients 

 Yes No 

Adjustment for race of the patients 

 Yes No 

Adjustment for patient sex 

 Yes No 

Adjustment for patient Diagnoses/comorbidities 

 Yes No 

Adjustment for socioeconomic status of the patients 

 Yes No 

Adjustment for hospital (provider) characteristics 

 Yes No 

Country 

 Canada 

 State or province abbreviation 

 Combined 
D-18 

Sampling units (can be more than one) 

 patients ⁪

 hospitals 

 hospital units 

 nurses 

 other (define)_______________ 

Analytic unit (can be more than one) 

 patients 

 hospitals ⁪ - 

 hospital units ⁪ - 

 nurses 

Level of evidence of the individual study (check one) 

Interventions: 

 I – Well-designed randomized controlled trial 

 II-1A - Well-designed controlled trial with pseudo-randomization 

 I-1B - Well-designed controlled trial without randomization 

Observational studies 

 I-2A - Well-designed cohort (prospective) study with concurrent controls 

 I-2B - Well-designed cohort (prospective) study with historical controls 

 II-2C - Well-designed cohort (retrospective) study with concurrent controls 

 II-3 – Well-designed case-controlled (retrospective) study 

 III – Large differences from comparisons between times and/or places 

 IY – Opinion of respected authorities based in clinical experience 
D-19 

Nurse Staffing in North American Hospitals 

Nursing Staffing Strategies /Patient Outcomes Abstraction Form 

(Complete for each study) 

Number of the study 

First author 

Year of the publication 

Journal of the publication 

Database to identify the study 

Person to score the study 

Publication type (check one) 

 Published article 

 Administrative report 

 Dissertation 

 Abstract/Presentation 

 Book/book chapter 

Purpose/aim of study 

Design of the study (check one) 

 prospective cohort 

 retrospective cohort 

 cross-sectional 

 descriptive study 

 case-control 

 case-series 

 randomized controlled clinical trial 

 not randomized clinical interventions 

 ecologic 

Nurse staffing strategies (independent variables). 

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

Data source for variables (define) 

Use of temporary nursing agencies 

 Yes No 

If Yes, define 

Use of part time nurses 

⁪ Yes No 

If Yes, define 

Proportion of registered nurses 

 Yes No 

If Yes, define 

 Experience mix of the nursing staffs 

 Yes No 

If Yes, define 
D-20 

⁪Continuing nurse education

 Yes No 

If Yes, define 

Nurse staffing models

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of staffing strategies (changes in staffing) used in the article 

Patient Focused Care 

 Yes No 

If Yes, define 

Primary or Total Nursing Care 

 Yes No 

If Yes, define 

Team or Functional Nursing Care 

 Yes No 

If Yes, define 

Magnet Hospital Environment/Shared governance 

 Yes No 

If Yes, define 

Evidence Based Clinical Pathway 

 Yes No 

If Yes, define 

Staff scheduling strategies:

Shift 

 Yes No 

If Yes, define 

Duration of shift in hours 

 Yes No 

If Yes, define 

Over time work 

 Yes No 

If Yes, define 

Decentralized scheduling – nurse manager 

 Yes No 

If Yes, define 
D-21 

Patient outcomes variables

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of the variable used in the article. 

Mortality 

 Yes No 

If Yes, define 

Data source to measure mortality :___________ 

Time of follow up from the day of surgery to death, in days____________ 

Time of follow up from hospitalization to death , in days_______________ 

Mortality rate in groups with different staffing levels 

 Yes No 

If yes, how reported (mark all applicable): 

 Number of events 

 Proportion in % 

 Relative risk 

Adverse Drug Events. 

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide the data source to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Source 

to 

measure 

Reporting 

number of 

events 

Proportion 

in % 

Relative 

risk 

 Yes No 

Adverse events 

Other 

 

Length of stay.

Length of stay in the unit, days 

 Yes No 

Length of stay in the hospital, days 

 Yes No 

Data source to measure LOS 
D-22 

Data extraction table: Complete cells with values of LOS reported in the article 

Categories of 

independent staffing 

variable 

LOS 

Exposure variable Mean STD Median RR 

Lower 

95%CL 

Upper 

95%CL 

 

LOS in hospital in days 

LOS in units in days 

Nurse quality outcomes

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide the data source to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Source 

to 

measure 

Reporting 

number 

of events 

Proportion 

in % 

Relative 

risk 

 Yes No 

Falls 

 

Injury 

Pressure ulcers 

Failure to rescue 
D-23 

Patient satisfaction.

1. Mark Yes/No by assessment in the study. 

2. Mark how the outcome was reported 

Variable 

Assessment in 

the study 

Reporting 

scores 

% of favorable 

responses 

Relative 

risk 

 Yes No 

 

Satisfaction with nurse care 

Satisfaction with education 

Satisfaction with pain management 

Time from the hospitalization to the measurement of the patient satisfaction, in days __________ days 

Patient satisfaction scale (define)______________________________ 

Other Quality Measures:

Patient related:

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide the data source to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Source 

to 

measure 

Reporting 

number of 

events 

Proportion 

in % 

Relative 

risk 

 Yes No 

 

Urinary tract infection 

Postoperative complications 

Gastrointestinal bleeding 

Hospital-acquired pneumonia 

Shock 

Atelectasis or pulmonal failure 

Accidental extubation 

Nosocomial infection 
D-24 

 

Surgical wound infection 

Post surgical thrombosis 

Cardio-pulmonary arrest 

Any complication 

Any Medical complication 

Any surgical complication 

Sepsis 

Post surgical bleeding 

Other 

Nurses related:

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide the data source to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Source 

to 

measure 

Reporting 

number of 

events 

Proportion 

in % 

Relative 

risk 

 Yes No 

 

Turnover rate 

Burnout 

Vacancy 

 
D-25 

Nurse self-reported. 

1. Mark Yes/No by assessment in the study. 

2. Provide the definition of each variable used in the article. 

3. Provide scale to measure the outcome. 

4. Mark how the outcome was reported 

Variable 

Assessment 

in the study Definition 

Scale to 

measure 

Reporting 

scores 

% favorable 

responses 

Relative 

risk 

 Yes No 

 

Satisfaction with job 

 

Perception of adequacy of 

staffing 

Perception of quality care 

Patient characteristics.

Patient Eligibility criteria 

Complete the table with definitions used in the article: 

Inclusion criteria Exclusion criteria 

Age 

Sex 

Race 

Insurance 

Residency 

Hospitalization 

Availability of records 

Diagnosis (ICD code) 

Comorbidities 

Severity 

Acuity 

Other 

 

Patients 

 Medical % of the sample 

 Surgical % of the sample 

 Adults % of the sample 

 Pediatric % of the sample 

 combined 
D-26 

Sample characteristics: 

Complete with values reported in the article and with page number in the article where the data was extracted: 

Page in 

the article 

Exposure 

categories 

Exposure : 

 

# Subjects 

Mean age 

Sex 

% of males 

Not reported 

Race (%) 

White 

Black 

Asian 

Other 

Not reported 

Ethnicity(%) 

Hispanic 

Not Hispanic 

Other 

Not reported 

Socioeconomic status (Scores) 

Not reported 

Primary diagnosis 

% ICD codes 

Co morbidities (case-mix index) 

 

Severity 

 

Acuity 

 

DRG 
D-27 

Nurse characteristics.

Nurse eligibility criteria 

Complete the table with definitions used in the article: 

 Inclusion criteria Exclusion criteria 

 

Age 

License 

Experience 

Gender 

Working status 

Self-selection 

Other 

 

Nurses sample characteristics:

Complete with values reported in the article and with page number in the article where the data was extracted: 

Page in 

the 

article 

Exposure categories 

Exposure : 

 

Mean age 

Gender 

% of males 

Not reported 

Race (%) 

White 

Black 

Asian 

Other 

Not reported 

Ethnicity (%) 

Hispanic 

Not Hispanic 

Other 

Not reported 

Foreign graduates % 

Not reported 

 
D-28 

Organization characteristics which may impact patient outcomes.

Hospital eligibility criteria

Complete the table with definitions used in the article: 

Inclusion criteria Exclusion criteria 

Data source 

Location 

Size 

Care 

Teaching status 

Ownership 

Availability of information 

Self-selection 

Other 

Status of selected hospital(s) 

 Number of eligible hospitals 

 Number of enrolled hospitals 

 Number of analyzed hospitals 

if more than 1: 

 Teaching, % of the sample 

 Not teaching, % of the sample 

 Combined sample 

Location 

Size (number of beds) 

Ownership 

 profit, % of the sample 

 non profit, % of the sample 

 public, % of the sample 

 private, % of the sample 

Technology index 

 not reported 

Computerization of communication and records 

 not reported 

Central hospital support adequacy 

 not reported 

HMO penetrating 

 not reported 

Clinical units 

 Intensive care unit 

 Labor and delivery 

 Pre-natal 

 Post-natal 

 Nursery 

 Emergency 

 Trauma 

 Critical care 

 Visits 

 Hospital general 

 Medical 

 Surgical 

 Operating room 

 Pediatric 
D-29 

 Post-anesthesia 

 Psychiatry 

 Specialty 

 Step down units 

 Telemetry 

 Combined 

 Unknown 

Data extraction tables. 

/*Complete with values reported in the article with the page number in the articles the data was extracted for a quality 

control*/ 

/*Add as many lines for categories as necessary*/ 

/*Median is calculated when ranges only reported assuming normal distribution*/ 

/* Increment is analyzed when regression coefficients only reported*/ 

Staffing variables: 

Variable 

Categories 

defined by 

authors Mean STD 95%CL Median 

Page 

number 

Proportion of part time nurses, in% 

 

Proportion of registered nurses, in % 

 

Proportion of nurses with BS, in % 

Proportion of nurses with MS, in % 

 

Duration of shift in hours 

Patient outcomes. 

/*Add lines for interactions Exposure*Interaction factor*/ 

Outcomes 

Exposure 

categories 

(treatment 

groups) 

Rate 

in % 

Rate in 

% Events Subjects Page 

 Mean STD 95%CL Median 

Mortality 

 

Adverse events 

Adverse events 

Nurse quality outcomes 

Urinary tract infection 

Falls 

Injury 

Pressure ulcers 

 

Any complication 

Any Medical complication 
D-30 

Any surgical complication 

Nosocomial infections 

Sepsis 

Surgical wound infection 

Postoperative complications 

Gastrointestinal bleeding 

Post surgical bleeding 

Hospital-acquired pneumonia 

Atelectasis or pulmonal failure 

Accidental extubation 

Post surgical Thrombosis 

Cardio-pulmonary arrest 

Failure to rescue 

Shock 

Outcomes 

Exposure 

categories 

Relative 

Risk 

(RR) 

Lower 

95%CL 

of RR Upper 95%CL of RR Page 

 

Mortality 

Adverse events 

Nurse quality outcomes 

Falls 

Injury 

Pressure ulcers 

Urinary tract infection 

Any complication 

Any Medical complication 

Any surgical complication 

Nosocomial infections 

Sepsis 

Surgical wound infection 

Postoperative complications 

Gastrointestinal bleeding 

Post surgical bleeding 

Hospital-acquired pneumonia 

Atelectasis or pulmonal failure 

Accidental extubation 

Post surgical Thrombosis 

Cardio-pulmonary arrest 

Failure to rescue 

Shock 
D-31 

Patient Satisfaction

Outcomes Exposure 

Exposure 

categories 

(treatment 

groups) Mean STD 95%CL Median Page 

 

Satisfaction with nurse care 

Satisfaction with pain management 
D-32 

ASSESSMENT OF STUDY QUALITY 

OBSERVATIONAL STUDIES (based on “Systems to Rate the Strength of Scientific Evidence, AHRQ Publication No. 

02-E016, April 2002) 

Score each domain on a scale of 0 (poor, not defined) to 5 (excellent, clearly defined) 

Observational Studies Quality Domains/Elements Score 

Study question clearly focused and appropriate 

Notes:

Sampling of Study Population 

Random 

Convenient 

Self-selected 

Notes: 

Clear definition of exposure 

Notes: 

Primary/secondary outcomes defined 

Notes: 

Statistical Analysis: Assessment of confounding attempted Did the analysis adjust for or examine 

the effects of various factors 

Patient characteristics 

Hospital characteristics 

Cluster of patients and hospitals 

Notes:

Statistical methods used to take into account the effect of more than one variable on the outcome 

such as multiple regression, multivariate analysis, regression modeling -see methods in paper 

Notes: 

Measure of effect for outcomes and appropriate measure of precision (SE, 95%CL) 

Notes:

Conclusions supported by results with possible bias and limitations taken into consideration 

Notes: 

Single versus Multi-site study (note one of the other) 

Notes:

Co morbidities mentioned 

Notes:

Co morbidities incorporated in the analyses 

Notes:

Total score 
D-33 

INTERVENTIONAL STUDIES. 

Intervention Studies Quality Domains/Elements Score 

Study question clearly focused and appropriate 

Notes: 

Sampling of Study Population 

Random 

Convenient 

Self-selected 

Notes: 

Clear definition of exposure 

Notes: 

Randomization used to allocate patients (units) into treatment groups 

Notes: 

Randomization allocation concealment method 

Clearly adequate: Centralized randomization by telephone, randomization scheme controlled by 

pharmacy, numbered or coded identical containers administered sequentially, on site computer 

system which can only be accessed after entering the characteristics of an enrolled participant, 

sequentially numbered sealed opaque envelopes. 

Clearly Inadequate: Alternation (consequent, odd-even, etc.), date of birth, date of week 

Sample size Justification of the sample size for each tested hypothesis 

Statistical Analysis: 

Assessment of adequacy of randomization - distribution of confounding factors at baseline in 

treatment groups: 

Patient characteristics 

Hospital characteristics 

Cluster of patients and hospitals 

Notes:

Intention to treat analysis. All eligible patients (units) included into analysis. 

Notes: 

For each primary and secondary outcome, a summary of results for each group, and the estimated 

effect size and its precision (SE, 95% confidence interval). 

Notes: 

Conclusions supported by results with clinical significance of effect size 

Notes: 

Single versus Multi-site study (note one of the other) 

Notes: 

Total score 
D-34 

Study design characteristics 

Adequacy of the sampling (random selection or not) (check one) 

 random sampling 

 convenience sampling 

 non-random sampling 

 single hospital study 

 self-selected 

 not specified 

 all sampled subjects were analyzed 

 sampled subjects were excluded from the analysis___________% 

95% CL as reported estimates of the association between exposure and outcomes 

 Yes No 

P value as reported estimates of the association between exposure and outcomes 

 Yes No 

Correlation coefficient reported between exposure and outcomes 

 Yes No 

Propensity scores used for nonrandom unequal distribution of confounding factors among treatment groups 

 Yes No 

Adjustment for confounding factors: 

Adjustment for age of the patients 

 Yes No 

Adjustment for race of the patients 

 Yes No 

Adjustment for patient sex 

 Yes No 

Adjustment for patient Diagnoses/comorbidities 

 Yes No 

Adjustment for socioeconomic status of the patients 

 Yes No 

Adjustment for hospital (provider) characteristics 

 Yes No 

Country 

 Canada 

 State or province abbreviation 

 Combined 
D-35 

Sampling units (can be more than one) 

 patients ⁪

 hospitals 

 hospital units 

 nurses 

 other (define)_______________ 

Analytic unit (can be more than one) 

 patients 

 hospitals ⁪ - 

 hospital units ⁪ - 

 nurses 

Level of evidence of the individual study (check one) 

Interventions: 

 I – Well-designed randomized controlled trial 

 II-1A - Well-designed controlled trial with pseudo-randomization 

 I-1B - Well-designed controlled trial without randomization 

Observational studies 

 I-2A - Well-designed cohort (prospective) study with concurrent controls 

 I-2B - Well-designed cohort (prospective) study with historical controls 

 II-2C - Well-designed cohort (retrospective) study with concurrent controls 

 II-3 – Well-designed case-controlled (retrospective) study 

 III – Large differences from comparisons between times and/or places 

 IY – Opinion of respected authorities based in clinical experience 

E-1 

Appendix E: Quality of the Studies 

Table E1 shows the quality of the studies, using a 5 score scale from 0 (poorest) to 5 (highest): 

A. Study question clearly focused and appropriate 

B. Clear definition of exposure 

C. Clear definition of the primary and secondary outcomes 

D. Validation of exposure (yes or no, the responses do not count for the total scores) 

E. Validation of outcomes (yes or no, the responses do not count for the total scores) 

F. Sampling of study population: 

 5 = Random population based sampling 

 4 = Random clinic based sampling 

 3 = Convenient 

 2 = Self-selected 

 1 = Single hospital study 

 0 = Not specified 

G. Statistical Analysis: Assessment of confounding attempted 

H. Adjustment to examine the effects of various factors 

 1) Patient characteristics: age; race; sex; comorbidities; SES - 1-3 scores 

 2) Hospital characteristics – 1+2 - 4 scores 

 3) Cluster of patients and hospitals - 1+2+3 - 5 scores 

I. Statistical methods used to take into account the effect of more than one variable on the 

outcome such as multiple regression, multivariate analysis, regression modeling 

J. Measure of effect for outcomes and appropriate measure of precision (SE, 95% CI) 

K. External validity: single hospital study; multi-site study; nationally representative sample 

L. Conclusions supported by results with possible bias and limitations taken into consideration; 

clinical significance of effect size provided 

M. Total score as a percentage of the maximum possible (50) 

Each item was graded with 0 to 5 scores. We summarized scores (maximum possible 50) to have 

the overall quality score and to compare with the maximum. 

Definitions 

External validity – applicability of the results from the studies on different clinical settings. 

Internal validity – the extent to which the findings of a study accurately represent the causal 

relationship between nurse staffing and patient outcomes. The truth why patients had different 

outcomes may be related to patient characteristics or quality of the treatments (surgical quality) 

more than nurse care. To examine how nurse ratios and hours may affect patient outcomes 

independent of all known factors they measured, the authors adjusted the results for confounding 

factors. 
E-2

Table E1. Quality of the studies 

Year Author Class A B C D E F G H I J K L 

1982 Arnow1 II-2C 5 4 5 Yes Yes 5 3 0 3 2 2 4 1987 Wan2 II-2C 5 4 4 3 4 2 4 4 4 4 1988 Flood3 III 4 4 4 1 3 1 3 3 2 3 1989 Hartz4 III 5 3 4 3 3 3 3 3 4 3 1992 McDaniel5 III 4 4 5 4 3 0 2 2 2 3 1992 Krakauer6 III 5 3 4 5 5 5 4 5 5 4 1993 Halpine7 III 5 4 5 3 3 2 3 3 3 4 1994 Aiken8 II-2B 5 4 5 4 5 5 4 5 4 4 1994 Shamian9 III 4 3 3 3 3 2 3 3 4 4 1994 Taunton10 III 5 4 4 2 3 0 2 3 3 4 1988 Shortell11 II-2C 5 3 4 5 4 4 4 4 5 4 1994 Shortell12 II-2C 5 4 4 4 3 3 3 4 4 4 1995 Grillo-Peck13 III 5 5 4 3 2 1 3 2 3 3 1995 Thorson14 II-2C 5 5 4 4 4 4 4 4 4 5 1996 Fridkin15 II-2C 5 4 5 Yes 4 5 4 5 4 3 4 1996 Dugan16 III 3 3 4 2 0 0 3 2 2 3 1997 Bloom17 III 4 4 5 4 3 3 4 4 5 4 1997 Archibald18 II-2C 5 4 5 Yes 3 3 2 3 3 2 4 1997 Minnick19 III 3 3 3 4 3 2 4 4 4 4 1997 Melberg20 III 0 4 5 3 0 0 2 2 3 3 1997 ANA21 II-2C 5 4 4 3 3 4 3 4 4 4 1998 Blegen22 II-2C 5 4 4 3 3 3 4 2 4 4 1998 Blegen23 II-2C 5 4 5 3 4 3 4 4 3 4 1998 Kovner24 III 5 4 4 4 4 4 4 4 4 4 1998 Leiter25 III 4 4 4 2 3 0 3 3 3 4 1998 Aiken26 II-2C 5 3 5 Yes 3 5 4 4 5 4 4 1999 Pronovost27 II-2C 5 3 5 2 5 5 5 5 4 5 1999 Aiken28 II-2C 5 3 5 Yes 3 5 4 4 5 4 4 1999 Robertson29 II-2C 5 4 5 3 4 4 4 4 4 4 1999 Lichtig30 II-2C 5 4 4 3 4 4 3 4 3 4 1999 Seago31 III 4 4 3 3 0 0 3 3 3 4 1999 Bond32 II-2C 5 4 4 5 4 4 5 5 5 4 2000 Amaravadi33 II-2C 5 4 5 Yes 2 5 5 5 5 4 5 2000 Gandjour34 III 3 3 5 3 4 3 3 4 3 4 2000 Robert35 II-2C 5 5 5 Yes Yes 4 4 2 5 4 3 5 2000 Silber36 II-2C 5 4 5 5 4 5 5 5 5 4 2000 ANA37 II-2C 5 3 4 5 3 3 4 3 5 4 2000 Hoover38 III 5 4 5 3 4 4 3 3 3 4 2000 Unruh39 II-2C 5 4 4 3 4 4 3 4 4 4 2001 Pronovost40 II-2C 5 4 5 3 5 4 5 5 4 5 2001 Dimick41 II-2C 5 4 5 2 5 4 4 5 4 5 
Table E1. Quality of the studies (continued) 

E-3

Year Author Class A B C D E F G H I J K L 

2001 Blegen42 II-2C 4 3 3 3 4 3 4 4 4 4 2001 Needleman43 III 5 5 5 4 5 4 4 5 5 5 2001 Bolton44 III 5 4 4 3 3 2 2 2 4 4 2001 Aiken45 III 4 3 3 3 3 0 2 2 3 4 2001 Whitman46 II-2A 4 4 5 3 2 2 3 3 3 4 2001 Sovie47 II-2C 5 4 4 3 3 2 3 3 3 4 2001 Ridge48 III 5 5 4 4 3 3 3 3 2 4 2001 Ritter-Teitel49 II-2C 5 4 4 5 4 4 4 4 5 5 2002 Dang50 II-2C 5 4 5 3 4 4 5 5 4 5 2002 Aiken51 II-2C 5 3 5 Yes 3 5 5 5 4 4 4 2002 Seago52 III 5 4 5 Yes 3 4 4 4 4 3 4 2002 Tourangeau53 II-2C 5 4 5 Yes Yes 3 5 4 4 4 5 5 2002 Kovner54 III 5 4 4 5 4 4 4 5 4 5 2002 Langemo55 III 5 3 4 3 3 0 2 0 3 3 2002 Needleman56 III 5 4 4 3 5 4 5 5 5 5 2002 Barkell57 III 5 4 5 Yes 3 2 0 2 2 1 3 2002 Stegenga58 II-2C 5 5 5 Yes Yes 3 4 0 5 4 2 4 2002 Whitman59 III 5 4 4 3 3 0 3 2 3 3 2002 Cheung60 III 3 5 5 Yes Yes 3 3 2 2 3 2 3 2002 Oster61 III 5 5 5 3 4 3 4 3 3 3 2003 Aiken62 III 5 4 5 Yes 4 5 5 5 5 4 5 2003 Beckman63 III 5 5 5 Yes Yes 4 4 4 3 3 2 3 2003 Berney64 II-2C 5 5 5 Yes 3 5 5 4 5 4 5 2003 Unruh65 II-2C 5 5 5 3 4 4 4 4 4 5 2003 Cho66,67 II-2C 4 4 4 Yes 3 5 4 5 5 4 5 2003 Langemo68 III 4 3 3 3 2 0 2 2 2 3 2003 Needleman69 III 5 4 4 4 4 4 4 4 5 4 2003 Mark70 II-1B 5 3 4 3 2 1 3 2 3 4 2003 Alonso-Echanove71 II-2A 5 5 5 Yes Yes 4 4 4 5 4 4 5 2003 Bolton72 III 5 4 4 3 2 1 2 3 4 3 2003 Potter73 III 4 4 5 3 3 2 3 3 2 4 2003 Hope74 II-2C 5 5 5 Yes Yes 3 5 4 5 5 3 5 2003 Simmonds75 II-2C 5 4 5 3 4 3 4 4 2 3 2003 Zidek76 II-2C 5 4 4 3 3 3 3 3 3 3 2003 Tallier77 II-2C 4 4 4 3 2 0 3 1 2 3 2004 Person78 II-2C 5 4 5 5 5 5 5 5 5 5 2004 Sochalski79 III 5 3 3 5 3 2 4 3 4 3 2004 Mark80 II-2C 5 4 4 4 4 4 5 5 4 5 2004 Van Doren81 III 4 5 5 4 2 0 3 2 3 4 2004 Vahey82 III 5 3 4 3 4 4 5 5 3 4 2004 Boyle83 III 3 3 4 3 3 2 3 3 2 3 2004 Cimiotti84 II-2C 5 4 4 3 4 4 4 4 3 4 2005 Estabrooks85 III 5 3 5 Yes Yes 3 4 4 5 5 4 4 
Table E1. Quality of the studies (continued) 

E-4

Year Author Class A B C D E F G H I J K L 

2005 Marcin86 II-2C 5 5 5 Yes Yes 3 4 4 5 5 3 4 2005 Elting87 II-2C 5 3 5 3 5 5 5 5 4 4 2005 Mark88 II-2C 5 4 4 4 4 4 4 4 4 5 2004 Donaldson89 III 5 4 3 3 3 2 4 3 4 4 2005 Tschannen90 III 5 5 5 Yes Yes 3 5 4 4 4 2 3 2005 Houser91 III 5 4 5 5 4 4 4 4 5 5 2005 Halm92 III 5 5 5 3 3 3 4 4 2 4 2005 Donaldson93 III 5 5 4 3 4 5 4 5 4 4 2005 Stratton94 II-2C 5 4 4 3 4 4 3 3 4 4 2006 Seago95 II-2C 5 4 5 3 3 2 3 3 3 3 
E-5 

Figure E1 plots the quality scores (expressed as the percent of maximum possible scores) over 

time to look for changes in ratings. Although there is a modestly positive overall trend, it is not 

significant. 

Figure E1. Association between quality of studies and time of publication 

40

50

60

70

80

90

100

1980 1985 1990 1995 2000 2005 2010

Year

Percent
E-6 

Table E2. Studies published in peer reviewed journals indexed in Medline 

Source* 

Number of 

Publications Quality (% from maximum) 

Am J Crit Care 1 86 

Anesthesiology 1 94 

book 2 77 

Can J Nurs Res 1 88 

Cancer 1 88 

Clin Nurse Spec 1 76 

Dissertation 15 77 

Eff Clin Pract 1 90 

Health Econ 1 84 

Health Serv Manage Res 1 82 

Health Serv Res 4 88 

Heart Lung 1 88 

Image J Nurs Sch 1 82 

Infect Control Hosp Epidemiol 4 84 

Intensive Care Med 1 90 

J Health Hum Serv Adm 1 54 

J Nurs Adm 12 65 

J Nurs Care Qual 1 44 

J Nurs Scholarsh 1 66 

J Trauma 1 66 

JAMA 3 89 

Lippincotts Case Manag 1 64 

Manag Care Interface 1 70 

Med Care 8 82 

N Engl J Med 3 81 

Nurs Adm Q 1 

Nurs Econ 4 65 

Nurs Manage 3 49 

Nurs Res 4 79 

Outcomes Manag 1 54 

Pediatr Crit Care Med 1 86 

Pediatr Infect Dis J 1 68 

Pharmacotherapy 1 90 

Phys Rev B Condens Matter 1 76 

Phys Rev C Nucl Phys 1 78 

Policy Polit Nurs Pract 1 70 

QRB Qual Rev Bull 1 76 

Qual Health C 1 84 

Report 1 94 

Report 1 86 

Soc Sci Med 2 64 

*Title abbreviations from the National Library of Medicine 
E-7 

Table E3. Assessment of patient comorbidities in included studies 

Author Source to Measure Patient Outcomes Assessment of Comorbid Conditions 

Analytic Unit 

Aiken Medical charts of consecutively admitted patients Severity classification for AIDS hospitalization, 

clinical AIDS Prognostic Staging 

Analytic unit: Patient 

Aiken Hospitals discharge database ICD codes for pre-existing comorbid conditions 

Analytic unit: Patient 

Aiken Health Care Cost Containment Council ICD codes for pre-existing co morbid conditions 

Analytic unit :Patient 

Aiken HCFA database Medicare Case Mix Index 

Analytic unit: Hospital 

Aiken Patients survey HIV risk categories, illness severity 

Analytic unit: Patient 

AlonsoEchanove Medical charts Secondary diagnoses and individual medical 

history present at the time of the admission 

Analytic unit: Patient 

Amaravadi Uniform Hospital Health Discharge Data Set ICD codes for comorbid conditions (secondary 

diagnoses and procedures) 

Analytic unit: Patient 

ANA HCFA discharges database Patients’ case mix index and severity of Illness 

index 

Analytic unit: Hospital 

ANA Uniform Hospital Discharge Data Set Patient case mix index and severity of Illness 

index 

Analytic unit: Hospital 

Berney New York Statewide Planning and Research 

Cooperative System 

DRG codes for comorbid conditions 

Analytic unit: Hospital 

Blegen Comparative occurrence reporting service 

(CORS) 

Hospital Medicare Case Mix Scores 

Analytic unit: Hospital Unit 

Blegen Hospitals discharge database Hospital Medicare Case Mix Index 

Analytic unit: Hospital Unit 

Blegen Hospital discharge records Patient’s acuity data from the monthly acuity 

system reports 

Analytic unit: Hospital Unit 

Bloom Transaction Cost Analysis; Area Resource File Medicare Case Mix Index 

Analytic unit: Hospital 

Bond Hospital Medicare mortality rates from the Health 

Care Financing Administration 

 Medicare case mix, APACHE scores, Severity of 

Illness scores 

Analytic unit: Hospital 

Boyle Hospital discharge data Patients case mix index 

Analytic unit: Patient 

Cho State inpatient databases DRG codes to calculate the number of diagnoses 

at admission 

Analytic unit: Patient and hospitals 

Cimiotti Patient discharges and medical records reviewed 

by study's nurse epidemiologist 

DRG for comorbid conditions and procedures 

Analytic unit: Patient 

Dang Uniform Hospital Health Discharge Data Set ICD codes for comorbid conditions (secondary 

diagnoses and procedures) 

Analytic unit: Patient 

Dimick Uniform Health Discharge Data Set ICD codes for comorbid conditions (secondary 

diagnoses and procedures) 

Analytic unit: Patient 

Elting Center for Medicare and Medicaid Services and 

the American Hospital Association 

Comorbid conditions were coded using the 

Dartmouth Manitoba Adaptation of Charlson 

comorbidity score

Analytic unit: Hospital 

Estabrooks Hospital inpatient database Charlson index modified by Devo 

Analytic unit: Patient 
Table E3. Assessment of patient comorbidities in included studies (continued) 

E-8 

Author Source to Measure Patient Outcomes Assessment of Comorbid Conditions 

Analytic Unit 

Fridkin Medical records Severity of illness with APACHE II scores 

Analytic unit: Patient 

Gandjour Health Care Financing Administration Medicare case-mix 

Analytic unit: Hospital 

Halm Hospital's data warehouse with patient 

discharges 

DRGs codes for comorbid conditions 

Analytic unit: Patient 

Halpine Hospital Medical Records Institute database Case Mix Groups 

Analytic unit: Patient 

Hartz Hospital discharges data from The Health Care 

Financing Administration (HCFA) 

ICD codes for 4 secondary diagnoses, Severity 

of Illness index 

Analytic unit: Hospital 

Hoover Health Care Financing Administration, 

HealthCareReportCards.com; MEDPAR 

database 

Medicare Case Mix Index 

Analytic unit: Hospital 

Hope Medical Microbiology Laboratory and Infection 

Control Services; Discharge Abstract Database 

Patient severity of Illness index 

Analytic unit: Patient 

Houser Nationwide inpatient sample of 2001 with 

hospital discharge records 

ICD codes for comorbid conditions 

Analytic unit: Patient 

Kovner National Inpatient Sample (NIS) Medicare Case Mix Index 

Analytic unit: Hospital 

Kovner Nationwide inpatient sample of hospital 

discharges 

Medicare Case Mix Index 

Analytic unit: Hospital 

Krakauer Medical records for all Medicare discharges ICD codes for 4 comorbid conditions and 

additional clinical data with MediQual system 

Analytic unit: Hospital 

Marcin Medical charts, Pediatric Intensive Care Unit 

Evaluations Database 

Pediatric Risk of Mortality (PRISM) III index 

Analytic unit: Patient 

Mark Centers for Medicare Services Minimum Cost 

and Capital File, CMS Provider of Services File, 

CMS Case Mix Index File, CMS Online Survey 

Certification and Reporting system (OSCAR) 

files, and HCUP files 

CMS Case Mix Index 

Analytic unit: Hospital 

Mark Hospital’s incident reporting system CMS Case Mix Index File 

Analytic unit: Patient (survey) 

Mark Healthcare Cost and Utilization Project (HCUP) 

National Inpatient Sample (NIS) 

CMS case mix index file, Medstat's Disease 

Staging methodology 

Analytic unit: Hospital 

Needleman Hospital discharge data from 11 states (all 

patients and Medicare sample) and MedPAR 

national database (all Medicare patients) 

DRGs codes for comorbid conditions 

Analytic unit: Hospital and units 

Person Medicare database Patients severity of illness index 

Analytic unit :Patient 

Pronovost Uniform Hospital Health Discharge Data Set ICD codes for comorbid conditions 

Analytic unit: Patient 

Pronovost Uniform Hospital Health Discharge Data Set ICD codes for comorbid conditions (secondary 

diagnoses and procedures) 

Analytic unit: Patient 

Ridge Patient survey 2 weeks after discharge with 

computerized phone interview system 

Medicare case mix 

Analytic unit: Patient 

Ritter-Teitel Hospitals Incidence reports and patient surveys Patients case mix index 

Analytic unit: Unit 

Robert Medical charts Severity of illness with APACHE II scores 

Analytic unit: Patient 

Robertson HCFA database and Hospitals Information 

Reports 

Medicare Case Mix Index 

Analytic unit: Hospital 

Seago California Office of Statewide Health Planning 

and Development (OSHPD) Hospital Disclosure 

Report database 

Patients severity of illness index 

Analytic unit: Hospital 
Table E3. Assessment of patient comorbidities in included studies (continued) 

E-9 

Author Source to Measure Patient Outcomes Assessment of Comorbid Conditions 

Analytic Unit 

Seago Incident reporting system, patient survey Case-mix index 

Analytic unit: Patient 

Shamian National Comparative Database for Nursing 

Resource Consumption 

ICD codes for secondary diagnoses present at 

admission 

Analytic unit: Unit 

Shortell MedPAR dataset of hospital discharges Medicare case mix 

Analytic unit: Hospital 

Shortell Hospitals discharge data DRG codes for comorbid conditions, APACHE III 

scores 

Analytic unit: Unit 

Silber Pennsylvania Medicare claims records; Medicare 

Standard Analytic Files; random sample of 50% 

of Medicare patients who underwent general 

surgical or orthopedic procedures 

ICD codes for comorbid conditions present at 

admission and physician’s current procedural 

terminology for outpatient visits within 3 months 

before index hospital stay 

Analytic unit: Hospital 

Tourangeau Ontario Acute Care Hospitals Dataset DCID codes for pre-existing comorbid conditions 

(Manitoba adaptation of the Charlson index) 

Analytic unit: Hospital 

Tschannen Patient medical records Patient Acuity Index, ICD codes for comorbid 

conditions 

Analytic unit: Patient 

Unruh Pennsylvania Health Care Cost Containment 

Council 

MediQual severity measure to calculate scores 

Analytic unit: Hospital 

Unruh State Health Care Cost Containment Council MediQual severity scores 

Analytic unit: Patient 

Wan Hospital records Patient Acuity Index 

Analytic unit: Hospital 

Zidek Hospital discharge data, patient records, and 

chart audits 

Patients severity of illness index 

Analytic unit: Patient 
E-10 

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F-1 

Appendix F. Analytic Framework 

Appendix F contains details on analytical framework of the meta-analysis: definitions, 

hypotheses, and statistical models. 

Differences in definitions of nurse staffing. The variation in the ways nurse staffing rates are 

calculated and expressed makes it difficult to summarize data across studies. The nurse to patient 

or patients to nurse ratio reflects the number of patients cared for by one nurse typically specified 

by job category (RN, LPN, or LVN); this ratio may be calculated by shift or by nursing unit; 

some researchers use this term to mean nurse hours per inpatient day. 

Various authors used different operational definitions for the nurse to patient ratio, including: 

• number of patients cared for by one nurse per shift 

• FTE/1,000 patient-days 

• nurse/patient-day or FTE/occupied bed 

Total nursing staff or hours per patient day represent all staff or all hours of care including RN, 

LPN, LVN, and aides counted per patient day (a patient day is the number of days any one 

patient stays in the hospital, i.e. one patient staying 10 days would be 10 patient days). 

RN, LPN, or LVN full-time equivalents per patient day: (an FTE is 2,080 hours per year and can 

be composed of multiple part-time or one full-time individual.1

 FTE/occupied bed ratios were 

calculated based on FTE/mean annual number of occupied bed-days (patient-days). 

We reported nursing rates as they were used by individual authors, but we have also created two 

standardized rates for purposes of comparison. 

1. The number of patients cared by one nurse per shift. This ratio can be expressed as 

FTE/patient or patients/FTE per shift. 

2. RN FTE/patient day ratio 

We conducted separate analysis and report the results in these ways: 

• with definitions the authors used 

• corresponding to increase by 1 RN FTE/patient day 

• in categories of patients/RN per shift in ICUs, and with surgical and medical patients. 

Different methods have been used to estimate nurse hours per patient day from FTEs. Some 

investigators assume a 40 hour week and 52 working weeks per year (2,080 hours/year). Others 

use more conservative estimates (e.g. 37.5 hours per week for 48 weeks = 1,800 hours/year). In 

our conversions, we used the latter estimate:2

Nurse hours per patient day = (FTE*40)/patient days3

One nurse/patient day = 8 working hours per patient day 2

Then the patient/nurse ratio = 24 hours/nurse hours per patient day.3

We made the following assumptions: 

37.5 hour work week on average; 

48 working weeks/year (4 weeks vacation, holidays, sick time); 
F-2 

All FTE are full-time nurses with the same shift distribution (assume 3 8-hour shifts); 

Length of shift does not modify the association between nurse staffing and patient outcomes; 

Patient density is the same over the year. 

The same estimation was used for the each nurse job category- RN, LPN, and UAP. 

The following examples of calculations may help clarify the approach to conversions. 

1. The authors reported RN FTE/1,000 patient-days. 

 We calculated: 

RN hours/patient days: [(RN FTE/1,000 *1,800hours)]/1,000 

 Nurse to patient per shift ratio: 

 Patient/nurse ratio = 24 hours/nurse hours per patient day3

Numeric example: The authors reported 3 RN FTE/1,000 patient days 

RN hours/patient day = (3*1,800)/1,000=5.4 RN hours/patient day 

Patients/RN per shift ratio = 24 hours/5.4 = 4.4 patients 

2. The authors reported RN/patient day 

 We calculated 

 RN hours/patient days: (FTE*40)/5 patient days per week3

 RN hours/patient day = FTE*8 

 Patients/RN per shift ratio = 24 hours/RN hours per patient day3

 

Numeric example: The authors reported 0.5 FTE/patient day 

 RN hours/patient day: 0.5 FTE*8 hours = 4 hours/patient day 

 Patients/RN per shift ratio = 24 hours/4 = 6 patients 

3. The authors reported patients/RN per shift ratio. 

 We calculated 

 RN hours/patient day = 24 hours/reported ratio of patients/RN3

 RN FTE/patient day = RN hours per patient day/8 hours 

Numeric example: The authors reported 2 patients/RN/shift 

 RN hours/patient day = 24 hours/2 = 12 hours/patient day 

 RN FTE/patient day = 12 hours per patient day/8 hours = 1.5 RN FTE 

When the authors reported outcome rates among different categories of nurse staffing; we 

extracted the reported means or calculated medians of nurse staffing ranges. When the authors 

reported changes in outcomes corresponding to 1 unit increase in nurse staffing ratio. We defined 

a reference nurse staffing level equal to the published means4,5 in different clinical settings 

assuming that the same linear association would be observed corresponding to an increase by 1 

unit from the mean. This assumption ignores nonlinearity but provides more realistic staffing 

estimation. When the authors reported regression coefficients form several statistical models, we 

used maximum likelihood criteria to extract one regression coefficient for the pooled analysis—

models with significant regression coefficient for the association: 

• the smallest number of nonsignificant regression coefficients for confounding factors in the 

model 

• main effects models without interaction and nonlinear associations. 
F-3 

Independent staffing variables for questions 1, 2, and 4 extracted from the studies: 

RN FTE/patient day as a continuous variable 

Patients/RN/shift ratio as a continuous variable 

Quartiles of patients/RN/shift ratio as a categorical variable 

Patients/LPN/shift ratio as a continuous variable 

Patients/UAP/shift ratio as a continuous variable 

Total nursing hours as a continuous variable equal nursing hours/patient or patient day 

RN hours/patient day as a continuous variable equal RN hours/patient day 

LPN hours/patient day as a continuous variable equal LPN hours/patient day 

UAP hours/patient day as a continuous variable equal UAP hours/patient day 

Licensed hours/patient day as a continuous variable equal RN and LPN hours/patient day 

We calculated means, standard deviations, and quartiles of nurse staffing variables in different 

clinical settings to compare with published articles.4,5

Nurse Variables Needleman et al 

Number of hours of nursing care per patient-day Mean ± STD 

Registered nurse–hours 7.8 ± 1.9 

Licensed-practical nurse–hours 1.2 ± 1.0 

Aide hours 2.4 ± 1.2 

Total 11.4 ± 2.3 

Proportion of total hours of nursing care (%) 

Registered nurse hours 68 ± 10 

The present report: 

Nurse Staffing Number of Studies Mean Standard Deviation 

ICUs 

RN FTE/patient day 15 1.31 0.70 

Patients/RN per shift 15 3.11 1.82 

Total nursing hours/patient day 15 11.00 5.23 

RN hours/patient day 10 12.61 5.28 

LPN hours/patient day 3 0.34 0.57 

UAP hours/patient day 4 2.26 1.20 

Licensed nurse hours/patient day 1 7.29 0.43 

Surgical patients 

RN FTE/patient day 13 1.14 0.84 

Patients/RN per shift 13 4.04 2.32 

Patients/LPN per shift 2 3.07 2.21 

Total nursing hours/patient day 12 7.73 4.31 

RN hours/patient day 11 7.81 5.28 

LPN hours/patient day 7 1.49 1.58 

UAP hours/patient day 5 2.07 0.62 

Medical patients 

RN FTE/patient day 20 1.10 0.99 

Patients/RN per shift 20 4.42 2.94 

Patients/LPN per shift 6 13.25 8.52 

Patients/UAP per shift 4 11.95 8.87 

Patients/licensed nurse per shift 2 4.12 1.09 

Total nursing hours/patient day 27 8.23 4.36 

RN hours/patient day 23 6.06 3.60 

LPN hours/patient day 13 2.84 3.33 

UAP hours/patient day 12 2.97 3.22 

Licensed nurse hours/patient day 4 3.32 2.92 
F-4 

Independent staffing strategies variables:

Skill mix % of RN nurses/total nursing personnel as a continuous variable 

 % of nurses with BSN degrees/total nursing personnel as a continuous variable 

 % of licensed nurses (RNs + LPNs)/total nursing personnel as a continuous variable 

Experience mix: nurse experience in years as a continuous variable 

 % of overtime nursing hours as a continuous variable 

 % of temporary nurses as a continuous variable 

 % of full-time nurses as a continuous variable 

The authors used different operational definitions of the outcomes rates: the percentage of the 

patients with outcomes among all hospitalized patients and the rates of the outcomes per 1,000 

patient days. We reported these rates as they were used by the individual authors, but we have 

also standardized rates as the percentage of patients with outcomes among all hospitalized 

patients for purposes of comparison. We estimated that 

Percentage of patients with outcomes = (rate per 1,000 patient days/10) * an average length of 

stay. We use published averages of length of stay in ICUs, in medical, and surgical patients.4

Weighting variable:

Sample size as patient or analytic unit number (when patient number was not reported); hospital 

number per every level of exposure. 

Tested sources of heterogeneity:

1. Analytic unit 

2. Patient population 

3. Hospital unit 

2. Study design 

3. Adjustment for comorbidities 

4. Definition of nurse to patient ratio 

5. Quality scores 

6. Adjustment for provider characteristics and patient socio-economic status 

7. Adjustment for clustering between providers and patients 

8. Source of the data (administrative vs. medical record) 

9. Definition of outcomes 

We tested the possible sources of heterogeneity as interaction variables which could modify the 

effect of nurse staffing on patient outcomes and conducted sensitivity analysis within each 

category of effect modifiers. 

Hypotheses tested in pooled analysis: 

1. The outcome is associated with nurse staffing as a continuous variable, weighted by the study 

sample size * number of hospitals, in a random effects model—random intercept for each 

study 

2. The outcome is associated with nurse staffing as a continuous variable, weighted by the study 

sample size * number of hospitals, in a fixed effects model 
F-5 

3. The outcome is associated with nurse staffing as a continuous variable with nonlinear 

association, weighted by the study sample size * number of hospitals in a random effects 

model 

4. The outcome is associated with nurse staffing as a continuous variable with nonlinear 

association, weighted by the study sample size * number of hospitals, in a fixed effects 

model 

5. The association with nurse staffing as a continuous variable can be modified by analytic unit 

(hospital, unit, and patient levels), when the model is weighted by the study sample size * 

number of hospitals in a random effects model—random intercept for each study 

6. The association with nurse staffing as a continuous variable can be modified by analytic unit 

when the model is weighted by the study sample size * number of hospitals in a fixed effects 

model 

7. The association with nurse staffing as a continuous variable can be modified by hospital unit 

(ICU, medical, surgical) when the model is weighted by the study sample size * number of 

hospitals in a random effects model—random intercept for each study 

8. The association with nurse staffing as a continuous variable can be modified by hospital unit 

when the model is weighted by the study sample size * number of hospitals in a fixed effects 

model 

9. The association with nurse staffing as a continuous variable can be modified by patient type 

(medical vs. surgical) when the model is weighted by the study sample size * number of 

hospitals in a random effects model with a random intercept for each study. 

10. The association with nurse staffing as continuous variables can be modified by patient type 

(medical vs. surgical) when the model is weighted by the study sample size * number of 

hospitals in a fixed effects model 

11. The outcome was associated with nurse staffing as a categorical variables, weighted by the 

study sample size * number of hospitals, in a random effects model—random intercept for 

each study 

12. The outcome is associated with nurse staffing as continuous variable weighted by the study 

sample size * number of hospitals in a fixed effects model 

13. A sensitivity analysis by analytic units, hospital units, and patient population tested all 

previous hypotheses with random and fixed effects models weighted by the sample size in 

subgroups where the analytic units are hospitals, hospital units, and patients and the hospital 

units are ICU, medical, and surgical and the patients are medical and surgical 

14. Individual studies were analyzed with simple linear regression in STATA to find slopes for 

each study when possible. Meta-analysis was used to estimate pooled regression coefficients: 

changes in outcomes corresponding to incremental changes by one unit in nurse staffing 

15. Interaction models and sensitivity analysis examined the effects of the year of outcomes 

occurrence and adjustment for patient and provider characteristics and clustering of patients 

and providers. 

Algorithms of meta-analysis6

Pooled estimate as a weighted average: 

∑

∑

=

i

i

i

i i

IV

w

wθ

θ
F-6 

Weights are inverse of variance (standard error):2

Standard error of pooled estimate: 

Heterogeneity (between-study variability) measured by: 

Assumptions for random effects model: true effect sizes qi have a normal distribution with mean 

q and variance t2; t2 is the between-study variance 

Between study variance: 

Where: 

wi are the weights from the fixed effect inverse-variance method 

Q is the heterogeneity test statistic from before (either from inverse-variance method or MantelHaenszel method) 

k is the number of studies, and 

t2 is set to zero if Q<k-1 

Random effect pooled estimate is weighted average: 

Weights used for the pooled estimate are similar to the inverse-variance, but now incorporate a 

component for between-study variation: 

Standard error of pooled estimate 

The likelihood-based approach to general linear mixed models was used to analyze the 

association between independent variable and outcomes with the basic assumption that the data 

are linearly related to unobserved multivariate normal random variables. 

2 ( )

1

i

i SE

w

θ =

∑ =

i

i

IV

w

SE 1 (θ )

2 ( ) i IV

i

Q = ∑wi θ −θ

∑ ∑

∑

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎝

⎛

−

− − =

i

i

i

i

i

i

w

w

w

Q k

2

2 ( 1)

τ

∑

∑

=

i

i

i

i i

DL

w

w

'

' θ

θ

2 2 ( )

1 ' θ + τ =

i

i SE

w

∑ =

i

i

DL

w

SE '

1 (θ )
F-7 

General linear model Y = Xβ + ε 

(Y - the vector of observed yi's, X - known matrix of xij's, β- the unknown fixed-effects parameter 

vector, and ε - the unobserved vector of independent and identically distributed Gaussian random 

errors) is written in the mixed model: 

Y = Xβ + Zλ + ε

where Z - known design matrix, and λ the vector of unknown random-effects parameters.

The model assumes that λ and ε are normally distributed. 

Attributable risk was calculated as the outcome events rate in patients exposed to different nurse 

staffing levels.7-9

Attributable risk of the outcome = rate of events in patients with below of the recommended 

nurse/patient ratio x (relative risk = 1) 

Number needed to treat to prevent one adverse event was calculated as reciprocal to absolute risk 

differences in rates of outcomes events in the groups of the patients with different nurse staffing 

levels.10

Administrative data was obtained to estimate nurse shortage and distribution in a state level in 

the USA.11,12 Correlation between nurse distribution and fatal adverse events related to health 

care were computed with 95%confidence level to determine a strength and directions of the 

correlations.13

Definitions of fatal injuries related to health care: 

Misadventures to patients during surgical and medical care (E870-E876): 

E870 Accidental cut, puncture, perforation, or hemorrhage during medical careE870.0 Surgical operation 

E870.1 Infusion or transfusion 

E870.2 Kidney dialysis or other perfusion 

E870.3 Injection or vaccination 

E870.4 Endoscopic examination 

E870.5 Aspiration of fluid or tissue, puncture, and catheterization 

Abdominal paracentesis 

Aspirating needle biopsy 

Blood sampling 

Lumbar puncture 

Thoracentesis 

E871 Foreign object left in body during procedure 

E872 Failure of sterile precautions during procedure 

E873 Failure in dosage 

E873.0 Excessive amount of blood or other fluid during transfusion or infusion 

 E873.1 Incorrect dilution of fluid during infusion 

 E873.2 Overdose of radiation in therapy 

 E873.3 Inadvertent exposure of patient to radiation during medical care 

 E873.4 Failure in dosage in electroshock or insulin-shock therapy 

 E873.5 Inappropriate [too hot or too cold] temperature in local application and packing 
F-8 

 E873.6 Nonadministration of necessary drug or medicinal substance 

 E873.8 Other specified failure in dosage 

 E873.9 Unspecified failure in dosage 

E874 Mechanical failure of instrument or apparatus during procedure 

E875 Contaminated or infected blood, other fluid, drug, or biological substance 

Includes: 

presence of: 

bacterial pyrogens 

endotoxin-producing bacteria 

serum hepatitis-producing agent 

E876 Other and unspecified misadventures during medical care 

E876.0 Mismatched blood in transfusion 

E876.1 Wrong fluid in infusion 

E876.2 Failure in suture and ligature during surgical operation 

E876.3 Endotracheal tube wrongly placed during anesthetic procedure 

E876.4 Failure to introduce or to remove other tube or instrument 

E876.5 Performance of inappropriate operation 

E876.8 Other specified misadventures during medical care 

Performance of inappropriate treatment NEC 

E876.9 Unspecified misadventure during medical care 

Surgical and medical procedures as the cause of abnormal reaction of patient or later 

complication, without mention of misadventure at the time of procedure (E878-E879) 

Includes: 

procedures as the cause of abnormal reaction, such as: 

displacement or malfunction of prosthetic device 

hepatorenal failure, postoperative 

malfunction of external stoma 

postoperative intestinal obstruction 

rejection of transplanted organ 

E878 Surgical operation and other surgical procedures as the cause of abnormal reaction of 

patient, or of later complication, without mention of misadventure at the time of operation 

E879 Other procedures, without mention of misadventure at the time of procedure, as the cause 

of abnormal reaction of patient, or of later complication 

Drugs, medicinal and biological substances causing adverse effects in therapeutic use (E930-E949) 

Includes: 

correct drug properly administered in therapeutic or prophylactic dosage, as the cause of any 

adverse effect including allergic or hypersensitivity reactions 
F-9 

References 

1. United States: Agency for Healthcare Research and 

Quality; University of California SF-SE-BPC. Making 

health care safer: a critical analysis of patient safety 

practices. Chapter 39. Nurse Staffing, Models of Care 

Delivery, and Interventions. Rockville, MD: Agency 

for Healthcare Research and Quality; 2001. 

2. American Nurses Association. Nurse Staffing and 

Patient Outcomes: In the Inpatient Hospital Setting. 

Washington DC: American Nurses Association; 2000. 

3. Spetz J. Minimum nurse staffing ratios in California 

acute care hospitals. San Francisco: California 

Workforce Initiative; 2000. 

4. Needleman J. Nurse staffing and patient outcomes in 

hospitals. Final Report for Health Resources Services 

Administration. 2001; Contract No. 230990021. 

5. Kovner C, Jones CB, Gergen PJ, Nurse Staffing in 

Acute Care Hospitals, 1990-1996. Policy, Politics, & 

Nursing Practice. 2000;1(3):194-204. 

6. DerSimonian R, Laird N. Meta-analysis in clinical 

trials. Control Clin Trials. Sep 1986;7(3):177-88. 

7. Dawson B and Trapp RG. Basic & Clinical 

Biostatistics (LANGE Basic Science). McGrawHill/Appleton & Lange. 2004. 

8. Harold A. Kahn CTS. Statistical Methods in 

Epidemiology (Monographs in Epidemiology and 

Biostatistics). Oxford University Press, USA. 1989. 

9. Egger M. Systematic Reviews in Health Care. BMJ, 

London, 2001 ISBN:0-7279-1488-X. 

http://www.blackwellpublishing.com/medicine/bmj/sy

streviews/pdfs/chapter18.pdf. 

10. Ebrahim S. The use of numbers needed to treat 

derived from systematic reviews and meta-analysis. 

Caveats and pitfalls. Eval Health Prof. Jun 

2001;24(2):152-64. 

11. Cho S-H. Nurse staffing and adverse patient outcomes 

[PhD]: Dissertation, University of Michigan; 2002. 

12. Spratley E. The registered nurse population. March 

2000, findings from the National Sample Survey of 

Registered Nurses. Rockville, MD; U.S. Dept. of 

Health & Human Services, Health Resources and 

Services Administration, Bureau of Health 

Professions, Division of Nursing. 2000: 

http://www.bhpr.hrsa.gov/healthworkforce/reports/rns

urvey/rnss1.htm. 

13. Centers for Disease Control. WISQARS Injury 

Mortality Reports. 1999-2003; Dept. of Health and 

Human Services, Public Health Services; OCLC: 

44350522: http://www.cdc.gov/ncipc/. 

G-1 

Appendix G: Evidence Tables 

Table G1. Design, external, and internal validity of the studies that examined 

the associations between nurse staffing and strategies and patient 

outcomes...................................................................................................... 3 

Table G2. Calculated change in hospital-related mortality corresponding to an 

increase by 1 RN, LPN, and UAP/patient day (results from individual 

studies)....................................................................................................... 35 

Table G3. Evidence of the association between nurse staffing and mortality ............. 36 

Table G4. The relative risk of hospital-related mortality among estimated 

categories or patients/nurse/shift ratio........................................................ 54 

Table G5. Evidence of the association between nurse/patient ratio and patient 

outcomes.................................................................................................... 55 

Table G6 Patient outcomes corresponding to an increase by one RN/patient 

day (effects reported by authors and calculated from published 

results, more studies contributed to pooled analysis)................................. 77 

Table G7. Patient outcomes corresponding to an increase by one patient/LPN 

(effects reported by authors and calculated from published results, 

more studies contributed to pooled analysis) ............................................. 79 

Table G8. Patient outcomes corresponding to an increase by one patient/UAP 

(effects reported by authors and calculated from published results, 

more studies contributed to pooled analysis) ............................................. 80 

Table G9. The association between nurse staffing and length of stay ........................ 81 

Table G10. Calculated change in hospital related mortality corresponding to an 

increase by 1 nursing hour/patient day (results from individual 

studies)....................................................................................................... 93 

Table G11. Evidence of the association between nurse hours/patient day and 

patient outcomes ........................................................................................ 94 

Table G12. Patient outcomes corresponding to an increase by 1 nursing 

hour/patient day (calculated from published results, more studies 

contributed to pooled analysis)................................................................. 138 

Table G13. Relative risk of patient outcomes corresponding to an increase by 1 

nurse hour/patient day as reported by authors ......................................... 140 

Table G14. Patient outcomes corresponding to an increase by 1 RN hour/patient 

day (calculated from published results, more studies contributed to 

pooled analysis)........................................................................................ 143 

Table G15. Relative risk of patient outcomes corresponding to an increase by 1 

RN hour/patient day as reported by authors............................................. 145 

Table G16. Patient outcomes corresponding to an increase by 1 LPN 

hour/patient day (effects reported by authors and calculated from 

published results, more studies contributed to pooled analysis)............... 149 

Table G17. Patient outcomes corresponding to an increase by 1 unlicensed 

assistive personnel hour/patient day (effects reported by authors and 

calculated from published results, more studies contributed to pooled 

analysis) ................................................................................................... 150 
G-2 

Table G18. Evidence of the association between nurse education and experience 

and patient outcomes ............................................................................... 151 

Table G19. The association between nurse characteristics and patient outcomes..... 154 

Table G20. The evidence of the association between nurse staffing and patient 

satisfaction ............................................................................................... 161 

Table G21. Research studies related to staffing ratios/hours/skill mix in acute 

care hospitals (not included in questions 1, 2, and 4)............................... 165 

Table G22. Research studies related to shift work of nurses (types of shifts; 

length of shifts) ......................................................................................... 169 

Table G23. Research studies related to use of agency/contract nursing staff in 

hospitals ................................................................................................... 173 

Table G24. Research studies related to full- and part-time nursing staff..................... 177 

Table G25. Research studies related to internationally educated nurses (IEN) .......... 181 

Table G26. Research related to nursing staff overtime ............................................... 184 

Table G27. Evidence of the association between nurse skill mix (proportion of 

registered nurses) and patient outcomes ................................................. 189 

Table G28. Relative risk of patient outcomes corresponding to an increase by 1% 

of RNs in nurse skill mix as reported by authors....................................... 209 

Table G29. Evidence of the association between nurse strategies (overtime 

hours, temporary nurse hours, full-time hours) and patient outcomes...... 211 

Table G30. The significant effect modification by the study design of the association 

between nurse staffing and patient outcomes .......................................... 216 

References for Evidence Tables ................................................................................. 217 
G-3

Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and stratoutcomes Case control studies 

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Fridkin, 19661

Article 

Examine the associations between nurse staffing and central venous catheterassociated bloodstream infections 

Single hospital study: university-affiliated Veterans Affairs medical center 

1992-1993, Patient, Random sample of 1,760 patients 

Medical records, Adults, Catheterassociated bloodstream infections, Veterans Affairs 

Patient age, gender, length of stay, primary diagnosis, severiof illness 

Arnow, 19822Article 

Examine association between staffing by overtime or temporary nurses and nosocomial infection in a burn unit 

Single unit study, Medical records 

1975, Patient, 147 patients, 27.21% 

Medical records, Adults 

Not reported 

Marcin, 20053

Article 

Examine the association between unplanned extubation and years of nurse experience and nurse-to-patient ratio in the pediatric intensive care unit 

Single hospital study 1999-2002, Patient, 

220 patients 

Medical records, Children 

Matching: a) weaning status aduration of intubation; b) patient age; and severity of illness as defined by PRISM III. Adjustment: patieage, physical restraints, sedatiopatient agitation 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-4

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Aiken, 19984

Article 

Examine association between hospital organization , nurse burnout, an patient satisfaction 

American Hospital Association Annual Hospital Survey 

1990-1991, Patient, 1,393 patients, 13.50% 

Medical records, Adults, AIDS 

Patient sex, age, race, type of insurance, HIV ricategories, illnesseverity; admittinphysician as a paof an AIDS specialty servicethe extent of nurscontrol over practice environment 

Aiken, 19995

Article 

Compare differences in AIDS patients' 30-day mortality and satisfaction with care in dedicated AIDS units, scattered-bed units in hospitals with and without dedicated AIDS units, and in magnet hospitals known to provide good nursing care 

American Hospital Association Annual Hospital Survey 

1990-1991, Patient, 1,393 patients, 13.50% 

Medical records, Adults, AIDS 

Patient sex, age, race, type of insurance, HIV ricategories, illnesseverity; admittinphysician as a paof an AIDS specialty servicethe extent of nurscontrol over practice environment 

Robert, 20006

Article 

Examine the association between nosocomial primary bloodstream infections (BSIs) and nursing-staff levels in surgical intensive care unit (SICU) patients 

Single hospital study - 20-bed SICU in a 1,000-bed inner-city public hospital, 100, South 

1994-1995, Patient, Random sample of 127 patients 

Medical records, Adults, Nosocomial primary bloodstream infections 

Patient age, diagnosis, comorbidity, lengof stay 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-5

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Aiken, 19947

Article 

Examine the association between Medicare mortality and hospitals with different nursing care 

39 magnet hospitals and 195 control hospitals, selected using a multivariate matched sampling procedure that controls for hospital characteristics, 28.2%, 7.7% 

1988, Hospital, Random sample of 234 hospitals 

Administrative, Adults, 65, Medicare 

Patient age, sex, comorbidities, typand source of admission, propensity scores for 12 hospital characteristics census, size occupancy rate, location, technology index

Case-series 

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Seago, 19998Article 

Examine the association of patientfocused care at one tertiary care university teaching hospital on patient outcomes 

Single tertiary care hospital study before and after implementation of patient-focused care 

1996-1997, Patient, 89,256 patients 

Medical records, Adults 

Not reported 

Donaldson, 20059

Article 

Examine patients’ outcomes before and after legislations for mandatory nurse/patient ratios in California hospitals 

Convenience sample of 68 acute hospitals participating in the California Nursing Outcomes Coalition project 

2004-2005, Unit, 268, 39.55% 

Administrative, Adults 

Not reported; before-after comparison were conducted in the same units 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-6

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Grillo-Peck, 199510

Article 

Examine the impact of implementation of a new nursing partnership model with a reduction of RN from 80% to 60% on patient outcomes in neuroscience unit 

Single hospital study 1995-1993, Patient, 

156 patients

Medical records, Adults, Cerebro vascular diseases 

Not reported. The authors reported that patients had similar demographic characteristics 

Cross-sectional studies

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Hartz, 198911

Article 

Examine the association between nurse staffing and mortality in Medicare population 

3,100 hospitals from the 1986 HCFA mortality study and the American Hospital Association's 1986 annual survey of hospitals, 8.1%, 11.9%

1986, Hospital, 5,781 patients 46.38% 

Administrative, Adults >65years, Medicare 

Severity of illness 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-7

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Krakauer, 199212Article 

Examine the association of nurse staffing on mortality in Medicare population 

84 statistically selected hospitals from 1986 American Hospital Association (AHA) survey, Single hospital study

1986, Hospital, 42,773 patients, Random sampling, bias assessed 

Medical records Adults, >65 years, Medicare 

Patient one principal dischargdiagnosis, up to four secondary diagnoses, age, sex, race, comorbidities, transfer status; hospital size, location, financestechnical capabilof the hospital, cluster patients ahospitals 

McDaniel, 199213

Article

Examine relationship between nurse turnover and patient and nurse satisfaction 

Single hospital study Patient, 300 patients Medical records, 

Adults 

Not reported 

Halpine, 199314

Article

Examine the association between nurse staffing and length of stay in Ontario hospitals 

The Hospital Medical Records Institute, 75% 

1989-1990, Hospital, 40,000 patients, 22.36% 

Administrative Nursing intensity 

index 

Shamian, 199415

Article

Examine relationship between length of stay and hours per patient day in 11 clinical specialty areas

58 hospitals in the U.S., 33% 

Unit, 1,733 patients Administrative Patient age, 

primary and secondary diagnosis; hospitunionization, unit computerization, hospital ownersh

Taunton, 199416

Article 

Examine associations between patient outcomes and staff registered nurse absenteeism 

Taunton, 25% 1989-1990, Unit, 65 

units 

Administrative, Adults 

Not reported 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-8

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Dugan, 199617

Article

Examine the association between nurses’ perceived stress and patient incidents, including falls 

Single hospital study 1996, Nurse, 600 

nurses, 51.17% 

Survey Not reported 

Bloom, 199718

Article

Examine association between registered nurses (RNs) from temporary agencies; part-time career RNs; RN rich skill mix; and organizationally experienced RNs on operational and total hospital cost

1981 AHA annual survey of hospitals; A 20% random sample (1,222 hospitals) 

Hospital, 732 hospitals, 20.36%, Random sampling, sample bias assessed 

Administrative, Adults 

Hospital size, ownership/controteaching status, operating capacitgeographic regiourban/rural statuslocal economic climate, hospital wage rates, suppof nursing labor within the community 

Minnick, 199719

Article 

Examine association between nurse staffing and patient satisfaction 

117 no intensive medical-surgical inpatient units in 17 hospitals selected from a pool of 69 institutions within a metropolitan area by a stratified random sample

1991-1992, Unit, 2,595 patients, 20.96% 

Survey, Adults Patient age, 

gender, marital status, race, education, diagnosis 

Melberg, 199720

Book 

Examine the association between nurse staffing and length of stay 

Single system in California, 100%, Pacific

1994-1995, Hospital, 5% 

Administrative, Adults 

Not reported 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-9

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Leiter, 199821Article

Examine the relationships of nurse burnout, intention to quit, and meaningfulness of work as assessed on a staff survey with patient satisfaction with nursing care

Single hospital study 1998, Patient 

Random sample of 605 patients 

Survey Not reported 

Kovner, 199822

Article 

Examine the relationship between nurse staffing and adverse events controlling for related hospital characteristics

Stratified probability sample of U.S. community hospitals - 589 acute-care hospitals in 10 states, 21%, 11.8%

1993, Hospital, 900 hospitals, 34.56% 

Administrative, Adults, >18years 

Case mix (patienage, sex, and comorbidity); hospital teaching status, ownershipbed size, region 

Hoover, 200023

Dissertation 

Examine the association between managed care penetration, nurse staffing, and hospital outcomes in three southern states 

American Hospital Association Annual Survey, Health Care Financing Administration, Mississippi State Department of Public Health Office of Rural Health, U.S. Census Bureau

1995-1997, Hospital, 271 hospitals, 35.06% 

Administrative, Adults, >65 years, Chronic obstructive pulmonary disease, viral pneumonia, heart attack, shock, stroke, and hip procedures, Medicare 

Patient age, sex, race, procedure, comorbidity; hospital size, location, and teaching status 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-10

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Gandjour, 200024

Article 

Determine the effect of managed health care plans on hospital staffing 

Tennessee Department of Health, 17%, 25.97%, 29-60% 

1995, Hospital, 151 hospitals, 49.01% 

Administrative, Adults 

Medicare case-mnumber of patiendays, hospital beds, average salary, hospital status, occupancrate 

Ridge, 200125

Dissertation 

Examine the association between nurse staffing and patient satisfaction 

Single hospital studyJCAHO-accredited tertiary care hospital, 100% 

1997-1999, Patient, 5,509 patients, 80.47% 

Survey, Adults Patient age, 

gender, race, and acuity, Medicare case mix, primary and secondary diagnoses 

Bolton, 200126

Article 

Examine association between nurse staffing and patient safety outcomes 

Voluntary sample of California acute care hospitals; 257 medical, surgical, medical-surgical combined, step-down, 24-hour observation units, and critical care patient care units, 9% of all general acute care hospitals in California

1998-1999, Unit, 257 units, Sampling bias, Assessed 

Administrative, Adults, >16 years 

Not reported 

Aiken, 200127Article

Examine the association between nurse staffing and mortality 

Hospital Association Annual Survey 

1997-1998, Hospital, 22 hospitals 

Administrative, Adults, Medicare 

Not reported 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-11

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Needleman, 200128,29Report 

Examine the relationship between patient outcomes potentially sensitive to nursing and nurse staffing in inpatient units in acute care hospitals 

American Hospital Association Annual Survey of hospitals; hospital patient discharge data and state hospital financial reports or hospital staffing surveys; 11 states across the U.S. 

1997, Hospital, 3,173,705 patients 

Administrative Patient diagnosis

age, sex, comorbidities, health care, emergency admission, hospilocation, number beds, occupancy rate, teaching status, patient acuity in each hospital’s mix of patients 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-12

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Cho, 200230

Dissertation 

Examine the association between nurse staffing and adverse patient outcomes 

Hospital Financial Data and HCUP State Inpatient Database, 5.6%, 29.7%

1997, Hospital, 124,204 patients 

Administrative, Adults, >18 years 

Patient age, sex, race, primary payer, DRG, number of diagnoses at admission, and type of admission (scheduled or unscheduled); hospital location, size, teaching status, ownershipclustering patientin hospitals (two levels model) 

Oster, 200231

Dissertation 

Examine the association between nurse staffing and patient outcomes in patient with acute myocardial infarction in urban emergency department

Single hospital study in an academic medical center

2000-2001, Patient, 543 patients 

Medical records, Adults, Acute myocardial infarction 

Patient age, sex, ethnicity, payer type 

Cheung, 200232

Dissertation 

Examine the association between nurse staffing, time spent on direct and indirect care, and adverse events in five inpatient units in acute care hospital 

Single hospital study Nurse, 1,007 nurses Medical records, 

Adults, >17 years 

Unit acuity, skill mix, total numbenursing personneevents, and nurscharacteristics 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-13

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Langemo, 200233

Article 

Examine nursing quality outcome indicators (falls and pressure ulcers) after implementation of ANA Nursing Care Report Card 

North Dakota Nurses Association (NDNA) Research Council 

2003, Patient, 942 patients 

Administrative, Adults 

Not reported 

Seago, 200234

Article 

Examine the relationship between the presence of a bargaining unit for registered nurses and the acute myocardial infarction mortality rate for acute care hospitals in California 

California Office of Statewide Health Planning and Development (OSHPD) Hospital Disclosure Report database 

1991-1993, Hospital, 385 hospitals, 10.91%, Sampling bias assessed 

Medical records, Adults, Acute myocardial infarction 

Patient age, sex, severity of illnesshospital servicespatient volume, teaching status, number of MDs pacute myocardial infarction-related discharges, the cardiac technologindex, rural statuand the Hospital Service Area (HSwage index 

Needleman, 200229

Article based on the report 

Examine the relationship between the amount of care provided by nurses at the hospital and patients' outcomes 

American Hospital Association's Annual Survey of Hospitals 

1997, Hospital, 6,180,628 patients 

Administrative, Adults 

Rate of the outcome in the patient's diagnosrelated group, staof residence, agesex, primary heainsurer, emergenadmission, and comorbidities, hospital number beds, teaching status, state, and metropolitan or nmetropolitan location 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-14

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Kovner, 200235

Article 

Examine the association between nurse staffing and patient adverse events after controlling for hospital characteristics 

National Inpatient Sample, 80.5% 

1990-1996, Hospital, Random sample of 570 hospitals 

Administrative, Adults, >18 years 

Medicare Case MIndex, hospital besize, location, region, ownershipteaching status, HMO penetration 

Whitman, 200236

Article 

Determine the relationships between nursing staffing and specific nursesensitive outcomes (central line bloodassociated infection, pressure ulcer, fall, medication error, and restraint application duration rates) across specialty units

Secondary analysis of prospective, observational data from 10 adult acute care hospitals 

1999, Unit, 95 units Administrative, 

Adults 

Not reported 

Beckman, 200337

Dissertation 

Examine association between nurse management and patient outcomes 

Single hospital study, 100%, 17%

1999-2000, Patient, 429 patients, 74.36% 

Survey, Adults Patient age, sex, 

race 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-15

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Cho, 200338

Article 

Examine the effects of nurse staffing on adverse events, morbidity, mortality, and medical costs 

Hospital financial data, state Inpatient databases, 5%, 20% 

1996-1999, Patient, 124,204 patients 

Administrative, Adults, >18 years 

Patient age, sex, race, primary payer, DRG, number of diagnoses at admission, and type of admission (scheduled or unscheduled); hospital location, size, teaching status, ownershipclustering patientin hospitals (two levels model) 

Aiken, 200339Article 

Examine whether the proportion of hospital RNs educated at the baccalaureate level or higher is associated with risk-adjusted mortality and failure to rescue (deaths in surgical patients with serious complications

Pennsylvania Health Care Cost Containment Council, 36% 

1998-1999, Patient, 232,342 patients 

Administrative, Adults, >20 years, general surgical, orthopedic, vascular operation 

Patient age, sex, referral from another hospital, comorbidities; hospital size, teaching status, and technology; having a boardcertified surgeon 

Potter, 200340

Article 

Examine the association between nurse staffing and patient outcomes at the unit level in the acute care adjusting for patient acuity and proportion of floating nurses

Single hospital study, 100% 

1999-2001, Unit, 32 units 

Medical records, Adults 

Not reported 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-16

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Langemo, 200341

Article 

Examine the association between pressure ulcer incidence, staff mix, and nursing care hours 

Midwest Research Institute/National Database of Nursing Quality Indicators 

2003, Hospital, 942 hospitals 

Administrative Not reported 

Bolton, 200342

Article 

Examine the relationship between nurse staffing and patient perceptions of nursing care in a convenience sample of 40 California hospitals 

Hospitals participating in both the ongoing California Nursing Outcomes Coalition statewide database project and the statewide Patients' Evaluation of Performance in California project 

1998-2000, Hospital, 113 hospitals 

Administrative, Adults 

Not reported 

Needleman, 200343

Article 

Assess whether adverse outcomes in Medicare patients can be used as a surrogate for measures from all patients in quality of care research using administrative datasets 

National MedPAR discharge data for Medicare patients from 3,357 hospitals, state hospital staffing surveys or financial reports, American Hospital Association Annual Survey, present sample is 26% of all discharges in the U.S. in 1997 

1997-1998, Hospital, 6,180,628 patients 

Administrative, Adults 

Patient age, sex, primary DRG, health insuranceemergency admission, and comorbidities, hospital teachingmetropolitan statand bed size 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-17

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Vahey, 200444

Article 

Examine the effects of the nurse work environment and nurse burnout on patients' satisfaction with their nursing care 

40 units in 20 urban hospitals across the U.S. (sample from the study of quality of care in AIDS patients) 

1991, Patient, 722 patients, 13.99% 

Survey, Adults, AIDS 

Patient age, sex, and race, severitof illness, nurse sex, race, age, experience in nursing and in thunit; clustering nurses and patiewithin hospitals 

Sochalski, 200445

Article 

Examine the effects of nurse staffing and process of nursing care indicators on assessments of the quality of nursing care 

Hospitals where responding licensed RNs in Pennsylvania worked in 1999 

1999, Nurse, 8,500 nurses, 7.70%, Random sample, Bias assessed 

Survey Nurses clustered 

within hospitals, nurses perceived quality of care anpatient safety 

Van Doren, 200446

Article 

Examine the relationships between congestive heart failure patient outcomes and RN hours 

Single hospital study, 75% 

1998, 0.57%, Random of 175 patients 

Medical records, Adults, Heart failure 

Not reported 

Boyle, 200447Article 

Examine the association between nurse autonomy and collaboration and patient outcomes 

Single hospital study, 100% 

2001, Unit, 11,496 patients 

Survey, Adults Case mix index 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-18

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Donaldson, 20059

Report 

Test associations between daily nurse staffing in adult medical-surgical units and hospital acquired pressure ulcers, patient falls 

25 acute care, notfor-profit California hospitals, the part of the California Nursing Outcomes Coalition (CalNOC) 

2002-2003, Unit, 77 units 

Administrative, Adults 

Hospital rural/urbdesignation; ownership; no. licensed acute cabeds; average dacensus 

Tschannen, 200548

Dissertation 

Examine association between patient length of stay and nurse staffing and nurse-physician collaboration 

Single hospital study 2005, Patient, 406 

patients, 23.65% 

Medical records Patient DRG, age

gender, acuity scores, unit of admission, admission type asource, and comorbidities; nursing characteristics 

Houser, 200549

Dissertation 

Examine the association between nurse staffing and nurse-sensitive patient outcomes 

American Hospital Association Annual Survey (685 hospitals); 20% random sample of U.S. hospitals 

2001, Patient, 7,452,727 patients, 24.37%, Random sample 

Administrative, Adults 

Patient age, racesex, health insurance, comorbidity; hospital size, teaching status, location, ownersh
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-19

Author, Year, 

Publication Type 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis, 

Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Estabrooks, 200550

Article 

Examine the association between nurse education and skill mix, and 30-day mortality after adjusting for institutional factors and individual patients characteristic

International Hospital Outcome Study, 8.2% 

1998-1999, Patient, 18,142 patients 

Administrative, Adults, >18 years, acute myocardial infarction, stroke, congestive heart failure, chronic obstructive pulmonary disease, pneumonia 

Comorbidity scores, patient agand gender 

Halm, 200551

Article 

Examine the association between nurse-to-patient ratio and patient mortality, failure to rescue, emotional exhaustion and job satisfaction of nurse

Single hospital study, 100%, 0% 

2002, Patient, 6,216 patients, 56.42% 

Administrative, Adults, General, orthopedic, and vascular surgery 

Patients demographics, emergency department admission, comorbidity and complications 

Studies that assessed temporality in association between patient outcomes and nurse staffing patterns 

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Wan, 198752

Article, Retrospective 

Examine association between nurse staffing and patient adverse events in 45 community acute care hospitals across the U.S. 

Health area resources file, hospital survey 

1985, Hospital, 60 hospitals, 25.0% 

Administrative, Adults 

Severity of adverevent 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-20

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Flood, 198853Article, Prospective 

Examine association between nurse shortage and length of stay 

Single hospital study 1986, Patient, 497 

patients 

Medical records, Adults 

Not reported, subgroup analysby patient acuity 

Shortell, 199415

Article, Retrospective 

Examine staffing factors associated with risk-adjusted mortality, riskadjusted average length of stay, and nurse turnover 

1,691 non federal U.S. hospitals with >200 beds, 53%, 12% 

1988-1990, Unit, 17,440 patients, Random sample, bias assessed 

Administrative, Adults, >16 years 

Patient demographic characteristics, primary DRG and comorbidity (APACHE III scores) 

Shortell, 198854

Article, Retrospective 

Examine the association between the proportion of RNs on mortality rates in Medicare patients for 16 selected clinical conditions 

981 hospitals in 45 states, 46% 

1983-1984, Hospital, 214,839 patients, Sample bias Assessed 

Administrative, Adults, >65 years, >16 years, Selected clinical conditions, Medicare 

Patient age, sex, comorbidity, lengof stay, Medicare case mix; hospitasize, location, ownership 

Thorson, 199555

Dissertation, Retrospective 

Relationship between the available hours of RN care and patient outcomes, defined as discharge disposition and death 

Acute care short term hospitals in North Carolina, 19% 

1988-1993, Patient, 146,000 patients 

Medical records, Adults 

Patient age, gender, length of stay, major diagnostic category; hospitaownership, occupancy, size, location, teaching status, and technology 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-21

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

ANA, 199756

Report, Retrospective 

Examine association between nurse staffing and patient outcomes 

502 hospitals from California, Massachusetts, and New York 

1992-1994, Hospital, 502 hospitals, Sample bias assessed 

Administrative Nursing Intensity 

weights, hospital teaching status, location 

Archibald, 199757

Article, Retrospective 

Examine the effect of fluctuations in cardiac intensive care unit nurse staffing levels and patient census on cardiac care unit nosocomial infection rate 

Single hospital study 1994-1995, Patient, 

782 patients 

Medical records, Children 

Not reported 

Blegen, 199858

Article, Retrospective 

Describe, at the level of the nursing care unit, the relationships among total hours of nursing care, registered nurse skill mix, and adverse patient outcomes 

Consortium of hospitals members of Information and Quality Healthcare 

1993, Unit, 42 units Administrative, 

Adults 

Patient severity, nursing acuity system 

Blegen, 199859

Article, Retrospective 

Determine the relationship between different levels of nurse staffing (total hours/patient day and proportion of RNs) and patient falls and cardiovascular arrests 

Consortium of hospitals members of Information and Quality Healthcare 

1993-1995, Unit, 39 Administrative, 

Adults 

Medicare case mscores 

Bond, 199960

Article, Retrospective 

Examine associations between nurse staffing levels and mortality rates in 3,763 U.S. hospitals 

American Hospital Association's Abridged Guide to the Health Care Field, 8.3%, 14.2% 

1992, Hospital, 4,822 hospitals, 21.96% 

Administrative, Adults, Medicare 

Severity of illness% of ICU days, annual number oemergency room visits/average dacensus, and % oMedicaid patients 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-22

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Pronovost, 199961

Article, Retrospective 

Determine whether nurse to patient ratio in ICUs is associated with length of stay in abdominal aortic surgery patients who typically receive care in an ICU 

Maryland Health Services Cost Review Commission 

1994-1996, Patient, 2,996 patients, 0.30%, Sample bias assessed 

Medical records, Adults, >30 years, Abdominal aortic surgery 

Patients’ age, serace, nature of admission, type oaneurism, comorbidity, surgeon and hospital volumes 

Robertson, 199962

Article, Retrospective 

Examine the association between staffing intensity, skill mix, and mortality in patients with chronic obstructive lung disease 

American Hospital Association 

1989-1991, Hospital, 5,708 patients, Sample bias assessed 

Administrative, Adults, chronic obstructive pulmonary disease, Medicare 

Severity of illness and comorbidity (Medicare case mindex); hospital’s financial status, ownership, technology indexsize, staffing variables (nursingphysicians, technologists) 

Lichtig, 199963

Article, Retrospective 

Examine the relationships between patient outcome indicators and nurse staffing 

Hospital cost reports from New York and California 

1992,1994, Hospital, 691, 33.00% 

Administrative, Adults 

Nursing intensity weights based on patients’ characteristics, teaching status, and location 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-23

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Amaravadi, 200064

Article, Retrospective 

Determine if a nighttime nurse-to-patient ratio in the intensive care unit is associated with clinical and economic outcomes following esophageal resection 

Maryland Health Service Cost Review Commission 

1994-1996, Patient, 366 patients in 32 hospitals 

Adults, >18 years, Esophageal resection 

Patient age, sex, nature of admission, type ooperation, comorbid disease and hospital and surgeon volume; clustering of outcomes within hospital 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-24

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

ANA, 200065

Report, Retrospective 

Examine the association between nurse staffing and patient outcomes in the inpatient hospital settings 

HCFA 1992-1996, Hospital, 

14,251,921 patients, 9.32% 

Administrative, Adults, >75 years, Medicare 

Large urban location (Y/N); rulocation (Y/N); teaching status; nursing intensity weights 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-25

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Unruh, 200066

Dissertation, Retrospective 

Examine the association between nurse staffing and quality of patient care 

211 hospitals yearly, 1,477 during 7 years acute care hospitals in Pennsylvania, State Department of health with unique information on nurse staffing and patients discharge, 0.4% 

1991-1997, Patient, 83,924 patients 

Administrative Patient age, 

gender, race, acu(Mediqual, hospitlocation, size, ratof board certified physicians/ adjusted patients days of care; hospital restructuring including capacitutilization, mergestatus, ownershipnumber of administrators/ adjusted patients days of care 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-26

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Silber, 200067

Article, Retrospective 

Examine the association between nurse staffing and patient outcomes in surgical Medicare patients 

Medicare patients in 245 hospitals 

1991-1994, Hospital, 217,440 patients 

Administrative, Adults, >65 years, Medicare 

27 patient characteristics including age, serace, diagnosis acomorbidities, hospital size, location, technology, % of certified physiciaand anesthesiologists 

Whitman, 200168

Article, Prospective 

Examine the relationship between restraint use and staffing 

A secondary analysis of prospective, observational data from 10 adult acute care hospitals with bed capacity ranging from 59–861 beds, in an integrated healthcare system in the east, 50% 

1999, Unit, 370,574 patients 

Medical records, Adults 

Not reported; however, the authors obtained hierarchical longitudinal lineamodels (random coefficient regression mode
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-27

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Ritter-Teitel, 200169

Dissertation, Retrospective 

Examine the association between nurse staffing and patient outcomes 

Sample from HRIO study (“Hospital Restructuring’s Impact on Outcomes”) of 42 teaching hospitals, 100% 

1997-1998, Unit, 56, Sample bias assessed 

Administrative Age, primary 

diagnosis and case-mix index, random effects ohospitals 

Dimick, 200170

Article, Retrospective 

Determine if nurse-topatient ratio in the intensive care unit at night is associated with differences in clinical and economic outcomes after hepatectomy 

Maryland Health Services Cost Review Commission 

1994-1998, Patient, 569 patients, 2.28% 

Administrative, Adults, >18 years, hepatic resection 

Patient age, sex, nature of admission, type ooperation, comorbidity; hospital and surgeon volumes 

Sovie, 200171Article, Retrospective 

Examine the association between nurse staffing and patient outcomes 

29 university teaching hospitals based on the MECON-PEERx Operations Benchmarking Database Reports, 100% 

Hospital, 29 hospitals Administrative, 

Adults 

Year of submissiand type of unit 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-28

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Pronovost, 200172

Article, Retrospective 

Evaluate the association between nurse-to-patient ratio in the ICU and risk for medical and surgical complications after abdominal aortic surgery 

Health Services Cost Review Commission 

1994-1996, Patient, 2,615 patients, 0.34%, Sampling bias assessed 

Administrative, Adults, >30 years, Abdominal aortic surgery 

Number of hospitbeds and the volume of aortic surgery performeduring the study period by each hospital and each surgeon in the database; patienage (in years), serace, and comorbidities 

Blegen, 200173

Article, Retrospective 

Describe the relationships between the quality of patient care and the education and experience of the nurses providing that care 

 1993-1995, Unit, 81 

units 

Administrative, Adults 

Hospital Medicarcase mix index 

Aiken, 200274Article, Retrospective 

Determine the association between the patient-to-nurse ratio and patient mortality, failure to rescue (deaths following complications) among surgical patients, and factors related to nurse retention 

American Hospital Association (AHA) annual survey and 1999 Pennsylvania Department of Health Hospital Survey, 36.2% 

1998-1999, Patient, 232,342 patients 

Administrative, Adults, >20 years, General surgical, orthopedic, or vascular operation 

Patient age, sex, surgery types, comorbidity; hospital size, teaching status, and technology; nurse’s sex, yearof experience in nursing, educatio
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-29

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Dang, 200275

Article, Retrospective 

Examine the association between ICU nurse staffing and the likelihood of complications for patients undergoing abdominal aortic surgery 

Maryland Health Services Cost Review Commission 

1994-1996, Patient, 2,987 patients, 12.76% 

Administrative, Adults, 30, Abdominal aortic surgery 

Patient age, sex, race, comorbidityseverity of illnessnature of admission, hospiand ICU bed sizehospital and surgeon volume, type of unit, fulltime medical director and nursmanager, RN attendance at darounds, use of clinical pathways 

Tourangeau, 200276

Article, Retrospective 

Examine the association between nursing-related hospital variables and 30-day mortality rates for hospitalized patients 

Ontario Hospital Reporting system, 13.3% 

1998-1999, Hospital, 46,941 hospitals 

Administrative, Adults, >21 years, Acute myocardial infarction, stroke, pneumonia, or septicemia 

Patient age, sex, comorbidities, socio-economic status; hospital teaching status, and location 

Barkell, 200277Article, Retrospective 

Examine the effects of a change in the staffing model on length of stay, variable cost, patient satisfaction, incidence of urinary tract infection and pneumonia, and pain management in bowel resection patients 

Single hospital study: 508-bed full service community-based teaching hospital 

1999-2000, Patient, 96 patients 

Medical records, Adults, >18 years, Postoperative bowel procedure 

Not reported 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-30

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Stegenga, 200278

Article, Retrospective 

Examine the relationship between nurse staffing levels and the rate of nosocomial viral gastrointestinal infections (NVGIs) in a general pediatrics population 

Single hospital study, general pediatrics ward at The Hospital for Sick Children in Toronto, Ontario, Canada, a 320-bed, tertiary-care pediatric institution 

1997-1999, Patient, 2,929 patients 

Medical records, Children 

Not reported 

Alonso-Echanove, 200379

Article, Prospective 

Examine the association between nurse staffing and bloodstream infections in intensive care units 

Part of Detailed ICU Surveillance Component (DISC) Study (prospective, multi center cohort study). 6 hospitals, 8 ICU units 

1997-1999, Patient, 8,593 patients 

Medical records, Adults, Central venous catheter 

Patient age, gender, weight, height, diagnosiscomorbidity 

Mark, 200380Article, Prospective 

Examine the association between nurse practice and patient outcomes (patient satisfaction, rate of reported medication errors, and falls) 

68 randomly selected non-federal, no psychiatric, not-forprofit, accredited acute care hospitals with more than 150 beds in 10 southeastern states, 34% 

1995-2000, Patient, 1,326 patients, Random sampling 

Survey, Adults Case mix index, 

hospital size, technology 

Unruh, 200381

Article, Retrospective 

Examine the changes in licensed nursing staff in Pennsylvania hospitals from 1991 to 1997, and to assess the relationship of licensed nursing staff with patient adverse events in hospitals 

Pennsylvania Department of Health 

1991-1997, Hospital, 83,924 patients, Sampling bias assessed 

Administrative, Adults 

Patient age, gender, race, ethnic status, and level of severity, ownership statushospital mergersnumber of boardcertified physiciaand capacity utilization 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-31

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Simmonds, 200382

Dissertation, Retrospective 

Examine the association between nurse staffing and colonization vancomycin-resistant enterococci colonization in chronic dialysis patients 

Single hospital study 2000-2002, Patient, 

1,084 patients, 26.11% 

Medical records, Chronic renal diseases that requires hemodialysis 

Nursing workload index, patient ageand acuity 

Tallier, 200383

Dissertation, Retrospective 

Examine the relationship between nurse staffing and patient outcomes 

Single hospital study including 7 nursing units with patients at high risk of acquiring events 

2000-2001, Patient, 2,897 patients 

Medical records, Adults, >18 years 

Not reported 

Berney, 200384

Dissertation, Retrospective 

Examine association between nurse overtime and patient mortality and 6 nursesensitive patient outcomes 

Hospitals in New York state completed Institutional Cost Reports, 41.2% 

1995-2000, Hospital, 10,210,556 patients 

Administrative, Adults 

Patient age's, racprimary payer, emergency admission, primadiagnosis and comorbidities (DRGs), hospital variables (locatioteaching status, unionization, sizemargins), clusterpatient within hospitals 

Zidek, 200385

Dissertation, Retrospective 

Examine the association between changes in nurse staffing determined based on a new patient classification system and patient outcomes 

Single hospital study: rural acute tertiary care facility 

1999-2001, Patient, 5,067 patients 

Medical records Patient age, sex, 

primary diagnosisacuity; unit size, organizational leadership 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-32

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Hope, 200386

Dissertation, Retrospective 

Examine the relationship between nursing workload and nosocomial infections in acute care hospital 

Single hospital study 1998-2000, Patient, 

39,481 patients, 37.23% 

Administrative Patient age, 

gender, and primary diagnosisseverity of illnessward type, nationrisk of infection; resource intensity weight 

Cimiotti, 200487

Dissertation, Prospective 

Examined the association between nurse staffing, healthcare-associated infection, and length of stay among infants in the neonatal ICU 

Two Level lII-IY neonatal ICU units in New York City participated in a clinical trial to test hygiene regimens 

2001-2003, Patient, 2,675 patients 

Medical records, Children 

Patient acuity based on DRG anursing Intensity weight; use of surgery and invasive medical devices, birth weight, differencein practices in study's sites 

Person, 200488

Article, Retrospective 

Assess the association of nurse staffing with inhospital mortality for patients with acute myocardial infarction 

Cooperative Cardiovascular Project (CCP) dataset, 39.2% 

1994-1995, Patient, 234,754 patients, 49.33%, Random 

Administrative, Adults, >65 years, Acute myocardial infarction, Medicare 

Patient age, gender, ethnicityand severity of illness, hospital volume, rural/urblocation, and teaching status 

Mark, 200489Article, Retrospective 

Examine the effects of change in registered nurse staffing on change in quality of care 

American Hospital Association 

1990-1995, Hospital, 422 patients, Random 

Administrative Patient’s age, 

gender, admissiotype, admission source, and type treatment (medicvs. surgical); hospital size, casmix, and the availability of high technology servic
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-33

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Mark, 200590Article, Retrospective 

Examine structural differences in the relationship between nurse staffing and quality of care in different levels of managed care penetration 

Longitudinal cohort of the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS); a 20% probability sample of U.S. community hospitals from 11 states, 0.122%, 3.26% 

1990-1995, Hospital, 422 hospitals, Random sampling, Sampling bias assessed 

Administrative Patient’s age, 

gender, admissiotype, admission source, and type treatment (medicvs. surgical), hospital size, casmix, and the availability of high technology servic

Stratton, 200591

Dissertation, Retrospective 

Relationships between pediatric nurse staffing and 5 indicators of quality care (measured as adverse occurrence rates) in 17 medical/surgical, 5 oncology, and 12 intensive care units 

Seven, academic, not-for-profit children's hospitals from the National Association of Children's Hospitals and Related Institutions (NACHRI), 100%, 0%, Different % HMO penetration 

2002, Unit, 6,011 patients 

Administrative, Children, >1year 

Patient age, sex, race, socio economic status, unit/hospital typesize, and occupancy, transfers, technological complexity, organizational factors including care model, lengof shift, flexible staffing, selfgovernance, paid continuing nursineducation, relationships with physicians 
Table G1. Design, external, and internal validity of the studies that examined the associations between nurse staffing and strat

outcomes (continued) 

G-34

Author, Year, 

Publication Type, 

Data Collection 

Aim of the Study Hospital Eligibility 

Criteria, Database, 

% of Teaching 

Hospitals, % of 

Hospitals for Profit, 

% of HMO 

Time, Analytic 

Units, Sample Size, 

% Excluded from 

Analysis Sampling, 

Assessment of 

Sampling Bias 

Patient Eligibility 

Criteria: 

Database, 

Population, Age, 

Diagnosis, 

Medical Care 

Adjustment fo

Confounding 

Factors 

Elting, 200592Article, Retrospective 

Examine the association between nurse staffing (RN/patient ratio) and patient mortality and complication after cystectomy 

Texas Hospital Discharge Public Use Data 

1999-2001, Hospital, 1,302 hospitals 

Administrative, Adults, Bladder carcinoma (ICD-9 codes 188.0-188.9 and 236.7) after total cystectomy 

Age, gender, racethnicity, comorbidities, andistance from the closest highvolume hospital 

Seago, 200693

Article, Retrospective 

Examine the association between nurse staffing and patient outcomes for 3 adult medicalsurgical nursing units in one university teaching hospital across 4 years (16 fiscal quarters) 

Single hospital study, 100% 

1999-2002, Patient, 1,012 patients 

Administrative, Adults 

Case-mix 

CNS = Central Nervous System; CPR = Cardio-pulmonary Resuscitation; DRG = Diagnosis Related Group; HMO = Health Maintenance Intensive Care Unit; MedPAR = Medicare Provider Analysis Review; RN = Registered Nurse 
G-35

Table G2. Calculated change in hospital-related mortality corresponding to an increase by one patient/RN, LPN/shift (results fr

Definition of Nurse 

to Patient Ratio Source to Measure Ratio Author Increase by One Patient/RN/Shift Increase by 

Death 

Rate 

p Value RR p Value Death 

Rate 

p 

RN/patient day Survey of RNs Aiken5 1.83 NS Patients/RN/shift Survey of RNs Aiken39 0.11 <0.05 1.06 <0.05 Patients/RN/shift Survey of RNs Aiken74 1.08 <0.05 Patients/RN/shift Survey of ICU directors Amaravadi64 4.7 NS 1.2 NS Nurse/patient day AHA and HCFA data bases Bond60 Patients/RN/shift Survey of ICU directors Dimick70 NS RN, LPN FTE/ number of occupied beds 

Hospital Cost Report Information System, Provider of Services files, and the American Hospital Association Survey 

Elting92 0.42 NS 1.18 <0.05 1.12 <

Patients/RN/shift Survey of staff nurses; daily 

staffing plans and unit census records 

Halm51 0.99 NS 

RN, LPN FTE/1,000 patient days 

Area Resource Files, American Hospital Association Annual Survey, CMS Wage Rate File, CMS Online Survey 

Mark90 1.001 NS 

RN, LPN FTE/1,000 patient days 

Area Resource Files, American Hospital Association Annual Survey, CMS Wage Rate File, CMS Online Survey 

Mark89 1 NS 

RN, LPN FTE/ patient day 

CCP and AHA datasets Person88 1.41 NS 1.1 <0.05 

Patients/RN/shift Survey of ICU directors Pronovost72 0.5 NS Patients/RN/shift Survey of ICU directors Pronovost61 1.9 <0.05 RN FTE/patient day AHA database Robertson62 1.02 <0.05 Patients/RN/shift Hospital administrative databases; 

survey of nursing directors in each unit 

Shortell94 NS 

Patients/RN/shift AHA Annual Surveys for 1991–

1993, and the Pennsylvania Health Care Cost Containment Council Data Base for years 1991–1994 

Silber67 1.05 <0.05 

RN, LPN FTE/ 1,000 patient days 

State Department of Health, AHA database 

Unruh66 -1.4 <0.05 0.14 <

LPN = Licensed Practical Nurse; NS = Not Significant; RN = Registered Nurse; RR = Relative Risk 
G-36

Table G3. Evidence of the association between nurse staffing and mortality 

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Pronovost, 200172

The Uniform Health Discharge Data Set In-hospital mortality from all causes

Survey to the ICU directors, An average ICU nurse-to-patient ratio during the day and evening

Mean age 68 years, 89% whites, 66% males, 11-13% emergency admissions, Units: ICU Patients: surgical 

More nurses: RN/patient 1:1 or 1:2 (7 

hospitals) Fewer nurses: RN/patient 1:3 or 1:4 (31 hospitals)

C7 8 

Pronovost, 199961

The Uniform Hospital Health Discharge Data Set In-hospital mortality

Survey of intensive care unit directors, An average nurse to patient ratio in day and in evening; decreased nurse to patient ratio in evening

Mean age 68 years, 89% whites, 66% males, 11-13% emergency admissions, Units: ICU Patients: surgical

Decreased nurse to patient ratio in evening (7 hospitals) Nurse to patient ratio >1:2 in evening (31 hospitals)

R1R

Amaravadi, 200064

The Uniform Health Discharge Data Set In-hospital mortality

Survey of ICU directors, An average nurse-topatient ratio during the day and at night

32 hospitals Units: ICU Patients: surgical Age % Whites Males  63 77 70  60 83 79  60 83 79  63 77 70 

Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 

R0RC51

Dimick, 200170

The Uniform Health Discharge Data Se In-hospital mortality

Survey of ICU directors, An average nurse-topatient ratio in the ICU during the day and evening and at night 

Units: ICU Patients: surgical 

Age % Whites Males  56 82 51  57 67 55 

More nurses: RN/patient 1:1-1:2 (8 hospitals) Fewer nurses: RN/patient 1:3-1:4 (25 hospitals) 

RR0
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-37

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Blegen, 199859

Hospital records Death rates per 1,000 patient days. All deaths, whether expected, unexpected, procedurerelated, or do not resuscitate, were included 

A record of hours worked for each individual employee was completed by the staffing clerk and approved by the employee and nurse manager before being entered into the computerized payroll database. The hours of care per patient day from all nursing personnel: Hours of direct patient care by RNs, LPNs, and nursing assistants each month divided by the patient days of care on the unit for the month. The hours of direct patient care from RNs divided by patient days excluding hours for non patient care (meetings, vacation, sick leave, and holidays)

Single hospital study, 42 units 

Increase by 1% in proportion of RN nurses Proportion of RN >87.5% Increase by 1 hour in total nursing hours Mean nurse staffing Total nursing hours 10.7, RN hours 7.7 

Cp-00D0

Aiken, 19995

Medical charts of consecutively admitted patients Mortality within 30 days from admission 

Survey of all registered and licensed practical nurses who worked at least 16 hours per week The average number of nurses per patient day (self-reported) Nurse autonomy: nurse control over the practice environment across hospital units (Clinical Environment Index)

Hospitals Units 

 20 40  5 8  5 8  5 8  20 40 

Age % Whites Males  37 47 88  39 29 77  37 45 87

Increase by 1 RN/patient Dedicated AIDS units AIDS hospital-scattered bed units Conventional scattered bed units Nurse control over practice setting Increase by 1 RN/patient Dedicated AIDS units AIDS hospital-scattered bed units 

R0101 1
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-38

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Aiken, 200339Discharge abstracts Deaths within 30 days of hospital admission 

Surveys of hospital nurses (the Pennsylvania Board of Nursing ) The mean number of patients assigned to all staff nurses who reported caring for at least 1 but fewer than 20 patients on the last shift they worked; highest credential in nursing: a hospital school diploma, an associate degree, a bachelor's degree, a master's degree, or another degree; the mean number of years of experience working as an RN for nurses from each hospital

Units: ICU Patients: surgical 

Hospitals 53 34 168 19 26 36 

Increase by 1 year in nurse experience Increase in workload of 1 patient 10% increase in nurses with BSN degree 40% of hospital workforce with BSN or higher, 4 patients/nurse 20% of hospital workforce with BSN or higher, 4 patients/nurse 60% of hospital workforce with BSN or higher, 6 patients/nurse 40% of hospital workforce with BSN or higher, 6 patients/nurse 20% of hospital workforce with BSN or higher, 6 patients/nurse 60% of hospital workforce with BSN or higher, 4 patients/nurse 20-29% of hospital workforce with BSN or higher <20% of hospital workforce with BSN or higher 20% of hospital workforce with BSN or higher, 8 patients/nurse >50% of hospital workforce with BSN or higher 40-49% of hospital workforce with BSN or higher 30-39% of hospital workforce with BSN or higher 40% of hospital workforce with BSN or higher 60% of hospital workforce with BSN or higher, 8 patients/day 

R1 10M11112122211121
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-39

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Aiken, 200274Hospital data (Health Care Cost Containment Council Death within 30 days of hospital admission

Survey of 50% random sample of registered nurses who were on the Pennsylvania Board of Nursing rolls; Burnout: the Emotional Exhaustion scale of the Maslach Burnout Inventory Scale Nurse’ job satisfaction: 4-point scale from very dissatisfied to very satisfied

Patients Surgical Hospitals 168 % males 44 Mean age 44 years

Increase by 6 patients/nurse Increase by 1 patient/nurse Increase by 8 patients/nurse Increase by 4 patients/nurse 

R1111

Person, 200488

Medicare database In-hospital mortality and within 30 days of hospital admission

AHA Survey The ratio of full-time equivalent RNs to average daily census (ADC) categorized by their respective quartiles of nurse to ADC ratio; the ratio of full-time equivalent licensed practical nurses (LPNs) to ADC categorized by their respective quartiles of nurse to ADC ratio; ratio of RNs to LPNs

Hospitals 4,401 Age % Whites Males 77 90 50 

Skill Mix: % of RN 1 quartile of LPN staffing 1 quartile of LPN staffing 1 quartile of RN staffing 1 quartile of RN staffing 2 quartiles of LPN staffing 2 quartiles of LPN staffing 2 quartiles of RN staffing 2 quartiles of RN staffing 3 quartiles of LPN staffing 3 quartiles of LPN staffing 3 quartiles of RN staffing 3 quartiles of RN staffing 4 quartiles of LPN staffing 4 quartiles of LPN staffing 4 quartiles of RN staffing 4 quartiles of RN staffing 1 quartile of LPN staffing 1 quartile of RN staffing 2 quartiles of LPN staffing 2 quartiles of RN staffing 3 quartiles of LPN staffing 3 quartiles of RN staffing 4 quartiles of LPN staffing 4 quartiles of RN staffing 

M2222122122121121R1 1 1 01010
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-40

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Berney, 200384

The New York Statewide Planning and Research Cooperative System In-hospital mortality

The New York State Institutional Cost Reports RN total hours in inpatient cost units/patient-days in units adjusted for nursing acuity, RN acute hours/ (RN+LPN acute hours); % of total RN hours paid as overtime hours; Union: RN are represented by unions as reported in ICR

Hospitals: 161 Surgical Medical Surgical Medical Medical Medical Surgical Surgical 

1% increase in RN overtime work 1 hour increase in RN hours/acute patient day 1% increase in RN hours/total licensed hours 1st (low overtime) quartile 4th (high overtime) quartile 1% increase in RN overtime work 1st (low overtime) quartile 4th (high overtime) quartile 

R

Needleman, 200128

799 hospitals (11 states, all-patients + Medicare patients) – hospital level analysis; 256 California hospitals (part of the 11 state sample) – unit level analysis; National sample of 3,357 hospitals (Medicare patients) –hospital level analysis; in-hospital mortality

State hospital financial reports or hospital staffing surveys; the American Hospital Association Annual Survey of hospitals (2,080 hours * each FTE category) + (1,040 hours * number of part-time employees). Total nursing hours/patient-day NIW adjusted; RNs, clinical nurse specialists, general duty nurses, nurse practitioner excluding nursing directors, managers, administrators, supervisors, instructors, anesthetists, and midwifes. RN hours/patient day NIW adjusted. Licensed hours/patient-day NIW adjusted LPN/LVN, excluding the director of nursing. LPN/LVN hours/patientday NIW adjusted Nursing aides, orderlies and attendants, excluding 

4,156 hospitals 

Increase by 1 hour of RN hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in LPN hours in surgical patients Increase by 1 hour in aide hours in medical patients Increase by 1 hour in aide hours in surgical patients Increase by 1 hour in total nursing hours in medical patients Increase by 1 hour in total nursing hours in surgical patients Increase by 1% in RN/total nursing hours in medical patients Increase by 1% in RN/total nursing hours in surgical patients Increase by 1 hour in licensed hours/patient-day in medical patients Increase by 1% of RN hours/total licensed hours per patient day in medical patients Increase by 1 hour in licensed hours/patient-day in surgical patients Increase by 1% in RN hours/total 

R11111111001010
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-41

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

ward clerks. Total aide hours/patient day NIW adjusted RN hours per day/total hours per day; RN hours/licensed hours = RN hours per day/licensed hours per day (RN + LPN)

licensed hours per patient-day in surgical patients Increase by 1 hour in RN hours in medical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in licensed hours in medical patients Increase by 1% in RN hours/total licensed hours in medical patients Increase in total nurse hours in medical patients Increase by 1% in RN hours/total nurse hours in medical patients Increase by 1 hour in aide hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN in surgical patients Increase by 1 hour in licensed hours in surgical patients Increase by 1% in RN hours/licensed hours in surgical patients Increase by 1 hour in aide hours in surgical patients Increase by 1 hour in total nursing hours Increase by 1% in RN hours/total nursing hours Increase by 1 hour in RN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in aide hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing 

111010101101110010
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-42

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

hours in medical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of licensed nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1% of RN hours/total licensed hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in aide hours/patient day in medical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, unit level analysis, California hospitals. Increase by 1% in RN hours/total nursing hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of total licensed hours in medical patients, unit level analysis, California hospitals Increase by 1% of RN hours/licensed hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in 

000001000011
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-43

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

surgical patients, hospital level analysis, California hospitals Increase by 1 hour in aide hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in aide hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, unit level analysis, California hospitals Increase by 1% in RN hours/total nursing hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, unit level analysis, California hospitals Increase by 1% in RN hours/ licensed hours in surgical patients, unit level analysis, California hospitals 

111101101110
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-44

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Seago, 200234

The California Office of Statewide Health Planning and Development (OSHPD) Hospital Disclosure Report database; the California Vital Statistics data set from the California Department of Human Services (DHS), mortality within 30 days of hospital admission

The California Office of Statewide Health Planning and Development (OSHPD) Hospital Disclosure Report database; the National Labor Relations Board, number of RN hours/acute myocardial infarction (AMI) related discharge; the presence of a bargaining unit for registered nurses

Hospitals 106 238 343 343 343 343

Union hospitals Not union hospitals Union vs. not union 5 RN hour/AMI discharge 1 RN hour/AMI discharge 8 RN hour/AMI discharge 

M11R0000

Estabrooks, 200550

Hospital Inpatient Database; Alberta Health Care Insurance Plan Registry (AHCIPR) was linked to identify persons who died within 30 days of admission Mortality within 30 days of hospital admission

Survey of RN (Alberta Association of Registered Nurses registry) working in acute care hospitals Self-reported % of RNs to total nursing staff, Self reported highest RN credential: Diploma; Baccalaureate; Masters; Otherwise; % of BSN in hospital level derived from the question regarding the highest degree; Nurse job satisfaction: responses for the question: "On the whole, how satisfied are you with your job?" 1. Very dissatisfied 2. A little dissatisfied 3. Moderately satisfied 4. Very satisfied) Nurse autonomy: freedom to make important patient care and work decisions

49 hospitals 

Hospitals with lower proportion of temporary nurses Hospitals with higher proportion of nurses with BSN Hospitals with lower proportion of nurses with BSN Hospitals with higher proportion of temporary nurses Hospitals with lower proportion of RN Hospitals with lower proportion of RN Hospitals with higher proportion of RN Hospitals with lower proportion of temporary nurses Hospitals with higher proportion of temporary nurses Hospitals with higher proportion of RN Hospitals with lower proportion of nurses with BSN Hospitals with higher proportion of nurses with BSN 

R1 01 11 1 01 101 0
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-45

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Cho, 200338

Hospital Financial Data, in hospital mortality 

The State Inpatient Databases, the total productive hours worked by all nursing personnel per patient day, the total productive hours by registered nurses per patient day

Mean age 68 years % Whites 79.3 Males 48.9% Hospitals 12 79 48 48 

Large non-profit teaching hospitals, 76.5% RN Medium, non-profit, non-teaching, non-rural, 68.1% RN Large, non-profit, non-teaching, nonrural 72.4% RN Medium, investor-owned non-teaching non-rural hospitals, 72.7% RN 

D5444

Elting, 200592The Texas Hospital Discharge Public Use Data File linked to the 2000 U.S. Census, In-hospital mortality 

Hospital Cost Report Information System, Provider of Services files, and the American Hospital Association Survey, number of LPN/mean annual number of occupied bed days, number of RN/mean annual number of occupied bed days 

Patients Surgical 58 75 75 58 75 58 58 75 

Hospitals with few LPNs/occupied bed (median 0.7) Hospitals with many LPNs/occupied bed (median 3.1) Hospitals with many RNs/occupied bed (median 3.1) Hospitals with few RNs/occupied bed (median 1.4) Hospitals with many RNs/occupied bed (median 3.1) Hospitals with few RNs/occupied bed (median 1.4) Hospitals with few RNs/occupied bed (median 1.4) Hospitals with many RNs/occupied bed (median 3.1)

D230114 41
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-46

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Tourangeau, 200276

Discharge abstract database linked to the Ontario Registered Persons Database, mortality within 30 days of hospital admission

The Ontario Registered Nurse Survey of Hospital Characteristics and Ontario Hospital Reporting System Total nursing staff worked hours per Ontario case weight RN inpatient hours/other nursing staff earned hours (RN + LPN + aide); number of years employed in the current clinical unit

75 hospitals 

Increase by 1 year in nursing experience in teaching hospitals Increase by 10% proportion of RN/total nursing personnel Increase by 1 year in nursing experience in non-urban hospitals Increase by 1 year in experience 30 days mortality in teaching hospitals (85% RN) 30 days mortality in non-urban community hospitals (71% RN) 30 days mortality in urban community hospitals (79% RN) 

R0010111

Mark, 200590Centers for Medicare and Medicaid Services Minimum Cost and Capital File, CMS Provider of Services File, CMS Case Mix Index File, CMS Online Survey; Certification and Reporting system (OSCAR) files, and HCUP files In-hospital mortality 

The Area Resource Files, American Hospital Association Annual Survey, CMS Wage Rate File, CMS Online Survey Certification and Reporting system (OSCAR) files RN FTEs/1,000 in-patient days RN hours/patient * day = (FTE RN/1,000 patient * days * 37.5 * 48)/1,000; 37.5 hour work week on average 48 working weeks/year LPN FTEs/1,000 in-patient days LPN hours/patient * day = (FTE LPN /1,000 patient * days * 37.5 * 48)/1,000; 37.5 hour work week on average 48 working weeks/year

Hospitals 353 362 362 360 422 

Lowest quartile of HMO penetration Second quartile of HMO penetration Third quartile of HMO penetration Highest quartile of HMO penetration Increase by 1 RN FTE/1,000 patient days in hospitals with high HMO penetration Increase by 1 LPN FTE/1,000 patient days in hospitals with high HMO penetration Increase by 1 RN FTE/1,000 patient days in hospitals with low HMO penetration Increase by 1 LPN FTE/1,000 patient days in hospitals with low HMO penetration 25th Quartile of RN FTE/1,000 patient days with high HMO penetration 50th Quartile of RN FTE/1,000 patient days with high HMO penetration 75th Quartile of RN FTE/1,000 patient days with high HMO penetration 25th Quartile of RN FTE/1,000 patient days with low HMO penetration 50th Quartile of RN FTE/1,000 patient 

R0101011000100
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-47

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

days with high HMO penetration 75th Quartile of RN FTE/1,000 patient days with low HMO penetration Reference 1 patient/FTE nurse 

01

Robertson, 199962

HCFA database and Hospitals Information Reports, mortality within 30 days of hospital admission 

The American Hospital Association database, hospital average of RN FTE/100 adjusted submissions, hospital average of LPN FTE/100 adjusted submissions, hospital average of aide FTE/100 adjusted submissions

Hospitals 1,791 2,133 1,791 1,784 2,133 2,133 2,133 2,133 2,133 

Increase by 1 aide in aide/patient ratio in 1989 Increase by 1 aide in aide/patient ratio in 1991 Increase by 1 LPN in LPN/patient ratio in 1990 Increase by 1 LPN in LPN/patient ratio in 1989 Increase by 1 RN in RN/patient ratio in 1990 Increase by 1 RN in RN/patient ratio in 1989 Increase by 1 RN in RN/patient ratio in 1991 Increase by 1 UAP aide/patient ratio in 1990 Increase by 1 LPN in LPN/patient ratio in 1991 

R010000011
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-48

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Needleman, 200343

Hospital discharge data In-hospital mortality 

The American Hospital Association's Annual Survey of Hospitals, Total licensed hours (RN + LPN) / adjusted patient day; RN hours / adjusted patient day calculated from FTE in hospital (2,080 hours, 52 weeks at 40 hours/ week) LPN hours / adjusted patient day calculated from FTE in hospital (2,080 hours, 52 weeks at 40/week). UPA hours/adjusted patient day calculated from FTE in hospital (2,080 hours, 52 weeks at 40/week). the proportion of hours of care by RN/licensed nurses (RN + LPN)

799 hospitals Units Medical Surgical Medical Surgical Surgical Medical 

1% increase in RN hours/total licensed hours (RN + LPN) Increase in 1 hour of RN in surgical patients Increase in 1 hour of RN in medical patients 1% increase in proportion of RN/total nursing personnel Surgical patients in 799 hospitals (68% RN) Medical patients in 799 hospitals 68% RN) 

R01 1 0D13

Hartz, 198911

Hospital discharges data from The Health Care Financing Administration (HCFA) Mortality within 30 days of hospital admission 

The American Hospital Association's 1986 annual survey of hospitals Proportion of RN/total nursing personnel in hospital 

3,100 hospitals 

Hospitals with high proportion of RNs (upper quartile, 61%) Hospitals with high proportion of RNs (upper quartile, 61%) Hospitals with lower proportion of RNs (lower quartile, 59%) Hospitals with lower proportion of RNs (lower quartile, 59%) Hospitals with 59% of RNs Hospitals with 61% of RNs 

D111111
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-49

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Krakauer, 199212Medical records for all Medicare discharges, a random sample of 700 discharges were abstracted from the stratum that included hospitals with 700 or more discharges Mortality within 30 days of hospital admission

1986 American Hospital Association (AHA) survey, the proportion of registered nurses/total nursing personnel

84 hospitals Age 72.3 years, Whites 84%, Males 46% 

Lower quartile of % of RN, claims model Upper quartile of % RN, claims model Lower quartile of % RN, clinical model Upper quartile of % RN, clinical model 

D1111

Aiken, 19947

HCFA database Mortality within 30 days of hospital admission 

1988 AHA annual survey of hospitals % of RN/total nursing personnel 

79 hospitals 

Control hospitals, 70.8 % RN Control hospitals, 67.1% RN Magnet hospitals, 76% RN Control hospitals, 69.2% RN Control hospitals, 69% RN Control hospitals, 68.2% RN 

D000000

Shortell, 198854

MedPAR dataset of hospital discharges In-hospital mortality 

Database of the larger study of 8 multi-hospital systems Proportion of RN/total hospital employee 

981 hospitals 

Increase by 1% in RN/total hospital staff 

R0

Mark, 200489The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) In-hospital mortality 

American Hospital Association Annual Survey, Online Survey Certification and Reporting System [OSCAR] RN FTEs/1000 inpatient days RN hours/patient * day = (FTE RN/1,000 patient*days * 37.5 * 48)/1000 LPN FTEs/1,000 inpatient days LPN hours/patient * day = (FTE LPN/1000 patient * days * 37.5 * 48)/1,000 

Hospitals 357 361 361 366 373 357 357 357 357 422 422 422 

 RN hours/patient day Year 1993 6.05 Year 1994 6.30 Year 1992 5.76 Year 1992 5.65 Year 1990 5.44 75th quartile of RN FTE/1,000 patient days, 7.24 RN hours/patient day 50th quartile of RN FTE/1,000 patient days, 6.01 RN hours/patient day 25th quartile of RN FTE/1,000 patient days, 4.79 RN hours/patient day Year 1995 6.48 RN hours Increase by 1 RN FTE/patient day Increase by 1 LPN FTE/patient day Reference 1 RN and LPN FTE/patient day 

R101110000011
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-50

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Silber, 200067

Pennsylvania Medicare claims records; the Medicare Standard Analytic Files; random sample of 50% of Medicare patients who underwent general surgical or orthopedic procedures Mortality within 30 days of hospital admission 

The American Hospital Association Annual Surveys for 1991–1993, and the Pennsylvania Health Care Cost Containment Council Data Base for years 1991–1994 RN/bed ratio at hospital level

Hospitals Units 245 Surgical 258 Surgical 258 Surgical 258 Surgical 

Hospitals with lower RN/bed ratio Hospitals with higher RN/bed ratio Indirect patients, RN/patient ratio 1.38Directed patients, RN/patient ratio 1.4

R1 0D43

Hoover, 200023

The Health Care Financing Agency, HealthCareReportCards.com; MEDPAR database Mortality index = [(P -A) / P] * 100 where P = predicted mortality for each hospital according to patients characteristics, and A = actual mortality; In hospital mortality, and 6 months after submission mortality 

The AHA and HCFA databases RN/LPN ratio = total number RN FTE/LPN FTE reported by the hospital and RN/total nursing staff 

Hospitals Units 176 Medical Lowest quartile of RN proportion 

Highest quartile of RN proportion

R1 0

Aiken, 200127MedPar Mortality Data file for 1997 In hospital mortality 

American Hospital Association Annual survey RN FTE/daily average units census 

22 hospitals Nurse staffing – RN FTE/average 

daily census in units 

C-
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-51

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Bond, 199960

Hospital Medicare mortality rates from the Health Care Financing Administration In hospital mortality/1,000 admissions and number of deaths/hospital/year 

Data from the AHA and HCFA data bases were matched for 3,763 hospitals FTE RN/the mean number of occupied beds for each hospital FTE LPN/the mean number of occupied beds for each hospital

3,763 hospitals 

Increase by 1 RN/patient Increase by 1 LPN/patient 

C-0

Shortell, 199494

Hospitals discharge data In hospital mortality, standardized morality ratio (actual mortality in each unit/predicted mortality) 

Hospital administrative databases; survey of nursing directors in each unit An average RN/patient ratio in unit during the study period, number of nurses who left ICU in the year of the study/number of nurses employed that year

40 hospitals, 42 ICU units; Patients Medical Increase by 1 RN/patient ratio

R1

Boyle, 200447Patient discharges In-hospital mortality 

Nurses NWI-R survey (N=390) of nurses working >1 month in the unit NWI-R 57 items questionnaire to report nurse autonomy and collaboration; NWI-R 57 items questionnaire to report nurse manager support

Single hospitals study, 21 units 

Nurse manager support 

C

Halm, 200551

The hospital's data warehouse with patients discharges Mortality within 30 days of hospital admission 

Survey of 140 staff nurses (42% response rate); daily variable staffing plans and unit census records Average RN/patient ratio was calculated for each nursing unit across all 3 shifts for every week; % of RN with BSN and 

Single hospital study, age 55.6 years, 37.4% Males 22.7% emergency admission Patients Surgical

Increase by 1 unit in RN/patient ratio

R1
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-52

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

higher; years of total nursing experience; Burnout: Maslach Burnout Inventory Manual (max 6 scores) with 3 subscales of burnout: emotional exhaustion; depersonalization; personal accomplishment (feelings of competence and successful achievement in one's work). Overall rating on a simple 4-point Likert scale, ranging from 1 (very dissatisfied) to 4 (very satisfied) and the likelihood to leave current position within the next 12 months

Thorson, 199555

Administrative data on patient discharges from the North Carolina Medical Database Commission In-hospital mortality 

The archives of the NC Board of Nursing for 100 hospitals, an average of total nursing hours/patient day in surgical and medical units, an average RN hours/patient day in surgical and medical units 

100 hospitals 

Increase by 1 RN hour, crude odds of death Increase by 1 RN hour, adjusted for patient characteristics odds ratio Increase by 1 RN hour, adjusted for patient and hospital characteristics odds ratio 

R111

Unruh, 200066

State Health Care Cost Containment Council In-hospital mortality 

State Department of Health, American Hospital Association Total nurses FTE/1,000 APDC RN FTE/1,000 APDC LPN FTE/1,000 APDC UAP FTE/1,000 APDC % of RN FTE /total nurses FTE

1,477 hospitals, Whites: 45.4% Males: 42.43% 

Year RN/patient ratio % RN 1991 2.9 69 1992 2.7 69 1993 2.7 70 1994 2.7 71 1995 2.6 72 1996 2.8 71 1997 2.7 72 Increase by 1 unit in RN/patient ratio Increase by 1 unit in RN/patient ratio in small hospitals 

D3222222C00
Table G3. Evidence of the association between nurse staffing and mortality (continued) 

G-53

Author, 

Source to Measure 

Mortality, Definition of 

Mortality 

Source to Measure 

Nurse Staffing, 

Definition of Nurse 

Staffing 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 unit in RN/patient ratio in medium hospitals Increase by 1 unit in RN/patient ratio in large hospitals Increase by 1 unit in LPN/patient ratio Increase by 1 unit in LPN/patient ratio in small hospitals Increase by 1 unit in LPN/patient ratio in medium hospitals Increase by 1 unit in LPN/patient ratio in large hospitals Increase by 1 unit in UAP/patient ratio Increase by 1 unit in UAP/patient ratio in small hospitals Increase by 1 unit in UAP/patient ratio in medium hospitals Increase by 1 unit in UAP/patient ratio in large hospitals Increase by 1% in RN proportion Increase by 1% in RN proportion in small hospitals Increase by 1% in RN proportion in medium hospitals Increase by 1% in RN proportion in large hospitals 

------00-00-00

AHA = American Hospital Association; AMI = Acute Myocardial Infarction; BSN = Bachelor or Science in Nursing; CI = Confidence Interv

Medicare and Medicaid Services; FTE = Full Time Equivalent; HMO = Health Maintenance Organization; ICU = Intensive Care Unit; LPN 

Nurse; LVN = Licensed Vocational Nurse; MedPAR = Medicare Provider Analysis Review; NIW = nursing intensity weights; RN = Regis

Standard Deviation; UAP = Unlicensed Assistive Personnel
G-54 

Table G4. The relative risk of hospital related mortality among estimated categories of patients/nurse/shift ratio 

Author (Patients/RN/Shift) RR 95% CI 

Pronovost61 (2 vs. 3) 0.53 0.33; 0.83 

Amaravadi64 (1.5 vs. 3) 0.70 0.30; 2.00 

Dimick70 (1.5 vs. 3.5) 2.04 0.78; 5.56 

Aiken5 (1.5 vs. 5) 0.19 0.06; 0.61 

Aiken5 (1.9 vs. 5) 0.08 0.01; 0.47 

Aiken5 (2 vs. 3) 0.94 0.91; 0.99 

Aiken39 (1 vs. 6) 0.67 0.51; 0.84 

Aiken39 (1 vs. 4) 0.76 0.64; 0.89 

Person88 (1.1 vs. 2.8) 0.91 0.86; 0.97 

Person88 (1.6 vs. 2.8) 0.94 0.88; 1.00 

Person88 (1.9 vs. 2.8) 0.96 0.90; 1.00 

Elting92(4.3 vs. 9.5) 0.43 0.19; 0.97 

Mark90 (4.2 vs. 13.3) 0.99 0.97; 1.02 

Mark90 (4.1 vs. 13.3) 1.03 1.00; 1.05 

Mark90 (3.8 vs. 13.3) 0.99 0.97; 1.01 

Mark90 (3.6 vs. 13.3) 1.01 0.99; 1.04 

Mark90 (6.7 vs. 13.3) 0.82 0.74; 0.91 

Mark90 (6.7 vs. 13.3) 1.01 0.74; 1.39 

Mark90 (5 vs. 13.3) 0.97 0.96; 0.99 

Mark90 (4 vs. 13.3) 0.99 0.98; 1.00 

Mark90 (3.3 vs. 13.3) 1.00 0.99; 1.02 

Mark90 (5 vs. 13.3) 0.97 0.93; 1.01 

Mark90 (4 vs. 13.3) 0.97 0.93; 1.01 

Mark90 (3.3 vs. 13.3) 0.97 0.91; 1.03 

Mark89 (4 vs. 13.3) 1.05 1.02; 1.08 

Mark89 (3.8 vs. 13.3) 0.97 0.94; 1.00 

Mark89 (4.2 vs. 13.3) 1.09 1.06; 1.12 

Mark89 (4.2 vs. 13.3) 1.15 1.12; 1.18 

Mark89 (4.4 vs. 13.3) 1.20 1.17; 1.23 

Mark89 (3.3 vs. 13.3) 0.96 0.95; 0.98 

Mark89 (4 vs. 13.3) 0.97 0.96; 0.98 

Mark89 (5 vs. 13.3) 0.98 0.97; 0.99 

Mark89 (3.7 vs. 13.3) 0.90 0.87; 0.93 

Mark89 (6.7 vs. 13.3) 0.84 0.76; 0.93 

Silber67 (1.6 vs. 2.7) 0.95 0.93; 0.96 

Shortell54 (1.5 vs. 3) 1.13 0.86; 1.13 

Robertson62 (1.5 vs. 3) 0.97 NR 

Robertson62 (1.5 vs. 3) 0.98 NR 

Robertson62 (1.5 vs. 3) 0.96 NR 

Halm51 (0.8 vs. 4) 1.02 NR 

Author (Patients/LPN/Shift) 

Person88 (8 vs.11) 1.07 1.00; 1.15 

Person88 (10 vs. 11) 1.00 0.94; 1.07 

Mark90 (18 vs. 13) 0.99 0.97; 1.02 

Mark90 (21 vs. 13) 1.03 1.00; 1.05 

Mark90 (24 vs. 13) 0.99 0.96; 1.01 

Mark90 (25 vs. 13) 1.01 0.99; 1.04 

Mark90 (7 vs. 13) 1.05 0.82; 1.34 

Mark90 (7 vs. 13) 0.68 0.30; 1.52 

Robertson62 (3 vs. 20) 0.92 NR 

Mark89 (21 vs. 13) 1.05 1.02; 1.08 

Mark89 (23 vs. 13) 0.97 0.94; 1.00 

Mark89 (20 vs. 13) 1.09 1.06; 1.12 

Mark89 (19 vs. 13) 1.15 1.12; 1.18 

Mark89 (20 vs. 13) 1.20 1.17; 1.23 

Mark89 (23 vs. 13) 0.90 0.87; 0.93 

Mark89 (7 vs. 13) 1.01 0.97; 1.06 

NR– not reported 
G-55

Table G5. Evidence of the association between nurse/patient ratio and patient outcomes 

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Aiken39Discharge abstracts, Failure to rescue: deaths within 30 days of admission among patients who experienced complications; Complications: the secondary diagnosis distinguished from preexisting comorbidities Surveys of hospital nurses (the Pennsylvania Board of Nursing) The mean number of patients assigned to all staff nurses who reported caring for at least 1 but fewer than 20 patients on the last shift they worked 

168 ICU Surgical Age 60.8 61.3 Sex 42.9 41.8 Severity 28.5 18.9 

60% of hospital workforce with BSN or higher, 8 patients/day 40% of hospital workforce with BSN or higher, 4 patients/nurse 20% of hospital workforce with BSN or higher, 4 patients/nurse 60% of hospital workforce with BSN or higher, 6 patients/nurse 40% of hospital workforce with BSN or higher, 6 patients/nurse 20% of hospital workforce with BSN or higher, 6 patients/nurse 60% of hospital workforce with BSN or higher, 4 patients/nurse 20-29% of hospital workforce with BSN or higher <20% of hospital workforce with BSN or higher 20% of hospital workforce with BSN or higher, 8 patients/nurse >50% of hospital workforce with BSN or higher 40-49% of hospital workforce with BSN or higher 30-39% of hospital workforce with BSN or higher 40% of hospital workforce with BSN or higher Increase in workload of 1 patient Reference 1 RN/patient 20-29% of hospital workforce with BSN or higher <20% of hospital workforce with BSN or higher >50% of hospital workforce with BSN or higher 40-49% of hospital workforce with BSN or higher 30-39% of hospital workforce with BSN or higher 

Failur8.47 7.84 8.54 7.80 8.50 9.26 7.18 9.40 10.20 10.02 6.90 8.60 8.00 9.22 Relat1.05 1 Comp22.90 22.90 25.20 22.00 22.80 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-56

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Aiken74Hospital data (Health Care Cost Containment Council; Failure to rescue: deaths within 30 days of admission among patients who experienced complications; Survey of 50% random sample of registered nurses who were on the Pennsylvania Board of Nursing rolls; The mean patient load across all staff registered nurses who reported having responsibility for at least 1 but fewer than 20 patients on the last shift they worked, regardless of the specialty or shift (day, evening, night) worked

168 Combined Surgical Age 59.3 Sex 43.7 Severity 27.3 

Increase by 6 patients/nurse Increase by 1 patient/nurse Increase by 8 patients/nurse Increase by 4 patients/nurse Reference 1 RN/patient 

Failur1.50 1.07 1.72 1.31 1.00 

Alonso-Echanove79All adult patients admitted to the ICU for at least 48 hours; Bloodstream infections as secondary diagnosis after CVC. Duration of CVCnumber of days from the placement date to the day when bloodstream infection occurred or to the day of CVC removal; Unit administrative records; Number of RN nurses for each patient each day;Number of patient care assistants/100 patients

ICU Medical Race 61 Sex 54 

All ICU from 1997-1999 RN/patient ratio: 0.5 Patient/UAP: 14.3 Increase by 1 RN and UAP/patient 

Blood2.80 RelatNot s
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-57

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Amaravadi64The Uniform Health Discharge Data Set; Postoperative pneumonia; aspiration, pulmonary failure; reintubation after unplanned extubation; cardiac arrest; Complications: respiratory, Pneumonia, reintubation, aspiration, infectious, septicemia, postoperative infection, myocardial infarction, cardiac arrest, surgical complications, acute renal failure, septicemia; Survey of ICU directors; An average nurse-to-patient ratio of greater than or equal to 1:2 versus less than 1:2 both during the day and at night 

ICU Surgical Age 63 Race 77 Sex 70 Severity 12 

Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 

Pneu16.00 8.00 Relat2.40 1.00 Pulmo25.00 22.00 Relat1.20 1.00 Reint25.00 12.00 Relat2.50 1.00 CPR 0.80 0.00 Relat1.20 1.00 Medic0.80 0.90 Relat0.90 1.00 Surgic17.00 8.00 Relat1.90 2.10 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-58

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio>1:2 

Sepsi6.20 1.80 Relat3.70 1.00 

Bolton26

California Nursing Outcomes Coalition database; the California Department of Health Services; 1,253,892 inpatient days; Hospital acquired pressure ulcers: the monthly rate per 1,000 patient days for each nursing unit and each hospital. Falls: unplanned descent to the floor in adult patients; the monthly fall rate per 1,000 patient days for each nursing unit and each hospital. Data were collected at the patient level and aggregated by CalNOC staff to the unit level. California Nursing Outcomes Coalition database; the California Department of Health Services RN/patient day

Unit Patients Medical Medical ICU Medical 

Medical-surgical units: 5 patients/RN, 2.4 patient/UAP Critical Care units: 1.6 patients/RN Medical-surgical units: 5 patients/RN, 2.4 patient/UAP Critical Care units: 1.6 patients/RN 

Falls /3.70 0.10 Pressdays 8.00 13.00 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-59

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Cheung32Incidence reports, quality referrals, and medical record coding stores in the database Excalibur system Pressure ulcers coded as secondary diagnosis; patients falls coded as secondary diagnosis; primary bloodstream infections after admitting the unit; Automated Nurse staffing Office system and direct observation of nursing activities with Hill_Rom COMposer@nurse locator system; Number of patients assigned to RN during a shift; number of patients assigned to LPN during the shift; ratio of RN and LPN to unlicensed nursing personnel

Unit Combined Patients Medical Increase by one increment in nurse staffing variables: 

RN/patient ratio LPN/patient ratio Increase by one increment in nurse staffing variables: RN/patient ratio LPN/patient ratio Increase by one increment in nurse staffing variables: RN/patient ratio LNPNpatient ratio 

PressRelatNS NS Falls, NS NS PrimaRelatNS NS 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-60

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Dang75

The Uniform Health Discharge Data Set Aspiration, atelectasis or pulmonary failure; pneumonia; pulmonary insufficiency after a procedure; tracheal reintubation; cardiac arrest; Cardiac complications: acute myocardial infarction Cardiac complications after a procedure Other: acute renal failure, platelet transfusion Any other complication Any complication; septicemia; Survey of ICU directors; An average nurse-to-patient ratio in the ICU during the daytime; low-intensity staffing (1:3 or greater on the day and night shifts); medium intensity (1:3 or greater on either the day or night shift, but not both);high-intensity staffing <1:2

Unit ICU Patients Surgical Race 89 Sex 68 Severity 13 

High Intensity 4 patients/RN Mixed Intensity 3 patients/RN Low Intensity 2 patients/RN High Intensity 4 patients/RN Mixed Intensity 3 patients/RN Low Intensity 2 patients/RN High Intensity 4 patients/RN Mixed Intensity 3 patients/RN Low Intensity 2 patients/RN High Intensity 4 patients/RN Mixed Intensity 3 patients/RN Low Intensity 2 patients/RN High Intensity 4 patients/RN Low Intensity 2 patients/RN 

RelatPulmo2.33 5.11 1.00 Extub2.33 2.09 1.00 CPR 1.34 2.10 1.00 Comp1.34 2.10 1.00 Sepsi1.13 1.00 

Dimick70The Uniform Health Discharge Data Set Postoperative pneumonia, pulmonary failure, aspiration, reintubation, cardiac arrest, myocardial infarction, acute renal failure; septicemia; Survey of ICU directors; An average nurse-to-patient 

Unit: ICU Patients: Surgical Group 316 Age 56 Race 82 Severity 15 

More nurses: RN/patient 1:1-1:2 Fewer nurses: RN/patient 1:3-1:4 More nurses: RN/patient 1:1-1:2 Fewer nurses: RN/patient 1:3-1:4 More nurses: RN/patient 1:1-1:2 Fewer nurses: RN/patient 1:3-1:4 

Pneu2.80 4.20 Relat1.00 1.40 Pulmo1.60 5.80 Relat
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-61

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

ratio in the ICU during the day and evening and at night; "more ICU nurses: nurse/ patient ratio 1:1 or 1:2; "fewer ICU nurses": nurse/patient ratio 1:3 or 1:4

More nurses: RN/patient 1:1-1:2 Fewer nurses: RN/patient 1:3-1:4 More nurses: RN/patient 1:1-1:2 Fewer nurses: RN/patient 1:3-1:4 More nurses: RN/patient 1:1-1:2 Fewer nurses: RN/patient 1:3-1:4 More nurses: RN/patient 1:1-1:2 Fewer nurses: RN/patient 1:3-1:4 More nurses: RN/patient 1:1-1:2 Fewer nurses: RN/patient 1:3-1:4 More nurses: RN/patient 1:1-1:2 Fewer nurses: RN/patient 1:3-1:4 

1.00 3.60 Extub1.90 10.80 Relat5.70 CPR 0.60 0.80 Comp6.60 1.20 Sepsi2.70 5.40

Donaldson9

CalNOC database Total number of patients with Stage I-IV pressure ulcers regardless of whether ulcer was acquired during hospitalization or present on admission; %/total number of surveyed patients, unplanned descent to the floor; rate/1,000 patient days. CalNOC database in 2004 and 2005 (after legislation); number of patients/RN 

Hospitals 68 Unit Combined Patients Medical 

Medical surgical units, before mandatory ratios: 5.43 patients/RN Medical and surgical units after mandatory ratios: 4.48 patients/RN Step-down units before mandatory ratios: 4.02 patients/RN Step-down units after mandatory ratios: 3.56 patients/RN Medical surgical units, before mandatory ratios: 5.43 patients/RN Medical and surgical units after mandatory ratios: 4.48 patients/RN Step-down units before mandatory ratios: 4.02 patients/RN Step-down units after mandatory ratios: 3.56 patients/RN 

Falls /0.31 ± 0.32 ± 0.30 ± 0.26 ± Pressdays 14.07 14.48 13.52 16.29 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-62

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Donaldson95California Nursing Outcomes Coalition (CalNOC) Hospital acquired pressure related skin injury controlling for date of admission, % of all patients on the day of prevalence study; patient’s unplanned descent to the hospital floor; were analyzed as 7 day aggregate per unit; also actually number per unit; the number of falls/1000 patient days. The California Nursing Outcomes Coalition (CalNOC)

Hospitals 25 Unit Combined Patient Medical Increase by 1 patient/RN 

Increase by 1 patient/licensed staff 

Chandays 0.02 ± 0.02 ± 

Elting92The Texas Hospital Discharge Public Use Data File linked to the 2000 U.S. Census Bacteremia, wound infection, pulmonary compromise, pneumonia, deep venous thrombosis, pulmonary embolus, reoperation, postoperative coma or shock, acute myocardial infarction, arrhythmia, and cardiac arrest or shock. Hospital Cost Report Information System, Provider of Services files, and the American Hospital Association Survey; number of LPN/mean annual number 

Hospitals 75 Unit Surgical Patients Surgical Hospitals with many RNs/occupied bed 3.1 RNs/patient 

Hospitals with few RNs/occupied bed 1.4 RNs/patient Hospitals with many RNs/occupied bed 3.1 RNs/patient Hospitals with few RNs/occupied bed 1.4 RNs/patient Hospitals with many LPNs/occupied bed 0.32 patients/LPN Hospitals with few LPNs/occupied bed 1.40 patients/LPN 

FailurRelat1.00 0.39 Comp12.60 16.20 14.20 14.00 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-63

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

of occupied bed days, number of RN/mean annual number of occupied bed daysFlood53Patient medical records; nosocomial infections including urinary tract infections and gangrene; congestive heart failure and arrhythmias, gastrointestinal bleeding. Staffing workload index; RN FTE/patient/shift/unit

Hospitals 1 Unit Combined Patients Medical 

Understaffed unit 3.8 patient/s RN Normally staffed unit 4.94 patients/RN Understaffed unit 3.8 patients/RN Normally staffed unit 4.94 patients/RN Understaffed unit 3.8 patients/RN Normally staffed unit 4.94 patients/RN 

Urina0.12 0.14 Nosoc0.16 0.19 Comp64.00 71.00 

Fridkin1

Medical records of surgical patient in ICU. Cases were defined as any patient hospitalized >48 hours, in the SICU >24 hours who developed a laboratory confirmed CVC-BSI during outbreak periods. Controls were randomly selected from all SICU patients; laboratory confirmed catheterassociated bloodstream infections or clinical sepsis; rates were compared in preand outbreak periods. Hospital administrative records; average monthly SICU patient-to-nurse ratio; ratio in pre- and outbreak periods

Hospitals 1 Unit ICU Patients Surgical Month's patient/nurse ratio = 1.2 

Month's patient/nurse ratio = 1.5 Month's patient/nurse ratio = 2 Month's patient/nurse ratio = 1 Pre-outbreak period Outbreak period Pre-outbreak period Outbreak period 

NosocRelat3.95 15.60 61.50 1.00 Rate/1.95 4.96 Sepsi0.53 1.31 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-64

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Halm51

The hospital's data warehouse with patient’s discharges; failure to rescue: death following complications within 30 days. Survey of 140 staff nurses (42% response rate); daily variable staffing plans and unit census records Average RN/patient ratio was calculated for each nursing unit across all 3 shifts for every week

Hospitals 1 Unit Surgical Patients Surgical 

Increase by 1 unit in RN/patient ratio 

FailurRelat

Hope86

Medical Microbiology Laboratory and Infection Control Services; Discharge Abstract Database incidence rate of urinary tract infection, incidence rate of ventilator associated pneumonia, incidence rate of infections that occurred after 72 hours of hospitalization, incidence rate of surgical site infections, incidence rate of positive culture with known pathogen or two or more positive cultures with pathogens one can be considered as contaminant. The Grace Reynolds Application of the Study of Peto; Nursing Workload Office Calculated from RN utilization 

Unit Patients Surgical Surgical Surgical Surgical Surgical Surgical Surgical Surgical Medical Medical Medical Medical Medical Medical Medical Medical Medical Medical Medical Medical Medical Medical Medical Medical Specialty Medical ICU Medical ICU Medical Surgical Medical Neonatal Medical 

 Patients/RN Surgery ward 1 5.64 Surgery ward 2 6.97 Surgery ward 3 5.16 Surgery ward 4 6.64 Medicine ward 1 6.79 Medicine ward 2 4.07 Medicine ward 3 6.11 Medicine ward 4 6.09 medicine ward 4 6.19 Medicine ward 5 6 Medicine ward 6 5.39 Medicine ward 7 5.54 Coronary Care Unit 4.62 ICU unit 2.45 Neonatal ICU 2.14 Neurosurgical critical care unit 6.79 Pediatrics unit 4.39 Surgery ward 1 5.64 Surgery ward 2 6.97 

Rate/Urina0.65 0.88 0.91 0.66 0.00 0.65 0.50 0.64 1.27 0.68 0.72 0.74  0.42 1.13 4.03 1.33 0.27 RelatNosoc0.01 0.06 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-65

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

as (national US standard * Utilization) / 100 

Surgery ward 3 5.16 Surgery ward 4 6.64 Medicine ward 1 6.79 Medicine ward 2 4.07 Medicine ward 3 6.11 Medicine ward 4 6.09 Medicine ward 4 6.19 Medicine ward 5 6 Medicine ward 6 5.39 Medicine ward 7 5.54 Coronary Care Unit 4.62 ICU unit 2.45 Neonatal ICU 2.14 Neurosurgical critical care unit 6.79 Pediatrics unit 4.39 Surgery ward 1 5.64 Surgery ward 2 6.97 Surgery ward 3 5.16 Surgery ward 4 6.64 Medicine ward 1 6.79 Medicine ward 2 4.07 Medicine ward 3 6.11 Medicine ward 4 6.09 medicine ward 4 6.19 Medicine ward 5 6 Medicine ward 6 5.39 Medicine ward 7 5.54 Coronary Care Unit 4.62 ICU unit 2.45 Neonatal ICU 2.14 Neurosurgical critical care unit 6.79 Pediatrics unit 4.39  Patients/RN Higher RN Utilization (111%) 5.34 

0.02 0.03 0.03 0.02 0.01 0.01 0.001 0.001 0.01 0.04 0.001 0.20 0.01 0.01 0.001 RelatSepsi7.54 11.80 0.33 4.59 0.00 7.21 2.95 1.31 7.87 8.20 6.56 1.97 23.28 9.51 4.59 2.30 UTI re1.14 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-66

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

1% increase in RN utilization 5.94 Higher RN Utilization (111%), 5.34 Higher RN utilization (>89%) 7.14 1% increase in RN utilization 5.94 Higher RN Utilization (111%) 5.34 1% increase in RN utilization 5.94 1% increase in RN utilization, surgery wards 5.94 Higher RN Utilization (111%), surgery wards 5.34 1% increase in RN utilization, surgery wards 5.94 Higher RN utilization (>114%) in surgical units 5.16 

Pneu0.97 0.66 1.59 Nosocrisk 0.97 0.62 1.01 Sepsi0.98 0.66 0.99 0.53 

Houser49

Nationwide Inpatient Sample of 2001 with hospital discharge records; Failure to rescue: death/1,000 patients who developed complications of care during hospitalization; cases of decubitus ulcer/1,000 discharges identified as secondary diagnosis, cases of acute respiratory failure/1,000 surgical discharges, cases of deep vein thrombosis or PE/1,000 surgical discharges. American Hospital Association Annual Survey for 2001; Hospital reported RN FTE/average daily census

Hospitals 170 Unit Combined Patients Medical Age 55.08 Race 51 Sex 42 

RN/patient ratio 0.15-1.29 RN/patient ratio 1.3-1.89 RN/patient ratio 1.9-2.49 RN/patient ratio 2.5-6.5 RN/patient ratio 3.5-4.41 RN/patient ratio 4.57-5.5 RN/patient ratio 5.67-7.67 Increase by 1 unit in nurse staffing levels Reference (RN/patient=1) RN/patient ratio 0.15-1.29 RN/patient ratio 1.3-1.89 RN/patient ratio 1.9-2.49 RN/patient ratio 2.5-6.5 RN/patient ratio 3.5-4.41 RN/patient ratio 4.57-5.5 RN/patient ratio 5.67-7.67 RN/patient ratio 0.15-1.29 RN/patient ratio 1.3-1.89 RN/patient ratio 1.9-2.49 

Failur11.61 13.82 12.40 10.51 9.01 ± 9.42 ± 5.43 ± Relat0.92 1.00 Decu2.21 ± 2.57 ± 2.14 ± 1.90 ± 1.70 ± 1.44 ± 2.24 ± Pulmo0.26 ± 0.33 ± 0.32 ± 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-67

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

RN/patient ratio 2.5-6.5 RN/patient ratio 3.5-4.41 RN/patient ratio 4.57-5.5 RN/patient ratio 5.67-7.67 Increase by 1 unit in nurse staffing levels Reference (RN/patient = 1) RN/patient ratio 0.15-1.29 RN/patient ratio 1.3-1.89 RN/patient ratio 1.9-2.49 RN/patient ratio 2.5-6.5 RN/patient ratio 3.5-4.41 RN/patient ratio 4.57-5.5 RN/patient ratio 5.67-7.67 Increase by 1 unit in nurse staffing levels Reference (RN/patient = 1) 

0.19 ± 0.15 ± 0.34 ± 0.00 Relat0.94 1.00 Throm0.52 ± 0.75 ± 0.68 ± 0.44 ± 0.38 ± 0.52 ± 0.06 ± 0.84 1.00 

Kovner35

The National Inpatient Sample (NIS) Post operative discharges with UTI, pneumonia, pulmonary congestion, lung edema, or respiratory failure, and DVT in any secondary diagnosis. American Hospital Association Annual Survey of Hospitals, the part of the Health Care Utilization Project 

Hospitals 5,708 Unit Surgical Patient Surgical 

Increase by 1 patient/LPN Increase by 1 patient/LPN Increase by 1 patient/LPN Increase by 1 patient/LPN 

Urina1.01 Pneu0.99 Pulmo1 Throm0.96 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-68

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Marcin3

ICU Evaluation Database (controls), incidence reports (cases) Extubation where the endotracheal tube was displaced or removed from the trachea by either the patient (self-extubation) or unplanned by medical personnel (e.g., when positioning a patient for a radiograph or procedure). Archived nursing assignments, self-reported years in ICU; nurse-to-patient ratio at the time of the unplanned extubation or matching time for the control patients. Standard ratio 1:1 or 1:2

Hospitals 1 Size 220 Unit ICU Patients Combined Age 3 years

1:2 nurse/patient ratio 1:1 nurse/patient ratio 

Extub4.24 1.00 

Mark89

The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) Risk-adjusted observed/ expected urinary tract infections, risk-adjusted observed/expected pneumonias, risk-adjusted observed/expected decubitus ulcers American Hospital Association Annual Survey, Online Survey Certification and Reporting System 

Hospitals 357 Unit Combined Patients Combined 

 RN/patient Patients/LPN Year 1993 3.36 1.56 Year 1994 3.5 1.69 Year 1992 3.2 1.52 Year 1992 3.14 1.45 Year 1990 3.02 1.47 75th quartile of RN FTE/1,000 patient-days 4.02 

50th quartile of RN FTE/1,000 patient-days 3.34 25th quartile of RN FTE/1,000 patient-days 2.66 Year 1995 3.6 1.69 Increase by 1 RN FTE/patient day 2 Reference 1 RN FTE/patient day 1 Year 1993 3.36 1.56 Year 1994 3.5 1.69 Year 1992 3.2 1.52 

Urina1.14 1.11 1.17 1.17 1.18 0.93 0.94 0.95 0.98 1.05 1.00 Pneu0.84 0.90 0.72 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-69

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

[OSCAR] RN FTEs/1,000 inpatient days 

Year 1992 3.14 1.45 Year 1990 3.02 1.47 75th quartile of RN FTE/1,000patient-days 4.02 50th quartile of RN FTE/1,000patient-days 3.34 25th quartile of RN FTE/1,000patient-days 2.66 Year 1995 3.6 1.69 Increase by 1 RN FTE/patient day 2 Reference 1 RN FTE/patient day 1 Year 1993 3.36 1.56 Year 1994 3.5 1.69 Year 1992 3.2 1.52 Year 1992 3.14 1.45 Year 1990 3.02 1.47 75th quartile of RN FTE/1,000patient-days 4.02 50th quartile of RN FTE/1,000patient-days 3.34 25th quartile of RN FTE/1,000patient-days 2.66 Year 1995 3.6 1.69 Increase by 1 RN FTE/patient day 2 Reference 1 RN FTE/patient day 1 

0.65 0.61 0.98 0.96 0.94 0.97 1.03 ReferDecu0.62 0.69 0.58 0.51 0.48 0.96 0.96 0.95 0.74 1.10 1.00 

Potter40

Medical records (number of falls on a unit/number of patient days * 1,000 Administrative hospital data Proportion of UAP hours of direct patient care

Hospitals 1 Size 32 Unit ICU Patients Medical 

 Patients/UAP Means in time period 2-4/2000 1.1501 Means in time period 5-7/2000 1.1078 Means in time period 8-10/2000 1.134 Means in time period 11-1/2001 1.1532 

Falls/0.30 0.29 0.30 0.23 

Pronovost72

The Uniform Health Discharge Data Set Acute lung edema, pulmonary insufficiency after surgery, respiratory failure not otherwise specified, reinsertion of endotracheal tube, cardio respiratory arrest Medical complications: acute 

Unit ICU Patients Surgical Age 68 Race 89 Sex 66 Severity 11 Hospitals 7 31 7 

Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 

Pulmo24.00 9.00 24.00 9.00 Pulmo2.60 1.00 4.50 1.00 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-70

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

renal failure, septicemia, acute myocardial infarction, cardiac arrest Surgical complications: surgical complications after a procedure, surgical E codes, reoperation for bleeding, bloodstream infection, hemorrhage or hematoma complicating surgery. Survey to the ICU directors; An average ICU nurse-topatient ratio during the day and evening

31 

Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RN/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2

Extub21 13 21 13 Extub1.50 1.00 1.60 1.00 CPR 2 1 2 1 CPR 1.40 1.00 1.70 1.00 Surgic47 34 47 34 Relat1.40 1.00 1.70 1.00 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-71

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2 Fewer nurses RNs/patient 1:3 or 1:4 More nurses RNs/patient 1:1 or 1:2

Medic43 28 43 28 Relat1.50 1.00 2.10 1.00 Sepsi4 3 4 3 Relat1.40 1.00 1.90 1.00 Bleed2 3 2 3 Relat0.80 1.00 1.20 1.00 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-72

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Silber67Pennsylvania Medicare claims records; the Medicare Standard Analytic Files; random sample of 50% of Medicare patients who underwent general surgical or orthopedic procedures; Failure to rescue: 30-day death rate after complications, in-hospital complication rate: Cardiac event, CHF, Shock, DVT and PE, Stroke, TIA, Coma, Nosocomial infections, pneumonia, pulmonary failure, pressure ulcers, wound infections, sepsis, and bleeding. The American Hospital Association Annual Surveys for 1991–1993, and the Pennsylvania Health Care Cost Containment Council Data Base for years 1991–1994; RN/bed ratio at hospital level

Hospitals 245 Size 217,440 Unit Surgical Patients Surgical 

Hospitals with lower RN/bed ratio 1.1 Hospitals with higher RN/bed ratio 1.87 Indirect patients 1.38 RNs/patient Directed patients 1.4 RNs/patient Hospitals with lower RN/bed ratio 1.1 Hospitals with higher RN/bed ratio 1.87 Indirect patients 1.38 RNs/patient Directed patients 1.4 RNs/patient 

Failur1.00 0.94 % 9.32 8.18 Comp1.00 1.04 % 47.87 41.15 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-73

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Simmonds82

Active microbiological surveillance of all chronic patients admitted for >30 days of hemodialysis; volunteering patient participation in other units, % of patients with positive colonization of vancomycinresistant enterococci 48 hours after admission to the hospital and after surgery; Administrative reports of Patient Care Manager and Nursing Workload Specialist; Integrated Nursing System database, FTE RNs/number of beds

Hospitals 1 Unit Spec Patients Medical Age 68.75 Sex 55.8 

 Patient/RN Means at the beginning of the study 1.64 Means after 1 year 1.62 Means after 2 year 1.60 Means after 3 year 1.58 RN/patient ratio at the beginning of the study 1.64 RN/patient ratio after 1 year 1.62 RN/patient ratio after 2 years 1.60 RN/patient ratio after 3 years 1.58 

Nosoc1.61 3.29 4.97 6.65 1.92 1.75 1.58 1.41 

Stegenga78Patients and laboratory records Nosocomial viral gastrointestinal infections (NVGIs) (CDC definition). Rate = number of NVGIs/1,000 patient days. Administrative hospital records Number of nurses/patient in each shift according to actual work schedule. Ratio was calculated 72 hours before and after infection event

Hospitals 1 Unit ICU Patients Medical 

 RN/patient ratio Pre infection night shifts 3.16 Post infection night shifts 3.26 

Nosocpatien1.3 0 

Unruh66

State Health Care Cost Containment Council Secondary diagnosis of 

Hospitals 1,477 Unit Combined Patients Combined Race 45.37 

 RN/patient Patients/LPN Patients/ UAP State data in 1991 2.9 1.5 1.6 

State data in 1992 2.7 1.7 1.7 State data in 1993 2.7 1.8 1.8 

UTI %5.18 4.48 4.44 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-74

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

nosocomial UTI, hospital acquired pneumonia, decubitus ulcer, adult atelectasis, and cardiac arrest 

Sex 42.43 State data in 1994 2.7 2.0 1.8 

State data in 1995 2.6 2.0 1.8 State data in 1996 2.8 2.1 1.8 State data in 1997 2.7 2.4 1.7 Mean RN/patient levels in medium size hospitals: 2.67 Reduction by 10% in LPN/patient ratio, medium size hospitals: 2.4 Mean LPN/patient levels in medium size hospitals: 1.9 Reduction by 10% in LPN/patient ratio, medium size hospitals: 2.1 Mean RN/patient levels: 2.81 Reduction by 10% in LPN/patient ratio: 2.53 Mean LPN/patient levels: 1.9 Reduction by 10% in LPN/patient ratio: 2.0 State data in 1991 2.9 1.5 1.6 State data in 1992 2.7 1.7 1.7 State data in 1993 2.77 1.8 1.8 State data in 1994 2.7 2.0 1.8 State data in 1995 2.6 2.0 1.8 State data in 1996 2.8 2.1 1.8 State data in 1997 2.7 2.4 1.7 Mean RN/patient levels in medium size hospitals: 2.67 Reduction by 10% in LPN/patient, medium size hospitals: 2.4 Mean LPN/patient levels in medium size hospitals: 1.9 Reduction by 10% in LPN/patient, medium size hospitals: 2.1 Mean RN/patient levels: 2.81 Reduction by 10% in RPN/patient ratio: 2.53 Mean LPN/patient levels: 1.9 Reduction by 10% in LPN/patient ratio 2.0 State data in 1991 2.9 1.5 1.6 State data in 1992 2.7 1.7 1.7 State data in 1993 2.7 1.8 1.8 State data in 1994 2.7 2.0 1.8 State data in 1995 2.6 2.0 1.8 State data in 1996 2.8 2.1 1.8 State data in 1997 2.7 2.4 1.7 

4.91 4.80 5.14 4.70 0.50 0.51 0.50 0.50 0.51 0.52 0.51 0.51 SWI %0.29 0.26 0.24 0.28 0.28 0.31 0.30 0.27 0.27 0.27 0.27 0.30 0.31 0.30 0.32 Pnm 0.98 0.91 0.96 1.54 1.55 1.63 1.64 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-75

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 unit in RN/patient ratio Increase by 1 unit in RN/patient ratio in small hospitals Increase by 1 unit in RN/patient ratio in medium hospitals Increase by 1 unit in RN/patient ratio in large hospitals Increase by 1 unit in LPN/patient ratio Increase by 1 unit in LPN/patient ratio in small hospitals Increase by 1 unit in LPN/patient ratio in medium hospitals Increase by 1 unit in LPN/patient ratio in large hospitals Increase by 1 unit in UAP/patient ratio Increase by 1 unit in UAP/patient ratio in small hospitals Increase by 1 unit in UAP/patient ratio in medium hospitals Increase by 1 unit in UAP/patient ratio in large hospitals Increase by 1 unit in RN/patient ratio Increase by 1 unit in RN/patient ratio in small hospitals Increase by 1 unit in RN/patient ratio in medium hospitals Increase by 1 unit in RN/patient ratio in large hospitals Increase by 1 unit in LPN/patient ratio Increase by 1 unit in LPN/patient ratio in small hospitals Increase by 1 unit in LPN/patient ratio in medium hospitals Increase by 1 unit in LPN/patient ratio in large hospitals Increase by 1 unit in UAP/patient ratio Increase by 1 unit in UAP/patient ratio in small hospitals Increase by 1 unit in UAP/patient ratio in medium hospitals Increase by 1 unit in UAP/patient ratio in large hospitals Increase by 1 unit in RN/patient ratio Increase by 1 unit in RN/patient ratio in small hospitals Increase by 1 unit in RN/patient ratio in medium hospitals Increase by 1 unit in RN/patient ratio in large hospitals Increase by 1 unit in LPN/patient ratio Increase by 1 unit in LPN/patient ratio in small hospitals Increase by 1 unit in LPN/patient ratio in medium hospitals Increase by 1 unit in LPN/patient ratio in large hospitals Increase by 1 unit in UAP/patient ratio Increase by 1 unit in UAP/patient ratio in small hospitals Increase by 1 unit in UAP/patient ratio in medium hospitals Increase by 1 unit in UAP/patient ratio in large hospitals

UTI -0.15  0.31 -0.34 -0.07 -0.10  0.24 -0.37  0.77 -0.09  0.00 -0.14  0.05 Falls  -0.01  0.05  -0.02  0.00  -0.09  -0.12  0.01  0.01  -0.03  -0.08  0.05  -0.02 SWI  -0.02  -0.09  0.00  -0.02  -0.04  -0.03  0.00  0.01  0.02  -0.06  0.05  0.01 
Table G5. Evidence of the association between nurse/patient ratio and patient outcomes (continued)

G-76

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse/Patient 

Ratios 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Unruh81

Health Care Cost Containment Council Yearly number of occurrences of adverse events per hospital: secondary diagnosis of diseases and disorders of the kidney and urinary tract, male reproductive system, or female reproductive system, decubitus ulcer, fall, atelectasis, infection or sepsis or septicemia following infusion, injection, transfusion, or vaccination, and complications of obstetrical surgical wounds. The Pennsylvania Department of Health (PDH) and the American Hospital Association (AHA) Number of FTE RNs + LPNs on hospital payroll as of June 30th yearly. No. FTE RNs + LPNs + NA on hospital payroll as of June 30th yearly. 

Hospitals 1,477 Unit Combined Patients Medical 

Reference, 3.3 licensed nurses/patient 10% increase in number of licensed nurses 10% increase in number of licensed nurses 10% increase in number of licensed nurses 10% increase in number of licensed nurses 10% increase in number of licensed nurses 

RelatReferUrina0.99 Pneu1.01 Decu0.98 Falls 0.97 Pulmo0.985 

BSI = Bloodstream Infection; BSN = Bachelor of Science in Nursing; CPR = Cardiopulmonary Resuscitation; Dec Ul = Decubitus Ulcer; F

Equivalent; ICU = Intensive Care Unit; LPN = Licensed Practical Nurse; NA = Nursing Assistants; NS = Not Significant; Pnm = PneumonFailure; RN = Registered Nurse; SD = Standard Deviation; SICU = Surgical Intensive Care Unit; SWI = Surgical Wound Infection; UAP = Personnel; UTI = Urinary Tract Infection
G-77 

Table G6. Patient outcomes corresponding to an increase by one patient/RN/shift (effects reported by 

authors and calculated from published results, more studies contributed to pooled analysis) 

Author Outcome Measure Effect Standard 

Error Significance 

Pronovost72 Pulmonary failure Relative risk 0.61 0.14 0.05 

Pronovost72 Unplanned extubation Relative risk 0.22 0.02 0.01 

Pronovost72 CPR Relative risk 0.22 0.05 0.05 

Pronovost72 Complications Relative risk 0.22 0.05 0.05 

Pronovost72 Medical complications Relative risk 0.29 0.08 0.08 

Pronovost72 Surgical complications Relative risk -0.12 0.06 0.21 

Pronovost72 Sepsis Relative risk 0.24 0.08 0.09 

Pronovost72 Bleeding Relative risk -0.01 0.10 0.93 

Dang75 Pulmonary failure Relative risk 0.43 0.24 0.13 

Dang75 Unplanned extubation Relative risk 0.41 0.11 0.01 

Dang75 CPR Relative risk 0.18 0.12 0.19 

Dang75 Complications Relative risk 0.06 0.14 0.69 

Dang75 Medical Complications Relative risk 0.18 0.12 0.19 

Dang75 Sepsis Relative risk 0.06 0.14 0.69 

Amaravadi64 CPR Rate 0.40 

Amaravadi64 Hospital acquired pneumonia Rate 4.00 

Amaravadi64 Sepsis Rate 2.20 

Amaravadi64 Pulmonary failure Rate 1.50 

Amaravadi64 Unplanned extubation Rate 6.50 

Amaravadi64 Hospital acquired pneumonia Relative risk 0.44 

Amaravadi64 Pulmonary failure Relative risk 0.09 

Amaravadi64 Unplanned extubation Relative risk 0.46 

Amaravadi64 CPR Relative risk 0.09 

Amaravadi64 Medical complications Relative risk -0.05 

Amaravadi64 Surgical complications Relative risk -0.05 

Amaravadi64 Sepsis Relative risk 0.65 

Dimick70 CPR Rate 0.10 

Dimick70 Hospital acquired pneumonia Rate 0.70 

Dimick70 Sepsis Rate 1.35 

Dimick70 Pulmonary failure Rate 2.10 

Dimick70 Unplanned extubation Rate 4.45 

Dimick70 Hospital acquired pneumonia Relative risk 0.17 

Dimick70 Pulmonary failure Relative risk 0.64 

Dimick70 Unplanned extubation Relative risk 0.87 

Aiken39 Failure to rescue Rate 0.41 0.16 0.03 

Aiken39 Failure to rescue Relative risk 0.05 

Aiken39 Failure to rescue Relative risk 0.08 0.00 0.00 

Marcin3 Unplanned extubation Relative risk 1.44 

Elting92 Failure to rescue Relative risk -0.18 

Flood53 Urinary tract infection Rate 0.02 

Flood53 Nosocomial infection Rate 0.03 

Fridkin1 Nosocomial infection Rate 41.06 

Fridkin1 Sepsis Rate 10.64 

Fridkin1 Sepsis Relative risk 3.99 0.58 0.02 

Mark89 Urinary tract infection Relative risk 0.00 0.01 0.69 

Mark89 Hospital acquired pneumonia Relative risk 0.02 0.02 0.36 

Donaldson9 Falls Rate 0.43 0.21 0.17 

Donaldson9 Pressure ulcers Rate -0.82 0.89 0.46 

Bolton26 Falls Rate 5.35 

Bolton26 Pressure ulcers Rate -1.47 

Silber67 Failure to rescue Rate 36.71 

Silber67 Failure to rescue Relative risk 0.06 

Silber67 Complications Relative risk -0.03 

Hope86 Urinary tract infection Rate -0.71 0.43 0.12 
Table G6. Patient outcomes corresponding to an increase by one patient/RN/shift (effects reported by 

authors and calculated from published results, more studies contributed to pooled analysis) (continued) 

G-78 

Author Outcome Measure Effect Standard 

Error Significance 

Hope86 Nosocomial infection Rate -0.03 0.03 0.31 

Hope86 Sepsis Rate -0.10 0.10 0.34 

Hope86 Urinary tract infection Relative risk -0.01 0.00 0.18 

Hope86 Hospital acquired pneumonia Relative risk 0.07 0.02 0.00 

Hope86 Nosocomial infection Relative risk 0.02 0.02 0.17 

Hope86 Surgical wound infection Relative risk 0.02 0.04 0.67 

Hope86 Sepsis Relative risk 0.02 0.03 0.42 

Houser49 Failure to rescue Rate 0.23 0.30 0.48 

Houser49 Pulmonary failure Rate 0.01 0.01 0.65 

Houser49 Deep venous thrombosis Rate 0.01 0.03 0.69 

Houser49 Failure to rescue Relative risk 0.03 

Houser49 Pulmonary failure Relative risk 0.02 

Houser49 Deep venous thrombosis Relative risk 0.06 

Halm51 Failure to rescue Relative risk 0.00 0.00 0.00 

Simmonds82 Nosocomial infection Rate -13.35 10.40 0.25 

Unruh66 CPR Rate -0.32 0.03 <.0001 

Unruh66 Falls Rate -0.24 0.12 0.08 

Unruh66 Urinary tract infection Rate -2.13 0.58 0.00 

Unruh66 Hospital acquired pneumonia Rate -0.71 0.13 0.00 

Unruh66 Surgical wound infection Rate -0.17 0.02 <.0001 

Unruh66 Pulmonary failure Rate -0.33 0.04 <.0001 
G-79 

Table G7. Patient outcomes corresponding to an increase by one patient/LPN (effects reported by authors 

and calculated from published results, more studies contributed to pooled analysis) 

Author Outcome Measure Effect Standard Error Significance 

Needleman28 Failure to rescue Rate -0.07 0.07 0.36 

Needleman28 Urinary tract infection Rate -0.07 0.04 0.10 

Needleman28 Hospital acquired pneumonia Rate -0.06 0.03 0.03 

Needleman28 Sepsis Rate 0.00 0.01 0.86 

Needleman28 Surgical wound infection Rate 0.01 0.01 0.42 

Needleman28 Pressure ulcers Rate -0.04 0.04 0.34 

Needleman28 Upper gastrointestinal bleeding Rate -0.01 0.01 0.33 

Needleman28 Shock Rate -0.01 0.01 0.14 

Needleman28 Pulmonary failure Rate -0.05 0.04 0.21 

Needleman28 Deep venous thrombosis Rate 0.00 0.00 0.27 

Kovner35 Urinary tract infection Rate -0.02 0.02 0.31 

Kovner35 Hospital acquired pneumonia Rate 0.02 0.01 0.32 

Kovner35 Pulmonary failure Rate 0.00 0.01 0.93 

Kovner35 Deep venous thrombosis Rate -0.04 0.02 0.12 

Langemo41 Pressure ulcers Rate 0.49 0.33 0.37 

Mark89 Urinary tract infection Relative risk -0.04 0.01 0.05 

Mark89 Hospital acquired pneumonia Relative risk 0.12 0.02 0.00 

Bolton26 Falls Rate 1.60 

Bolton26 Pressure ulcers Rate -0.44 

Unruh66 CPR Rate 0.03 0.00 <.0001 

Unruh66 Falls Rate 0.03 0.01 0.00 

Unruh66 Urinary tract infection Rate 0.14 0.06 0.03 

Unruh66 Hospital acquired pneumonia Rate 0.06 0.01 <.0001 

Unruh66 Surgical wound infection Rate 0.01 0.00 <.0001 

Unruh66 Pulmonary failure Rate 0.04 0.01 <.0001 

Zidek85 Falls Rate 0.02 0.08 0.77 

Zidek85 Pressure ulcers Rate -0.01 0.04 0.82 

Tallier83 Urinary tract infection Rate 0.81 0.32 0.07 

Tallier83 Pressure ulcers Rate -0.38 0.33 0.31 
G-80 

Table G8. Patient outcomes corresponding to an increase by one patient/UAP (effects reported by authors 

and calculated from published results, more studies contributed to pooled analysis) 

Author Outcome Measure Effect Standard 

error 

Significance 

Needleman28 Failure to rescue Rate 0.14 0.41 0.73 

Needleman28 Urinary tract infection Rate -0.19 0.22 0.39 

Needleman28 Hospital acquired pneumonia Rate -0.15 0.15 0.33 

Needleman28 Sepsis Rate 0.04 0.06 0.48 

Needleman28 Surgical wound infection Rate 0.02 0.03 0.57 

Needleman28 Pressure ulcers Rate 0.06 0.25 0.81 

Needleman28 Gastrointestinal bleeding Rate -0.04 0.05 0.36 

Needleman28 Shock Rate -0.02 0.04 0.60 

Needleman28 Pulmonary failure Rate 0.01 0.19 0.97 

Needleman28 Deep venous thrombosis Rate -0.03 0.02 0.11 

Potter 40 Falls Rate 0.28 0.50 0.64 

Sovie71 Falls Rate -0.08 0.34 0.82 

Sovie71 Urinary tract infection Rate -0.17 0.13 0.26 

Sovie71 Pressure ulcers Rate -0.25 0.26 0.41 

Ritter-Teitel69 Falls Rate -0.07 0.04 0.18 

Ritter-Teitel69 Urinary tract infection Rate -0.41 0.02 <.0001 

Ritter-Teitel69 Pressure ulcers Rate 0.25 0.13 0.12 

Unruh66 CPR Rate 0.03 0.00 <.0001 

Unruh66 Falls Rate 0.03 0.01 0.02 

Unruh66 Urinary tract infection Rate 0.28 0.02 <.0001 

Unruh66 Hospital acquired pneumonia Rate 0.07 0.01 0.00 

Unruh66 Surgical wound infection Rate 0.02 0.00 <.0001 

Unruh66 Pulmonary failure Rate 0.03 0.00 <.0001 

Zidek85 Falls Rate 0.00 0.01 0.97 

Zidek85 Pressure ulcers Rate 0.00 0.01 0.44 

Stratton91 Nosocomial infection Rate 0.04 0.11 0.70 

Tallier83 Urinary tract infection Rate 0.21 3.58 0.96 

Tallier83 Pressure ulcers Rate -1.23 2.57 0.66 
G-81

Table G9. The association between nurse staffing and length of stay 

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Amaravadi64The Uniform Health Discharge Data Set; hospital length of stay, survey of ICU directors; average nurse-topatient ratio of ≥1:2 versus <1:2 both during the day and at night

Hospitals 1 Unit ICU Patients Surgical 

Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 Night time nurse to patient ratio <1:2 Night time nurse to patient ratio >1:2 

15 9 Relative incr1.39 1.1 1 

ANA65Uniform Hospital Discharge Data Set; an average length of stay in hospital, American Hospital Association survey, hospitals cost reports; total nursing hours per Nursing Intensity Weight, % RN Hours/total nursing hours 

Increase by 1 hour in total nursing hours in Massachusetts, 1992 Massachusetts, 1994 New York, 1992 New York, 1994 California, 1992 California, 1994 Increase by 1% in RN in Massachusetts, 1992 Massachusetts, 1994 New York, 1992 New York, 1994 California, 1992 California, 1994

Relative incr0.903 1 0.9354 0.956 0.9518 0.946 0.9973 0.9981 0.9981 0.9989 0.9993 0.9984

Barkell77

Medical records; length of stay in the unit: the number of midnights a patient was on the unit as an inpatient, hospital administrative database, proportion of RN/total nursing staff

Hospitals 1 Unit Surgical Patients Surgical 

Team nursing model with patient care associate assisting RNs in delivery of patient care (66% of RN) Total patient care model, 79% RN 

Length of sta6.8 ± 3.1 7.1 ± 2.9 
Table G9. The association between nurse staffing and length of stay (continued)

G-82

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Beckman37

Medical records, length of stay in unit, unit administrators and nurses survey, hospital administrative data; scheduled RNs/patients in unit, % of RN/total nursing personnel 

Hospital 1 Unit ICU Unit Surgical Surgical Specialty Medical Medical Surgical Surgical 

RN + Case manager RN + MSW RN + Clinical nurse specialist RN + mixed support (rehabilitation nurse) Advanced practice nurse + clinical nurse specialist Advanced practice nurse + social worker Advanced practice nurse + mixed support RN staff with no support Patient/RN % RN 0.86 60 0.85 66 0.63 69 1.04 61.5 1.16 58.5 0.91 69 1.39 57 

Length of sta29 ± 32.6 35 ± 42 11 ± 2.1 17 ± 8.5 11 ± 6 7 ± 0 14 ± 0 9 ± 7.4 13.25 ± 5.73 7.92 ± 6.64 28.53 ± 33.710.50 ± 5.87 9.77 ± 8.17 12.29 ± 9.42 4.23 ± 3.00 

Cho30

The State Inpatient Databases in hospital length of stay, Hospital Financial Data; the total productive hours worked by RN per patient day; contracted hours = productive nursing hours (direct care to patient) worked by nursing personnel contracted on a temporary basis. Contract hours * % of RN; RN hours divided by all hours 

Unit Combined Patients Combined 

RN hours % RN % contract hours  7.2 76.5 3.60  6 68.1 3.30  6.6 72.4 3.20  6.2 72.7 5.00 

Length of sta8.6 ± 1.5 7.2 ± 1.3 7.6 ± 9 7.8 ± 1.5 
Table G9. The association between nurse staffing and length of stay (continued)

G-83

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Cimiotti87

Patients discharges and medical records review by study's nurse epidemiologist; the length of stay as the 1 day of admission and all succeeding days except the day of discharge, nurse staffing office and sign-in/out sheet from each supplemental nursing agency; total nursing hours worked by direct care providers adjusted for Nursing Intensity Weights categorized as below and above median; RN hours/patient day adjusted for Nursing Intensity Weights categorized as below and above median; % of RN hours among total nursing hours adjusted for Nursing Intensity Weights; hours/patient day worked by float pool and agency RN not regularly assigned to the NICU 

Hospitals 1 Unit Neonatal Patients Medical 

Nurse hours RN hours % RN 10.68 10.68 100 10.97 10.56 96 8.705 12.95  8.5  12.74 % of contract nurses 0.19 24.07 14.19 12.13 

Length of sta17.23 ± 24.319.6 ± 28.28 10.01 ± 13.421.3 ± 29.03 15.75 ± 24.418.05 ± 24.617.23 ± 24.319.6 ± 28.28 12.52 ± 16.017.1 ± 30.75 

Dimick70The Uniform Health Discharge Data Set; In-hospital length of stay; survey of ICU directors; average nurse-topatient ratio in the ICU during the day and evening and at night. 

Hospitals 32 Unit ICU Patients Surgical 

More nurses: RNs/patient 1:1-1:2 Fewer nurses: RNs/patient 1:1-3-1:4 

Relative incr1 1 1.09 0.89 

Flood53Patient medical records; length of stay in unit, staffing workload index; RN FTE/patient per shift per unit

Hospitals 1 Unit Combined Patients Medical 

Nurse hours % RN 6.9 60.45 6.7 42.32 

Length of sta8.56 ± 7.81 9.49 ± 8.74 

Gandjour24

Health Care Financing Administration database; average hospital length of stay; Joint Annual Report of Hospital Data; number of administrative full time employees RN (FTE)/1,000 patient days

Hospitals 77 Unit Combined Patients Combined 

Nurse hours Patients/nurse 19 2.86 19 2.85 8.9 3.22 8.4 3.44 4 3.2 

Length of sta5.49 5.54 5.43 5.13 5.29 
Table G9. The association between nurse staffing and length of stay (continued)

G-84

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Grillo-Peck10

Review of risk management records and medication records 6 months before and after implementation of nursing model; length of stay in unit; hospital administrative records; decrease in % of RN in the unit within new partnership model with increase patient care technicians and service associates; RN spent more time on direct patient care 

Hospitals 1 Unit Specialized Patients Medical 

% RN 80 60 

Length of sta9.46 8.76 

Halpine14

The Hospital Medical Records Institute database; in average length of stay in units; The Hospital Medical Records Institute; GRASP workload system; total nursing hours/patient day 

Hospitals 5 Unit Patients Spec Medical Surgical Surgical Surgical Surgical Surgical Surgical Surgical Surgical Surgical Surgical Neonatal Medical Surgical Surgical Specialty Surgical Surgical Surgical Surgical Surgical Surgical Surgical Surgical Surgical Neonatal Medical ICU Medical Surgical Surgical ICU Medical Specialty Medical Specialty Medical Medical Medical Surgical Surgical Surgical Surgical Medical Medical Medical Medical Neonatal Medical Surgical Surgical Medical Medical Surgical Surgical 

Hour 8.64 8.51 7.57 6.92 6.64 6.56 6.32 6.14 6.07 5.87 5.78 5.78 5.47 4.67 4.66 4.58 4.52 4.51 4.41 4.38 9.28 9.19 7.51 7.32 6.49 6.33 6.32 6.15 

Length of sta39.25 1.86 13.33 15 9.24 12.2 7.58 21.79 19.79 16.71 14.31 26.5 2.19 4.74 12.34 6.72 10.1 12.49 17.86 6.67 9.75 10.76 2.56 1.32 3.06 1.52 3.34 2.1 
Table G9. The association between nurse staffing and length of stay (continued)

G-85

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Neonatal Medical Medical Medical Medical Surgical Medical Medical Surgical Surgical Neonatal Medical Neonatal Medical ICU Medical Medical Medical Surgical Surgical Specialty Medical Surgical Surgical 

6.01 5.78 5.59 5.58 5.53 5.49 5.45 5.41 5.34 5.13 5.1 5.06 

2.52 4.42 2.17 4.33 9 2.26 2.86 9.42 2.75 17.11 2.6 3.23 

Hoover23

The Health Care Financing Agency, HealthCareReportCards.com; MEDPAR database, the Medicare Average Length of Stay (ALOS) = total number of Medicare discharge days/total number of Medicare discharges for each hospital. The AHA and HCFA databases; RN/LPN ratio = total number RN FTE/LPN FTE reported by the hospital and RN/total nursing staff 

Unit Combined Patients Medical Hospitals 54  52  70  176  176 

% RN 79.6 69.8 72.83 81.8 62.9 

Length of sta5.67 ± 0.36 5.69 ± 0.67 6.31 ± 0.47 5.82 ± 0.09 6.18 ± 0.09 

Houser49

Nationwide Inpatient Sample of 2001 with hospital discharge records; average length of stay in the hospital in days; American Hospital Association Annual Survey for 2001; hospital reported RN FTE/RN + LPN 

Unit Combined Patients Medical Hospitals 170  172  174  171  39  14  8 

RN/patient ratio 0.15-1.29 RN/patient ratio 1.3-1.89 RN/patient ratio 1.9-2.49 RN/patient ratio 2.5-6.5 RN/patient ratio 3.5-4.41 RN/patient ratio 4.57-5.5 RN/patient ratio 5.67-7.67 

LOS, days ± 4.64 ± 2.68 4.54 ± 0.97 4.38 ± 2.59 3.84 ± 2.19 4.08 ± 4 3.47 ± 1.25 2.76 ± 0.88 
Table G9. The association between nurse staffing and length of stay (continued)

G-86

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Lichtig63

The Uniform Hospital Discharge Data Set; The California Office of Statewide Health Planning and Development; the Statewide Planning and Research Cooperative System Administratively Releasable file; a relative length of stay (LOS) index was calculated as the ratio of the actual-to-expected geometric mean LOS; The Annual Hospital Disclosure Report, Institutional Cost Reports; total nursing hours per NIW-adjusted patient day; RN hours as a percentage of total nursing hours per NIW-adjusted patient day.

Unit Surgical Patients Surgical Hospitals 126  131  352  295  126  131  352  295 

Increase by 1 hour in total nursing hours in New York, 1992 12.50 New York, 1994 13.00 California, 1992 12.00 California, 1994 6.50 New York,1992 13.50 New York, 1994 12.80 Increase by 1% in proportion of RNs, California, 1992 Increase by 1% in proportion of RNs, California, 1994 

Relative cha0.94 0.96 0.95 0.95 1.00 1.00 Not significaNot significa

Mark90

Centers for Medicare Services, Minimum Cost and Capital File, CMS Provider of Services File, CMS Case Mix Index File, CMS Online Survey; Certification and Reporting system (OSCAR) files, and HCUP files. riskadjusted ratio of observed/expected length of stay; Area Resource Files, American Hospital Association Annual Survey, CMS Wage Rate File, CMS Online Survey; Certification and Reporting system (OSCAR) files; RN FTEs/1,000 inpatient days, RN hours/patient * day = (FTE RN/1,000patient * days * 37.5 * 48)/1,000; 37.5 hours work week in average 48 working weeks/year, LPN FTEs/1,000 inpatient days, LPN hours/patient * day = (FTE LPN/1,000 patients * days * 37.5 * 48)/1,000; 37.5 hours work week in average 48 working weeks/year

Unit Patients Combined Medical 

Pt/RN RN hours Pt/LPN LPN hours 0.31 5.74 1.32 1.36 0.31 5.88 1.57 1.15 0.28 6.36 1.81 0.99 0.27 6.59 1.87 0.96 Increase by 1 RN FTE/1,000 patient days in hospitals with high HMO penetration Increase by 1 LPN FTE/1,000 patient days in hospitals with high HMO penetration Increase by 1 RN FTE/1,000 patient days in hospitals with low HMO penetration Increase by 1 LPN FTE/1,000 patient days in hospitals with low HMO penetration Nurse hours Patient/RN RN hours  14.60 0.38 4.79  9.60 0.30 6.01  17.60 0.25 7.24  7.80 0.38 4.79  10.90 0.30 6.01  0.25 7.24 

Relative cha0.78 0.83 0.81 0.80 0.97 1.03 0.99 1.04 0.99 0.99 1.00 1.00 1.00 1.00 
Table G9. The association between nurse staffing and length of stay (continued)

G-87

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Mark80

The hospital’s incident reporting system and patient survey; total patient days divided by the number of discharges, administrative hospital data, nursing survey; proportion of RNs to the total complement of nursing staff, as a ratio of the number of nurses who left during the period divided by the number of nurses employed at the end of the year; availability of support services was evaluated with a 27-item, 3-point checklist 24 in which staff nurses (n = 1,682) indicated whether a variety of support services was available, not available, or inconsistently available (alpha =.85)

Hospitals 64 Unit Combined Patients Medical 

Nurse hours % RN % BSN 10.00 58.00 21.00 

Length of sta5.31 ± 1.47 

Melberg20

Hospital discharge data; average length of stay in hospital; hospital administrative data; FTE RN/100 occupied bed in acute units; % of RN/total nursing personnel

Hospitals 1 Unit ICU Patients Medical 

Patient/RN % RN 0.41 96.00 0.44 73.00 0.36 64.00 0.42 76.00 0.42 82.00 

Length of sta5.97 6.70 6.15 5.20 6.30 

Needleman28

799 hospitals (11 states, all-patients + Medicare patients) – hospital level analysis; 256 California hospitals (part of the 11 state sample) – unit level analysis; national sample of 3,357 hospitals (Medicare patients) - hospital level analysis; length of stay in hospital; nurse hours calculation: (2,080 hours * each FTE category) + (1,040 hours * number of part-time employees). Total nursing hours/patient-day NIW adjusted including RNs, clinical nurse specialists, general duty nurses, nurse practitioner excluding nursing directors, managers, administrators, 

Hospitals Patient 32 Medical 280 Medical 83 Medical 128 Medical 68 Medical 86 Medical 145 Medical 154 Medical 25 Medical 127 Medical 488 Medical 3,357 Medical 3,296 Surgical 127 Surgical 280 Surgical 83 Surgical 

Nevada New York Maryland Virginia West Virginia South Carolina Wisconsin Missouri Arizona Massachusetts California Medicare patients Medicare patients Massachusetts New York Maryland 

Length of sta4.5 ± 1.26 6.31 ± 1.42 4.34 ± 0.70 4.62 ± 1.16 5.72 ± 1.57 4.71 ± 0.72 4.03 ± 0.84 5.38 ± 1.67 3.63 ± 0.92 4.79 ± 1.10 4.81 ± 2.71 5.79 ± 2.92 7.68 ± 2.90 4.15 ± 0.59 5.35 ± 0.97 4.25 ± 0.92 
Table G9. The association between nurse staffing and length of stay (continued)

G-88

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

supervisors, instructors, anesthetists, and midwifes; RN hours/patient day NIW adjusted; licensed hours/patient-day NIW adjusted including LPN/LVN, excluding the director of nursing. LPN/LVN hours/patient day NIW adjusted; RN hours per day/total hours per day; RN hours/licensed hours = RN hours per day/licensed hours per day (RN + LPN) 

128 Surgical 68 Surgical 86 Surgical 145 Surgical 154 Surgical 25 Surgical 32 Surgical 488 Surgical 4,156 Medical 4,156 Surgical 4,156 Medical 4,156 Surgical 4,156 Medical 4,156 Surgical 4,156 Medical 4,156 Surgical 4,156 Medical 4,156 Surgical 4,156 Medical 4,156 Medical 4,156 Surgical 4,156 Surgical 3,357 Medical 3,357 Medical 3,357 Medical 3,357 Medical 3,357 Medical 3,357 Medical 3,357 Medical 3,357 Surgical 3,357 Surgical 3,357 Surgical 3,357 Surgical 3,357 Surgical 3,357 Surgical 3,357 Surgical 256 Medical 256 Medical 256 Medical 

Virginia West Virginia South Carolina Wisconsin Missouri Arizona Nevada California Increase by 1 hour of RN hours Increase by 1 hour in RN hours Increase by 1 hour in LPN hours Increase by 1 hour in LPN hours Increase by 1 hour in aide hours Increase by 1 hour in aide hours Increase by 1 hour in total nursing hrs Increase by 1 hour in total nursing hrs Increase by 1% in RNs Increase by 1% in RNs Increase by 1 hour in licensed hour increase by 1% of RN/licensed hour Increase by 1 hour in licensed hour Increase by 1% in RN/licensed hour Increase by 1 hour in RN hours Increase by 1 hour in LPN hours Increase by 1 hour in licensed hours Increase by 1% in RN/licensed hours Increase in total nurse hours Increase by 1% in RNs Increase by 1 hours in aide hours Increase by 1 hour in RN hours Increase by 1 hour in LPN hours Increase by 1 hour in licensed hours Increase by 1% in RN/licensed hours Increase by hour in aide hours Increase by 1 hour in total nursing hrs Increase by 1% in RNs California hospitals Increase by hour in RN hours Increase by 1 hour in LPN hours Increase by 1 hour in aide hours 

4.32 ± 0.92 8.09 ± 3.15 4.62 ± 1.10 4.38 ± 0.74 4.52 ± 0.76 3.91 ± 0.50 5.35 ± 0.79 4.27 ± 1.19 Relative cha0.90 0.80.97 0.90.98 0.91.05 0.91.07 1.01.00 0.90.95 0.90.99 0.90.12 0.00.84 0.30.91 0.80.28 0.10.99 0.90.48 0.20.94 0.90.99 0.90.95 0.90.45 0.20.94 0.90.07 0.01.09 1.00.98 0.90.97 0.90.98 0.90.93 0.50.99 0.90.64 0.40.73 0.10.80 0.61.54 0.60.99 0.7
Table G9. The association between nurse staffing and length of stay (continued)

G-89

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

256 Medical 256 Medical 256 Medical 256 Medical 256 Medical 256 Medical 256 Medical 256 Medical 256 Medical 256 Medical 256 Medical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 

Increase by 1 hour in nursing hours Increase by 1% in RNs Increase by 1 hour of licensed hours Increase by 1% of RNs/licensed hour Increase by 1 hour of RN hours Increase by 1 hour in LPN hours Increase by 1 hour in aide hours Increase by 1 hour nursing hours Increase by 1% in RNs Increase by 1 hour/licensed hour Increase by 1% of RN hours/licensed hr Increase by 1 hour of RNs Increase by 1 hour in LPN hours Increase by 1 hour in aide hours Increase by 1 hour in total nursing hours Increase by 1% in RNs Increase by 1 hour in licensed hours Increase by 1% in RNs Unit level analysis: Increase by 1 hour of RN hours Increase by 1 hour in LPN hours Increase by 1 hour in aide hours Increase by 1 hour in total nursing hoursIncrease by 1% in RNs Increase by 1 hour in licensed hours Increase by 1% in RNs 

0.92 0.70.00 0.00.47 0.20.00 0.00.71 0.51.14 0.50.93 0.60.82 0.70.00 0.00.19 0.00.01 0.01.00 0.91.20 1.00.92 0.81.00 0.90.16 0.01.03 0.90.31 0.01.00 0.93.12 1.10.89 0.70.98 0.92.47 0.81.02 0.90.48 0.1

Needleman43

Hospital discharge data from 11 states (all patients and Medicare sample) and MedPAR national database (all Medicare patients); adjusted length of stay; state hospital staffing surveys or financial reports. American Hospital Association Annual Survey; Licensed hours (RN + LPN)/patient days adjusted for nursing case-mix index for each hospital, proportion of RN hours/licensed hours (RN + LPN) adjusted for nursing case-mix index for each hospital 

Hospitals 799 Unit Combined Patients Medical 

1% increase in RN hours/licensed hour Increase in 1 licensed hour Increase in 1 licensed hour 1% increase in RN hours/licensed hour Increase in 1 licensed hour 1% increase in RN hours/licensed hour 1% increase in RN hours/licensed hour Increase in 1 licensed hour 1% increase in RN hours/licensed hour Increase in 1 licensed hour Increase in 1 licensed hour 1% increase in RN hours/licensed hour 1% increase in RN hours/licensed hour Increase in 1 licensed hour 

Relative cha0.24 0.10.99 0.90.97 0.90.94 0.50.99 0.90.46 0.10.58 0.20.95 0.90.44 0.30.87 0.80.91 0.80.11 0.00.33 0.10.91 0.8
Table G9. The association between nurse staffing and length of stay (continued)

G-90

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Oster31

Electronic medical records system; length of stay in the hospital for each patient; hospital administrative daily statistic reports; total productive nursing hours/patient day; total number of productive hours worked by nursing personnel with direct patient care/number of patients; % of RN hours/total nursing hours per patient day; % of contract agencies nurses; % of full time nurses

Hospitals 1 Unit Patients Emergency Medical Surgical Surgical Surgical Surgical Intensive Care Unit Medical Intensive Care Unit Medical Specialty Medical Specialty Medical 

% RN % contract hrs % full-time hrs 67.00 18.30 70.00 

Length of sta5.24 ± 3.95 0.03 -0.02 -0.02 0.01 -0.19 -0.11 

Pronovost72

The Uniform Health Discharge Data Set; Hospital length of stay, survey to the ICU directors, average ICU nurse-to-patient ratio during the day and evening 

Unit ICU Patients Surgical Hospitals 7  31  7  31 

More nurses: RNs/patient 1:1 or 1:2, adjusted Fewer nurses: RNs/patient 1:3 or 1:4, adjusted 

Length of staUnit H3.00 3.00 

Pronovost61

The Uniform Hospital Health discharge Data Set; in-hospital length of stay; in ICU length of stay; survey of ICU directors; average nurse to patient ratio in day, in evening. decreased nurse to patient ratio in evening 

Unit ICU Patients Surgical Hospitals 8  31  14  25 

Nurse to patient ratio <1:2 during the dayNurse to patient ratio >1:2 during the dayNurse to patient ratio <1:2 in evening Nurse to patient ratio >1:2 in evening 

Relative chanunit 1.49 1.17 1.00 1.00 Relative cha9.60 1.28.00 1.0

Ridge25

Patient survey 2 weeks after discharge with computerized phone interview system; length of stay in hospital; hospital administrative database, finance reports, Health Care Information Access database, unit nurse manager reports; educational level by degree learned: AD, BSN; number of individual staff 

hired annually/total number of staff, staffing adequacy - RN worked hours/RN target hours 

Hospitals 1 Unit Surgical Patients Surgical 

% BSN Experience % full time 44.00 8.70 86.00 

Length of sta4.10 ± 3.90 
Table G9. The association between nurse staffing and length of stay (continued)

G-91

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Shamian15

The National Comparative Database for Nursing Resource Consumption; average length of stay in unit. GRASP work Load Measurement System, The National Comparative Database for Nursing Resource Consumption; the amount of nursing services for each patient during 24 hours

Hospitals 58 

Rehabilitation units Psychiatric units Neonatal units Pediatric units Obstetrics Oncology Neurological Intensive Care Unit Medical surgical Orthopedics Cardiac step-down 

Length of sta24.8 12.5 14.0 3.7 3.0 7.9 6.6 3.8 6.6 6.1 6.0 

Shortell94

Hospitals discharge data; length of stay in unit for survivors (observed length of stay/expected length of stay) hospital administrative databases; survey of nursing directors in each unit 

Hospitals 40 Unit ICU Patients Medical 

Increase by 1 RN/patient ratio 

Relative cha1.06

Stratton91

Medical records, hospital incidence and infection control records, surveys; average length of stay in units; payroll records from the National Association of Children's Hospitals and Related Institutions (NACHRI); average in each quarter 2002 of total hours of productive nursing care/patient day adjusted for short-stay patients; average in each quarter 2002 of % of RN productive hours/total nursing hours/patient day; % of RN productive hours worked by supplemental nurse staffing (total nursing overtime hours and percentages of hours from float/agency/traveler RN hours) 

Hospitals Unit Patients 7 Combined Combined 7 Specialty Surgical 7 ICU Medical 

 Experience Medical/Surgical units 7.6 years Oncology units 6.6 years ICU units 8.3 years 

Length of sta3.58 ± 0.94 4.47 ± 0.77 6.48 ± 4.80 
Table G9. The association between nurse staffing and length of stay (continued)

G-92

Author, Definition of Length of 

Stay, Definition of Nurse Staffing 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories Le

Tschannen48

Patients medical records; patient's episode of care on the study unit; actual patients days were calculated as the time from admission to the time of discharge from the unit; nursing surveys, daily staff assignment sheets, census logs, and payroll records; proportion of RNs working in the unit; self reported years working in the present job category 

Hospitals 2 Unit ICU Patients Medical 

Experience in years 15.91 12.58 7.42 10.31 Increase by 1 hour in total nursing hoursIncrease by 1% in RNs 

Length of sta2.67 ± 2.20 2.83 ± 2.10 2.86 ± 2.20 3.11 ± 2.60 Relative cha1.18 0.97 

Unruh66

State Health Care Cost Containment Council; average length of stay in hospital. State Department of Health, American Hospital Association; total nurses FTE/1,000 APDC, RN FTE/ 1,000 APDC, LPN FTE/1,000 APDC 

Hospitals 211 Unit Combined Patients Medical 

Patient/RN % RNs 0.34 68.50 0.37 69.20 0.37 70.20 0.37 71.20 0.38 71.50 0.36 71.40 0.38 71.80 

Length of sta6.70 6.90 6.50 6.10 5.80 5.40 5.50 

Zidek85

Patient records and chart audits, individuals length of stay in the hospital, administrative records; total nursing hours/patient day; RN hours calculated from % of RN FTE/total FTE 

Hospitals 1 Unit Combined Patients Medical 

Nurse hours RN hours % RN  6.60 2.05 31.00  8.40 2.62 31.00  7.30 2.03 28.00  8.20 2.63 32.00  6.90 2.07 30.00  10.20 3.05 30.00  8.30 2.58 31.00  9.00 2.97 33.00  7.30 2.32 32.00  8.80 2.72 31.00  11.20 3.70 33.00  8.50 2.54 30.00 

APDC = Adjusted Patient Day Care; FTE = Full Time Equivalent; hrs = hours; ICU = Intensive Care Unit; LPN = Licensed Practical Nurs

LVN = Licensed Vocational Nurse; MSW = Master of Social Work; NICU = Neonatal Intensive Care Unit; NIW = Nursing Intensity Weigh

SD = Standard Deviation 
G-93

Table G10. Calculated change in hospital related mortality corresponding to an increase by 1 nursing hour/patient day (results 

Author 

Increase 

by 1 Nurse Hour 

Increase 

by 1 RN Hour 

Increase 

by 1 LPN Hour 

Increase 

by 1 UAP Hou

Death 

rate p value 

Death 

rate p value RR p value 

Death 

rate p value 

Death 

rate p va

Berney84 0.98 <0.05 Blegen59 NS NS Cho38 NS NS Mark90 1.01 NS Mark89 0.94 NS Needleman28 NS NS 1.00 NS NS NNeedleman29 NS NS 1.00 NS NS Seago34 0.98 <0.05 Thorson55 1.01 <0.05 

LPN = Licensed Practical Nurse; NS = Not Significant; RN = Registered Nurse; RR = Relative Risk; UAP = Unlicensed Assistive Person
G-94

Table G11. Evidence of the association between nurse hours/patient day and patient outcomes 

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

ANA65HCFA and MEDPAR national data sets; Urinary tract infections, bacterial unspecified pneumonia, pressure ulcers, postoperative infections, vascular complications, anoxic brain damage; communicable conditions; complications in post-partum period; diabetic complications; joint effusion; metabolic imbalances, personal care complications; psychiatric secondary diagnosis; transfusion reactions; trauma in non-trauma patients RN % of licensed hours

Hospitals 1,384 Unit Combined Patients Combined Increase by 1 hour in total nursing hours in New York, 1992 

Increase by 1 hour in total nursing hours in New York, 1994 Increase by 1 hour in total nursing hours in California, 1992 Increase by 1 hour in total nursing hours in California, 1994 Increase by 1 hour in total nursing hours in New York, 1992 Increase by 1 hour in total nursing hours in New York, 1994 Increase by 1 hour in total nursing hours in California, 1992 Increase by 1 hour in total nursing hours in California, 1994 

RelatiUTI NS NS NS NS Pneum1.00 1.00 1.00 1.08 

Archibald57

Retrospective review of patient and microbiology records from December 1994 through December 1995. The total number of nosocomial infections caused by Serratia marcescens; number of infections per 1,000 patient days. Retrospective review of administrative records from December 1994 through December 1995 RN hours worked by the registered nursing staff of this unit; monthly nursing hours/patient day ratio

Hospitals 1 Unit ICU Patients Combined Median RN hours/patient day,15.2 

Increase by 1 hour in RNs/patient day, 16.2 

Nosocpatien0.69 0.67 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-95

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Berney84

The New York Statewide Planning and Research Cooperative System Actual number of events identified as secondary DRG: Death among patients with shock, sepsis, pneumonia, deep vein thrombosis/ pulmonary embolism, or gastrointestinal bleeding The New York State Institutional Cost Reports RN total hours in inpatient cost units/patients days in units adjusted for nursing acuity

Hospitals 161 Unit Medical Patients Medical Patients Surgical Patients Medical Patients Surgical Patients Medical Patients Surgical Patients Medical Patients Medical 

1 hour increase in RN hours/patient day 1 hour increase in RN hours/patient day 1 hour increase in RN hours/patient day 1 hour increase in RN hours/patient day 1 hour increase in RN hours/patient day 1 hour increase in RN hours/patient day 1 hour increase in RN hours/patient day 1 hour increase in RN hours/patient day 

RelatiUrina0.99 0.98 Gastr- 0.95 Failur0.98 0.98 Sepsi0.96 0.97 

Blegen58

Comparative occurrence reporting service (CORS) The number of patient falls on the unit in quarter/1,000 patient days, the number of arrests on the unit in quarter/1,000 patient days Hospital reports (Institute for Quality Healthcare database) Hours of patient care for each unit provided by all personnel were added for each quarter and divided by patient days for that unit in that quarter

Hospitals 11 Unit Patients Combined Combined Combined Combined Neonatal Surgical ICU Surgical Combined Medical 

 Hours RN hours Mean of outcome in units 8.6 6.0 Increase by 1% in proportion of RN 1.1 Increase by 1 hour in total nursing care 1.0 Mean of outcome in units 5.7 2.1 Mean of outcome in units 11.3 9.9 Mean of outcome in units 18.0 16.2 Mean of outcome in units 10.8 7.8 

Rate Falls 0.27 -0.05 0.00 0.40 0.04 0.14 0.22 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-96

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Blegen73

Discharge databases of participating hospitals The number of patient falls on the unit in quarter/1,000patient days. Hospitals were members of the Institute for Quality Healthcare 

Hospitals 11 Unit Combined Patients Combined 

Total hours -11, RN hours -7.8 Increase by 1% of RN hours/total nursing hours Increase by 1 nurse hour/patient day Increase by 1% of RN hours/total nursing hours Total hours -11, RN hours -7.7

Falls 0.220 -0.028 -0.005 -0.019 0.270

Blegen59

Hospital records; The number of patient complaints standardized as a rate per 1,000 patient days, new incidences of skin breakdown secondary to pressure or exposure to urine or feces, suddenly and involuntarily leaving a position and coming to rest on the floor or some object. All reported falls were included whether or not injuries resulted, nosocomial infections that express themselves in hospitalized patients in whom the infection was not present or incubating at the time of admission. A record of hours worked for each individual employee was completed by the staffing clerk and approved by the employee and nurse manager before being entered into the computerized payroll database The hours of care per patient day from all nursing 

Hospitals 1 Unit Combined Patients Combined Acuity 4.19 

Increase by 1 hour in total nursing hours Total hours: 10.74, RN hours: 7.7 Increase by 1 hour in total nursing hours Total hours: 10.74, RN hours: 7.7 

Rate UTI  0.34 Falls 0.01 0.27 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-97

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

personnel: hours of direct patient care by RNs, LPNs, and nursing assistants each month divided by the patient days of care on the unit for the month The hours of direct patient care from RNs divided by patient days excluding hours for non patient care (meetings, vacation, sick leave, and holidays) Bolton26

California Nursing Outcomes Coalition database; the California Department of Health Services. Hospitalacquired pressure ulcers, unplanned descent to the floor in adult patients; the monthly fall rate per 1,000 patient days for each nursing unit and each hospital. Data are collected at the patient level and aggregated by CalNOC staff to the unit level. California Nursing Outcomes Coalition database; the California Department of Health Services Productive hours worked by the nursing staff who provide direct patient care on the defined unit RN hours/patient day % of UAP hours/total nursing hours 

Medical-surgical units ICU Hours RN hours LPN hours 

 8 4.7 0.88  16.8 15.3 1.51 

Rate/Falls  3.70  0.10 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-98

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Cheung32Incidence reports, quality referrals, and medical record coding stores in the database Excalibur system Pressure ulcers, falls, primary bloodstream infections after admitting the unit as secondary diagnosis. Automated Nurse staffing Office system and direct observation of nursing activities with Hill_Rom COMposer@nurse locator system Total nursing personnel on the unit for each shift including the number of RN, LPN, aides, and unit secretaries RN hours/patient day LPN hours/patient day Aide hours/patient day

Hospitals 1 Unit Combined Patients Medical 

Increase by 1 hour in total nursing hours Increase by 1 hour in total nursing hours Increase by 1 hour in total nursing hours 

RelatiDecubFalls Nosoc

Cho30,38

The State Inpatient Databases ICD-9-CM for UTI, pressure ulcers, falls and injury, surgical wound infection, sepsis, adverse drug event. Hospital Financial Data The total productive hours worked by all nursing personnel per patient day; the total productive hours by registered nurses per patient day

Hospitals-232 Unit Combined Patients Combined Age 67.9 Race 79.3 Sex 48.9 Severity 49.7 

RN hours/patient day Large, nonprofit, non-teaching, non-rural, 4 Large, nonprofit, non-teaching, non-rural ,5 Large, nonprofit, non-teaching, non-rural, 6 Large, nonprofit, non-teaching, non-rural, 8 Large, nonprofit, non-teaching, non-rural, 7 Medium, nonprofit, non-teaching, non-rural, 8 Medium, investor-owned, non-teaching, non-rural, 4 Medium, investor-owned, non-teaching, non-rural, 5 Medium, investor-owned, non-teaching, non-rural, 6 Medium, investor-owned, non-teaching, non-rural, 7 Medium, investor-owned, non-teaching, non-rural, 8 Medium, investor-owned, non-teaching, non-rural, 8 Large, nonprofit, teaching, non-rural, 5 Large, nonprofit, teaching, non-rural, 6 

Pneum2.06 1.88 1.72 1.43 1.57 1.33 2.09 1.91 1.74 1.59 1.45 2.16 1.98 1.81 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-99

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Large, nonprofit, teaching, non-rural, 8 Medium, nonprofit, non-teaching, non-rural, 4 Medium, nonprofit, non-teaching, non-rural, 5 Medium, nonprofit, non-teaching, non-rural, 6 Medium, nonprofit, non-teaching, non-rural, 7 Large, nonprofit, teaching, non-rural, 4 Large, nonprofit, teaching, non-rural, 7  Total hours RN hours Increase in 1 hour of total nurse hours large nonprofit teaching hospitals 10 7.2 Medium, nonprofit, non-teaching, non-rural 9 6 Large, nonprofit, non-teaching, non-rural 9 6.6 Medium, investor-owned non-teaching non-rural hospitals 9 6.2 Large nonprofit teaching hospitals 10 7.2 Medium, nonprofit, non-teaching, non-rural 9 6 Large, nonprofit, non-teaching, non-rural 9 6.6 Medium, investor-owned non-teaching non-rural hospitals 9 6.2 Large nonprofit teaching hospitals 10 7.2 Medium, nonprofit, non-teaching, non-rural 9 6 Large, nonprofit, non-teaching, non-rural 9 6.6 Medium, investor-owned non-teaching non-rural hospitals 9 6.2 Increase in 1 hour of total nurse hours Increase in 1 hour of RN hours Increase in 1 hour of total nurse hours Increase in 1 hour of RN hours Increase in 1 hour of total nurse hours Increase in 1 hour of RN hours Increase in 1 hour of total nurse hours 

1.51 1.91 1.75 1.59 1.45 2.17 1.65 UTI % 2.50 1.60 2.00 2.10 Falls 0.20 0.20 0.20 0 Pneum3.10 2.70 2.80 2.80 RelatiUrina1.02 1.01 Pneum0.96 0.91 Falls 1.08 1.07 Pulmo1.13 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-100

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase in 1 hour of RN hours Increase in 1 hour of total nurse hours Increase in 1 hour of RN hours Increase in 1 hour of total nurse hours Increase in 1 hour of RN hours

1.11 SWI 1.00 0.97 Sepsi1.01 1.02 

Cimiotti87

Patient discharges and medical records review by study's nurse epidemiologist Infections occurring in an infant 48 hours or longer after admission to the NICU including bloodstream infections, device associated pneumonia, CNS and skin infections, conjunctivitis; Nurse staffing office and signin/out sheet from each supplemental nursing agency; Total nursing hours worked by direct care providers adjusted for Nursing Intensity Weights categorized as below and above median RN hours/patient day adjusted for Nursing Intensity Weights categorized as below and above median 

Hospitals 1 Unit Neonatal ICU Patients Medical

NICU A, 10.7 nursing hours/patient day NICU B, 11 nursing hours/patient day Mean staffing levels, 10.8 nursing hours/patient day Low nursing hours, 8.7/patient day High nursing hours,12.9/patient day Low RN hours, 8.5 hours/patient day High RN hours, 12.7 hours/patient day NICU A, 10.7 nursing hours/patient day NICU B, 11 nursing hours/patient day Mean staffing levels, 10.8 nursing hours/patient day Low nursing hours, 8.7/patient day High nursing hours, 12.9/patient day Low RN hours, 8.5 hours/patient day High RN hours, 12.7 hours/patient day 

Sepsi10.50 5.50 1.00 2.56 1.38 3.71 1.74 % Pn 0.50 0.90 RelatiNosoc1.00 1.25 0.84 1.75 1.08 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-101

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Donaldson9

CalNOC database; Total number of patients with Stage I-IV pressure ulcers regardless of whether ulcer was acquired during hospitalization or present on admission;%/total number of surveyed patients, unplanned descent to the floor; rate/1,000 patient days. CalNOC database in 2004 and 2005 (after legislation); Productive hours worked by total nursing staff who have direct patient care responsibilities on the defined units and are included in the staffing matrix, total number of productive RN hours worked by all RNs (including contracted staff) with direct patient care responsibilities, total number of productive LPN hours worked by all LPNs (including contracted staff) with direct patient care responsibilities 

Hospitals 68 Unit Combined Patients Medical Medical surgical units, before mandatory ratios 

Hour RN hours licensed hours 8.08 4.76 5.44 Medical and surgical units after mandatory ratios Hour RN hours licensed hours 8.68 5.75 6.41 Step-down units before mandatory ratios Hour RN hours licensed hours 9.59 6.59 6.98 Step-down units after mandatory ratios Hour RN hours licensed hours 10.11 7.28 7.59 Medical surgical units before mandatory ratios Hour RN hours licensed hours 8.08 4.76 5.44 Medical and surgical units after mandatory ratios Hour RN hours licensed hours 8.68 5.75 6.41 Step-down units before mandatory ratios Hour RN hours licensed hours 9.59 6.59 6.98 Step-down units after mandatory ratios Hour RN hours licensed hours 10.11 7.28 7.59

Rate/Falls 0.31 ± 0.32 ± 0.30 ± 0.26 ± Press14.07 14.48 13.52 16.29 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-102

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Donaldson95California Nursing Outcomes Coalition (CalNOC) Hospital acquired pressure related skin injury controlling for date of admission, % of all patients on the day of prevalence study Patient’s unplanned descent to the hospital floor; were analyzed as 7 day aggregate per unit; also actual number per unit; the number of falls/1,000 patient days. The California Nursing Outcomes Coalition (CalNOC); hours worked by RNs, LPNs, and others (aides and other direct care providers) that have direct patient care responsibilities/ assignments on the defined unit and are included in the staffing matrix.

Hospitals 25 Unit Combined Patients Medical 

Increase by 1 hour in total RN hours/patient day Increase by 1 hour in total licensed hours of care/patient day Increase by 1 hour in total nursing hours patient day 

Rate/-0.02 -0.02 -0.01 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-103

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Fridkin1

Medical records of the patients in surgical intensive care unit. Cases were defined as any patient hospitalized >48 hours, in the SICU >24 hours who developed a laboratory confirmed CVCBSI during outbreak periods. Controls were randomly selected from all SICU patients; Laboratory confirmed catheter-associated bloodstream infections or clinical sepsis; rates were compared in pre- and outbreak periods. Hospital administrative records; RN hours/patient day

Hospitals 1 Unit ICU Patients Surgical Pre-outbreak period, 20 RN hours/patient day 

Outbreak period, 17 RN hours/patient day  RN hours Month's patient/nurse ratio = 1.2 20 Month's patient/nurse ratio = 1.5 16 Month's patient/nurse ratio = 2 12 Month's patient/nurse ratio = 1 24 

Rate/Nosoc1.95 4.96 Relati 3.95  15.60  61.50  1.00 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-104

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Kovner35

The National Inpatient Sample (NIS) Post operative discharges with urinary tract infection, pneumonia, pulmonary congestion, lung edema, or respiratory failure, and DVT in any secondary diagnosis. American Hospital Association Annual Survey of Hospitals, the part of the Health Care Utilization Project 

Hospitals 5,708 Unit Surgical Patient Surgical 

Increase by 1 hour in LPN hours/patient day Increase by 1 hour in LPN hours/patient day Increase by 1 hour in LPN hours/patient day Increase by 1 hour in LPN hours/patient day Year RN hours LPN hours 1990 5.84 1.24 1991 6.01 1.23 1992 5.9 1.13 1993 6.13 1.09 1994 6.13 1.01 1995 6.39 1.01 1996 6.56 0.97 1990 5.84 1.24 1991 6.01 1.23 1992 5.9 1.13 1993 6.13 1.09 1994 6.13 1.01 1995 6.39 1.01 1996 6.56 0.97

UTI, rPneumPulmoThromRate, UTI 3.77 3.75 3.84 3.72 3.81 3.57 3.68 Pulmo       
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-105

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Kovner22

The Nationwide Inpatient Sample of hospital discharges; UTI, gastrointestinal hemorrhage or ulceration, pneumonia, invasive vascular procedure, pulmonary congestion, lung edema, respiratory insufficiency or failure, DVT or PE, AMI as secondary diagnoses after surgery. American Hospital Association data RN FTE working in the hospital and outpatient departments/adjusted patient day, LPN FTE working in the hospital and outpatient departments/ adjusted patient day.

Hospitals 589 Unit Surgical Patients Surgical Reference 5.8 RN hours/adjusted patient day 

Increase by 0.5 RN hour/adjusted patient day Reference 5.8 RN hours/adjusted patient day Increase by 0.5 RN hour/adjusted patient day Reference 5.8 RN hours/adjusted patient day Increase by 0.5 RN hour/adjusted patient day Reference 5.8 RN hours/adjusted patient day Increase by 0.5 RN hour/adjusted patient day Increase by 1 LPN hour/patient day 

Rate Urina3.58 ± 3.42 ± Pneum0.95 ± 0.91 ± Pulmo0.82 ± 0.81 ± Deep 0.32 ± 0.31 ± All ou

Langemo41

The Midwest Research Institute/National Database of Nursing Quality Indicators; % of patients who had a pressure ulcer on a given day to all patients assessed for a pressure ulcer; pressure ulcers that occurred post admission were documented as hospital-acquired. The Midwest Research Institute/National Database of Nursing Quality Indicators; Total nursing hours/patient day 

Hospital 1 Patients Medical Unit ICU 

Medical-surgical units in hospitals with <100 bed Hours RN hours LPN hours 9.6 5 1.7 ICU in hospitals with 200-299 beds Hours RN hours LPN hours 18 17.6 0.1 ICU units in hospitals <100 beds Hours RN hours LPN hours 15 8.7 0.7 Medical-surgical units in hospitals with 200-299 beds Hours RN hours LPN hours 7.8 4.8 1.2 

Press4.10 0.00 13.10 0.00 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-106

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Langemo33

The North Dakota Nurses Association (NDNA) Research Council; Any lesion which is caused by unrelieved pressure that results in damage to underlying tissues; unplanned descent to the floor recorded in incidence reports. The North Dakota Nurses Association (NDNA) Research Council; Total number of productive hours worked by nursing staff with direct patient care responsibilities 

Hospitals 6 Unit ICU Patients Medical Age 61.9 Sex 41 

Acute care units 11 total nursing hours and 5.42 RN hours/patient day The authors compared the rate with published studies 

Press8.60 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-107

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Lichtig63

The Uniform Hospital Discharge Data Set; The California Office of Statewide Health Planning and Development; the Statewide Planning and Research Cooperative System Administratively Releasable file Urinary tract infection as the likely adverse patient outcomes of the hospital stay (secondary diagnosis), pneumonia as the likely adverse patient outcomes of the hospital stay (secondary diagnosis), pressure ulcers as the likely adverse patient outcomes of the hospital stay (secondary diagnosis), any secondary diagnosis of infection in surgical patients as the likely adverse patient outcomes of the hospital stay. The Annual Hospital Disclosure Report Institutional Cost Reports; Total RN hours per NIWadjusted patient day 

Unit Surgical Patients Surgical Hospitals 126 131 352 295 

Increase by 1 hour in total nursing hours in New York, 1992 Increase by 1 hour in total nursing hours in New York, 1994 Increase by 1 hour in total nursing hours in California, 1992 Increase by 1 hour in total nursing hours in California, 1994 Increase by 1 hour in total nursing hours in New York, 1992 Increase by 1 hour in total nursing hours in California, 1994 

RelatiUrinapneuminfectNS NS NS NS Rate, Press-17.89 -15.59 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-108

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Mark89

The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS); Risk-adjusted observed/expected urinary tract infections, pneumonias, decubitus ulcers. American Hospital Association Annual Survey, Online Survey Certification and Reporting System [OSCAR]; RN hours/patient * day = (FTE RN/1,000patient * days * 37.5 * 48) / 1,000 LPN hours/patient * day = (FTE LPN/1,000 patient * days * 37.5 * 48) / 1,000 

Hospitals 357 Unit Combined Patients Combined 

Year RN hours LPN hours 1990 5.4 1.2 1992 5.8 1.2 1992 5.7 1.2 1993 6.0 1.1 1994 6.3 1.1 1995 6.5 1.1 1990 5.4 1.2 1992 5.8 1.2 1992 5.7 1.2 1993 6.0 1.1 1994 6.3 1.1 1995 6.5 1.1 1990 5.4 1.2 1992 5.8 1.2 1992 5.7 1.2 1993 6.0 1.1 1994 6.3 1.1 1995 6.5 1.1 

RelatiUrina1.18 1.17 1.17 1.14 1.11 0.98 Pneum0.61 0.72 0.65 0.84 0.90 0.97 Decub0.48 0.58 0.51 0.62 0.69 0.74 

Needleman28

799 hospitals (11 states, allpatients + Medicare patients) – hospital level analysis; 256 California hospitals (part of the 11 state sample) – unit level analysis; National sample of 3,357 hospitals (Medicare patients) – hospital level analysis. Urinary tract infection coded in discharge abstract as secondary diagnosis, acute gastric ulcer, duodenal ulcer, peptic ulcer, gastrojejunal ulcer, hemorrhagic gastritis, 

Hospitals Patients 32 Medical 280 Medical 83 Medical 128 Medical 68 Medical 86 Medical 145 Medical 154 Medical 25 Medical 127 Medical 488 Medical 3,357 Medical 

Sample Hours RN hours LPN hours UAP hours Nevada 12.8 9.6 1.1 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Massachusetts 10.9 7.6 0.8 2.3 California 10.7 7.5 1 2.2 Medicare, medical patients  10.6 7.8 1.7 Medicare, surgical patients 

Rate Urina4.92 ± 5.67 ± 6.10 ± 6.14 ± 5.85 ± 6.27 ± 5.89 ± 7.46 ± 4.99 ± 5.52 ± 6.92 ± 8.81 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-109

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

erosive gastritis, unspecified GI-hemorrhage, esophageal hemorrhage coded in discharge abstract as secondary diagnosis, aspiration pneumonia 507.0, post-operative pneumonia 997.3, hypostatic pneumonia 514, bacterial pneumonia 482, bronchopneumonia 485, unspecified pneumonia 486 coded in discharge abstract as secondary diagnosis, cardiac arrest, shock without mention of trauma, shock, unspecified, cardiogenic shock. shock, other, respiratory arrest, nonmechanical methods of resuscitation, cardiopulmonary resuscitation, closed chest massage, death in patients with sepsis, pneumonia, GI bleeding, shock or DVT coded in discharge abstract as secondary diagnosis, pressure ulcers coded with ICD 682 and 707.0 in discharge abstract as secondary diagnosis, pulmonary congestion/ hypostasis, acute edema of lung, unspecified pulmonary insufficiency following trauma and surgery, respiratory failure, posttraumatic (958.3), postoperative (998.5), V. 

3,296 Surgical 127 Surgical 280 Surgical 83 Surgical 128 Surgical 68 Surgical 86 Surgical 145 Surgical 154 Surgical 25 Surgical 32 Surgical 488 Surgical 

 10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 California 10.7 7.5 1 2.2 Nevada 12.8 9.6 1.1 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Massachusetts 10.9 7.6 0.8 2.3 California 10.7 7.5 1 2.2 Medicare, medical patients  10.6 7.8 1.7 Medicare, surgical patients  10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 

7.75 ± 3.31 ± 3.01 ± 2.87 ± 3.49 ± 6.95 ± 3.62 ± 2.73 ± 4.05 ± 2.89 ± 2.80 ± 2.95 ± Gastr0.70 ± 1.05 ± 1.22 ± 0.96 ± 

0.52 ± 0.89 ± 0.84 ± 1.21 ± 0.81 ± 0.83 ± 1.18 ± 1.53 ± 1.37 ± 0.35 ± 0.49 ± 0.58 ± 0.38 ± 1.56 ± 0.44 ± 0.36 ± 0.49 ± 0.32 ± 0.59 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-110

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

illiaca-451.81, V. fem-451.11, V. pop.-451.19, post-op PE415.11, PE-415.1, DVT NEC453.8 coded in discharge abstract as secondary diagnosis, cardiac arrest, shock without mention of trauma, shock, unspecified cardiogenic shock, shock, other respiratory arrest, nonmechanical methods of resuscitation, cardiopulmonary resuscitation, closed chest massage, CNS complications (coma and stupor, acute delirium, reactive confusion, reactive depression); physiologic/metabolic derangement 

California 10.7 7.5 1 2.2 Nevada 12.8 9.6 1.1 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Massachusetts 10.9 7.6 0.8 2.3 California 10.7 7.5 1 2.2 Medicare, medical patients  10.6 7.8 1.7 Medicare, surgical patients  10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 California 10.7 7.5 1 2.2 Nevada 12.8 9.6 1.1 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 

0.48 ± Pneum2.61 ± 2.36 ± 2.38 ± 2.58 ± 1.89 ± 2.19 ± 1.89 ± 3.57 ± 2.01 ± 0.56 ± 2.54 ± 3.72 ± 3.42 ± 0.12 ± 0.98 ± 1.18 ± 1.32 ± 5.35 ± 2.00 ± 0.74 ± 1.56 ± 0.84 ± 1.68 ± 1.00 ± Shock 0.59 ± 0.57 ± 0.56 ± 0.52 ± 0.18 ± 0.49 ± 0.41 ± 0.48 ± 0.55 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-111

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Massachusetts 10.9 7.6 0.8 2.3 California 10.7 7.5 1 2.2 Medicare, medical patients  10.6 7.8 1.7 Medicare, surgical patients  10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 California 10.7 7.5 1 2.2 Nevada 12.8 9.6 1.1 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Massachusetts 10.9 7.6 0.8 2.3 California 10.7 7.5 1 2.2 Medicare, medical patients  10.6 7.8 1.7 Medicare, surgical patients  10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 

0.08 ± 0.80 ± 0.94 ± 1.23 ± 0.06 ± 0.39 ± 0.45 ± 0.35 ± 1.56 ± 0.27 ± 0.38 ± 0.50 ± 0.42 ± 0.83 ± 0.59 ± Failur18.68 22.62 18.83 16.54 13.63 19.05 16.15 16.10 16.76 14.74 18.98 19.97 22.75 13.02 20.88 20.72 19.51 22.48 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-112

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 California 10.7 7.5 1 2.2 Nevada 12.8 9.6 1.1 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Massachusetts 10.9 7.6 0.8 2.3 California 10.7 7.5 1 2.2 Medicare, surgical patients  10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 California 10.7 7.5 1 2.2 Nevada 12.8 9.6 1.1 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 

16.59 13.00 17.36 18.39 21.58 22.57 Decub6.31 ± 7.52 ± 9.01 ± 6.61 ± 5.22 ± 6.57 ± 4.57 ± 6.37 ± 4.43 ± 3.08 ± 9.20 ± Pulmo3.53 ± 0.18 ± 1.09 ± 1.57 ± 1.17 ± 2.19 ± 2.04 ± 0.72 ± 1.23 ± 1.09 ± 3.90 ± 1.24 ± Press6.31 ± 7.52 ± 9.01 ± 6.61 ± 5.22 ± 6.57 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-113

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Massachusetts 10.9 7.6 0.8 2.3 California 10.7 7.5 1 2.2 Medicare, medical patients  10.6 7.8 1.7 Medicare, surgical patients  10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 California 10.7 7.5 1 2.2 Nevada 12.8 9.6 1.1 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Massachusetts 10.9 7.6 0.8 2.3 California 10.7 7.5 1 2.2 Medicare, medical patients  10.6 7.8 1.7 Medicare, surgical patients  10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 

4.75 ± 6.37 ± 4.43 ± 3.08 ± 9.20 ± 6.78 ± 8.13 ± 2.99 ± 6.55 ± 7.07 ± 6.47 ± 6.97 ± 4.63 ± 2.87 ± 3.89 ± 4.11 ± 6.24 ± 6.93 ± Deep pulmo0.57 ± 0.48 ± 0.59 ± 0.50 ± 0.43 ± 0.40 ± 0.52 ± 0.64 ± 0.45 ± 0.34 ± 0.51 ± 0.68 ± 0.85 ± 0.19 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-114

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 California 10.7 7.5 1 2.2 Medicare, surgical patients  10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 California 10.7 7.5 1 2.2 Nevada 12.8 9.6 1.1 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Massachusetts 10.9 7.6 0.8 2.3 California 10.7 7.5 1 2.2 Medicare, medical patients  10.6 7.8 1.7 

0.44 ± 0.49 ± 0.36 ± 0.77 ± 0.36 ± 0.46 ± 0.41 ± 0.27 ± 0.77 ± 0.35 ± Surgic1.09 ± 0.85 ± 0.91 ± 0.91 ± 0.70 ± 0.38 ± 0.69 ± 0.73 ± 0.67 ± 0.72 ± 0.85 ± 0.83 ± Sepsi1.47 ± 1.30 ± 1.53 ± 1.04 ± 0.49 ± 1.12 ± 1.00 ± 1.10 ± 1.58 ± 0.35 ± 1.71 ± 1.33 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-115

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Medicare, surgical patients  10.6 7.8 1.7 Massachusetts 10.9 7.6 0.8 2.3 New York 11.3 7.2 1.2 2.8 Maryland 11.2 8.2 0.6 2.4 Virginia 12.2 8.6 1.9 1.9 West Virginia 11.8 7.1 2.2 2.9 South Carolina 11.7 7.7 2 2.2 Wisconsin 12.7 8.9 0.9 3 Missouri 12.7 8.9 0.9 2.9 Arizona 12.4 9.9 0.7 1.9 Nevada 12.8 9 1.1 2.3 California 10.7 7.5 1 2.2 Increase by 1 hour of RN hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in LPN hours in surgical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours in medical patients Increase by 1 hour in total nursing hours in surgical patients Increase by 1 hour in licensed hours/patient-day in medical patientsincrease by 1% of RN hours/total licensed hours per patient day in medical patients Increase by 1 hour in licensed hours/patient-day in surgical patientsIncrease by 1 hour in RN hours in medical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in licensed hours in medical patients Increase in total nurse hours in medical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN in surgical patients Increase by 1 hour in licensed hours in surgical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours Increase by 1 hour in RN hours in medical patients, hospital level analysis, California hospitals 

2.37 ± 0.15 ± 1.06 ± 1.35 ± 0.91 ± 1.30 ± 0.79 ± 0.65 ± 0.85 ± 0.94 ± 1.84 ± 1.19 ± Relati0.99 1.00 1.06 1.04 1.00 1.00 1.00 1.01 1.00 0.48 1.01 0.99 1.01 1.00 1.00 0.99 0.99 1.00 0.99 1.00 1.00 0.99 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-116

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 hour in LPN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of licensed nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours/patient-day in medical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, unit level analysis, California hospitals. Increase by 1 hour of total licensed hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, unit level analysis, California hospitals 

1.10 1.00 1.00 1.00 0.98 1.05 0.99 0.99 0.99 0.87 1.02 1.00 1.00 0.89 0.64 0.77 1.03 1.01 0.81 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-117

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 hour in licensed hours in surgical patients, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours (RN + LPN) Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 hour of RN in surgical patients Increase by 1 hour of RN in medical patients Increase by 1 hour of RN hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in LPN hours in surgical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours in medical patients Increase by 1 hour in total nursing hours in surgical patients Increase by 1 hour in licensed hours/patient-day in medical patientsincrease by 1% of RN hours/total licensed hours per patient day in medical patients Increase by 1 hour in licensed hours/patient day in surgical patients Increase by 1 hour in RN hours in medical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in licensed hours in medical patients Increase in total nurse hours in medical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN in surgical patients Increase by 1 hour in licensed hours in surgical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours Increase by 1 hour in RN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, hospital level analysis, California hospitals 

0.70 0.49 1.01 0.99 1.00 1.00 1.00 1.00 1.00 0.99 Gastr0.98 0.98 1.02 1.03 1.00 1.00 0.99 0.99 0.99 0.66 0.99 0.99 0.99 0.99 0.99 1.00 0.98 1.00 0.99 1.00 0.99 0.98 1.02 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-118

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 hour in UAP hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of licensed nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1hour of RN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours/patient-day in medical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, unit level analysis, California hospitals. Increase by 1 hour of total licensed hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, unit level analysis, California hospitals 

0.99 0.99 0.98 0.98 1.01 0.99 0.99 0.98 1.01 1.05 1.00 0.85 1.02 0.72 1.03 1.09 0.96 0.74 1.04 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-119

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

1% increase in RN hours/total licensed hours (RN + LPN) Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 hour of RN in medical patients Increase by 1 hour of RN hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in LPN hours in surgical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours in medical patients Increase by 1 hour in total nursing hours in surgical patients Increase by 1 hour in licensed hours/patient-day in medical patientsincrease by 1% of RN hours/total licensed hours per patient day in medical patients Increase by 1 hour in licensed hours/patient day in surgical patients Increase by 1 hour in RN hours in medical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in licensed hours in medical patients Increase in total nurse hours in medical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN in surgical patients Increase by 1 hour in licensed hours in surgical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours Increase by 1 hour in RN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, 

0.66 0.99 0.99 0.99 0.99 0.99 0.99 0.98 Pneum0.99 1.00 1.05 1.07 1.00 1.00 1.00 1.02 1.00 0.59 1.02 1.00 1.01 1.00 1.10 1.00 0.99 0.99 0.99 1.01 1.03 0.99 1.08 0.99 1.00 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-120

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

hospital level analysis, California hospitals Increase by 1 hour of licensed nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in medical patients, unit level analysis, California hospitals Increase by1 hour in LPN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours/patient day in medical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, unit level analysis, California hospitals. Increase by 1 hour of total licensed hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours (RN + LPN) Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day 

1.00 0.98 1.04 0.98 0.99 0.99 1.02 1.06 1.07 1.03 1.02 0.66 1.02 1.06 1.06 1.03 1.03 0.61 1.02 0.99 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-121

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 hour of RN in medical patients Increase by 1 hour of RN hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in LPN hours in surgical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours in medical patients Increase by 1 hour in total nursing hours in surgical patients Increase by 1 hour in licensed hours/patient-day in medical patientsIncrease by 1% of RN hours/total licensed hours per patient day in medical patients Increase by 1 hour in licensed hours/patient day in surgical patients Increase by 1 hour in RN hours in medical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in licensed hours in medical patients Increase in total nurse hours in medical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN in surgical patients Increase by 1 hour in licensed hours in surgical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours Increase by 1 hour in RN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of licensed nursing hours in medical patients, hospital level analysis, California hospitals 

1.02 1.00 1.00 1.00 0.99 Shock 0.98 0.99 1.07 1.04 1.02 0.98 0.84 0.99 1.00 0.46 1.00 0.99 1.03 1.00 1.00 1.03 0.99 1.03 1.00 1.01 1.00 0.97 1.17 1.08 1.02 1.00 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-122

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 hour of RN hour in medical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours/patient day in medical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, unit level analysis, California hospitals. Increase by 1 hour of total licensed hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours (RN + LPN) Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day 

0.97 1.08 1.08 1.01 0.99 0.97 1.18 1.01 1.00 0.99 0.22 1.55 1.21 1.94 1.01 1.68 0.49 1.00 1.00 1.00 1.00 1.00 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-123

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 licensed hour (RN +LPN)/patient day Increase by 1 hour of RN in medical patients Increase by 1 hour of RN hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in LPN hours in surgical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours in medical patients Increase by 1 hour in total nursing hours in surgical patients Increase by 1 hour in licensed hours/patient-day in medical patientsIncrease by 1% of RN hours/total licensed hours per patient day in medical patients Increase by 1 hour in licensed hours/patient day in surgical patients Increase by 1 hour in RN hours in medical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in licensed hours in medical patients Increase in total nurse hours in medical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN in surgical patients Increase by 1 hour in licensed hours in surgical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours Increase by 1 hour in RN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of licensed nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in medical patients, unit level analysis, California hospitals Increase by1 hour in LPN hours in medical patients, unit level 

1.00 0.98 Failur1.00 0.98 1.02 1.01 1.01 1.02 1.01 0.99 1.00 0.81 0.98 1.00 1.01 1.00 1.01 1.01 0.97 1.01 1.00 1.01 0.99 0.99 1.05 1.03 1.01 1.00 0.99 1.04 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-124

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

analysis, California hospitals Increase by 1 hour in UAP hours/patient day in medical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, unit level analysis, California hospitals. Increase by 1 hour of total licensed hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours (RN + LPN) Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 hour of RN in surgical patients Increase by 1 hour of RN in medical patients 

1.03 1.00 1.00 0.96 1.09 1.00 1.90 1.12 0.45 0.96 1.07 1.01 0.98 1.41 0.80 0.98 1.00 0.98 1.00 1.00 1.00 0.98 1.00 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-125

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 hour of RN hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in LPN hours in surgical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours in medical patients Increase by 1 hour in total nursing hours in surgical patients Increase by 1 hour in licensed hours/patient-day in medical patientsIncrease by 1% of RN hours/total licensed hours per patient day in medical patients Increase by 1 hour in licensed hours/patient day in surgical patients Increase by 1 hour in RN hours in medical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in licensed hours in medical patients Increase in total nurse hours in medical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN in surgical patients Increase by 1 hour in licensed hours in surgical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours in surgical patients Increase by 1 hour in RN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of licensed nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in medical patients, unit level analysis, California hospitals Increase by1 hour in LPN hours in medical patients, unit level analysis, California hospitals 

Deep pulmo1.01 1.03 0.97 1.01 1.01 1.01 1.00 1.02 1.01 1.39 1.03 1.00 0.99 1.00 1.00 1.00 1.00 0.97 1.00 0.99 1.01 1.00 0.91 1.01 1.00 0.99 1.02 0.50 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-126

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 hour in UAP hours/patient day in medical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, unit level analysis, California hospitals. Increase by 1 hour of total licensed hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours (RN + LPN) Increase by 1 hour of RN hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in LPN hours in surgical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours in medical patients Increase by 1 hour in total nursing hours in surgical patients Increase by 1 hour in licensed hours/patient day in medical patients 

1.04 1.02 1.01 1.07 1.05 1.02 1.06 1.07 0.03 1.11 1.09 1.03 1.09 1.55 Sepsi1.04 1.01 0.96 1.00 1.01 0.99 1.00 1.00 0.99 1.34 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-127

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1% of RN hours/total licensed hours per patient day in medical patients Increase by 1 hour in licensed hours/patient day in surgical patients Increase by 1 hour in RN hours in medical patients Increase by 1 hour in LPN hours in medical patients Increase by 1 hour in licensed hours in medical patients Increase in total nurse hours in medical patients Increase by 1 hour in UAP hours in medical patients Increase by 1 hour in RN hours in surgical patients Increase by 1 hour in LPN in surgical patients Increase by 1 hour in licensed hours in surgical patients Increase by 1 hour in UAP hours in surgical patients Increase by 1 hour in total nursing hours Increase by 1 hour in RN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of licensed nursing hours in medical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in medical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours/patient day in medical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of total licensed hours in medical patients, unit level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, hospital level 

1.01 1.00 0.98 0.99 0.99 1.01 0.99 0.98 0.96 1.01 0.99 1.01 0.96 1.02 1.01 1.00 1.02 0.96 1.02 1.01 1.01 1.01 1.00 1.02 0.59 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-128

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours in surgical patients, hospital level analysis, California hospitals Increase by 1 hour of RN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in LPN hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in UAP hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in total nursing hours in surgical patients, unit level analysis, California hospitals Increase by 1 hour in licensed hours in surgical patients, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours (RN + LPN) Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day Increase by 1 licensed hour (RN + LPN)/patient day

1.01 0.12 1.03 1.06 1.02 1.03 1.04 1.39 1.01 0.99 0.99 0.99 0.99 0.99 

Potter40

Medical records; (number of falls on a unit/number of patient days) * 1,000. Administrative hospital data; an average number of nursing care per patient day on the day shift, proportion of UAP hours of direct patient care

Hospitals 1 Unit ICU Patients Medical 

Period Hour RN hour Means in time period Feb-Apr 2000 3 1.67 Means in time period May-Jul 2000 3 1.61 Means in time period Aug-Oct 2000 3 1.69 Means in time period Nov 2000-Jan 2001 3 1.77 

Falls, 0.30 0.29 0.30 0.23 

Ritter-Teitel69

Hospital Incidence reports; % of patients with urinary tract infections not presented at admission among total discharged or sampled 

Hospitals 28 Time, Place Hour RN hours UAP hours 

1997 9.3 5.1 2.4 1998 9.6 5.3 2.6 Medical Units 1997 9.2 5.0 2.5 Medical Units 1998 9.8 5.5 2.7 

Rate, Urina2.09 ± 2.53 ± 2.25 ± 2.61 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-129

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

patients, % of patients with pressure ulcers, number of events/1,000 patient days. Labor Productivity Program Database and nurse survey; Total nursing hours worked/ patient-day, RN hours worked/patient day, UAP hours worked/patient day 

Surgical Units 1997 9.4 5.2 2.3 Surgical Units 1998 9.4 5.1 2.6 1997 9.3 5.1 2.4 1998 9.6 5.3 2.6 Medical Units 1997 9.2 5.0 2.5 Medical Units 1998 9.8 5.5 2.7 Surgical Units 1997 9.4 5.2 2.3 Surgical Units 1998 9.4 5.1 2.6 1997 9.3 5.1 2.4 1998 9.6 5.3 2.6 Medical Units 1997 9.2 5.0 2.5 Medical Units 1998 9.8 5.5 2.7 Surgical Units 1997 9.4 5.2 2.3 Surgical Units 1998 9.4 5.1 2.6 Increase by 1 hour in RN hours Increase by 1 hour in RN hours Increase by 1 hour in RN hours Increase by 1hour in RN hours in medical units Increase by 1hour in RN hours in surgical units 

1.93 ± 2.45 ± Falls 0.32 ± 0.34 ± 0.40 ± 0.41 ± 0.24 ± 0.27 ± Press2.42 ± 2.06 ± 2.33 ± 2.23 ± 2.50 ± 1.88 ± Urina-0.18 Falls -0.42 -0.24 Falls -0.49 -0.15 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-130

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Robert6

Case—all patients hospitalized in ICU >3 days with a primary BSI during the study period. Controls—randomly selected patients hospitalized ≥3 days in the 

same unit; primary bloodstream infections (BSIs) (CDC), Index date for casesthe day of 1 positive blood culture; for controls = (cases LOS before BSI/total cases LOS) * control total LOS. Administrative hospital data; total nursing hours-patient day

Hospitals 1 Unit ICU Patients Surgical 

 Hour/patient day Lower % of temporary nurses 13.5 High proportion of temporary nurses 12.8 Lower % of temporary nurses 13.5 High proportion of temporary nurses 12.8 

NosocRate/1.00 3.20 Relati1.00 3.20 

Seago93

Incident reporting system; Decubitus ulcers, rate/1,000 patient days. ANSOS/TSI database; Both RN and non-RN hours divided by total patient day, RN hours divided by total patient days 

Hospitals 1 Unit Combined Patients Medical 

 Nursing hours RN hours Medical surgical unit A 8 6 Medical surgical unit B 8 8 Medical surgical unit C 7 5 Medical surgical unit A 8 6 Medical surgical unit B 8 8 Medical surgical unit C 7 5 

Rate Decub0.78 ± 0.02 ± 0.05 ± Falls 0.35 ± 0.19 ± 0.45 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-131

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Simmonds82

Active microbiological surveillance of all chronic patients admitted for >30 days of hemodialysis; volunteering patient participation in other units % of patients with positive colonization of vancomycinresistant enterococci 48 hours after admission to the hospital and after surgery. Administrative reports of Patient Care Manager and Nursing Workload Specialist; Integrated Nursing System database; Total nursing FTE per shift * 8 hours/beds in the units

Hospitals 1 Unit Specialized Patients Medical Age 68.75 Sex 55.8 

Nursing hours RN hours  5.5 4.2  5.7 4.3  5.9 4.3  6.0 4.4  5.5  5.7  5.9  6.0 

Rate 1.61 3.29 4.97 6.65 1.56 1.33 1.11 1.11 

Sovie71Incident reports; nosocomial infection (not present at admission or within 72 hours after); the number of infections / number of patients discharged * 100 at hospital level, any lesions caused by unrelieved pressure not presented in admission; annual rate (%) at hospital level, any fall or slip in which a patient came to rest unintentionally on the floor; the ratio of the number of falls in a unit (or area) to the number of patient days * 1000. The MECON-PEERx 

Hospitals 29 Unit Combined Patients Combined 

Hospital nursing department, 1997 Nurse hours RN hours UAP hours  14 8.45 3 Hospital nursing department, 1998 Nurse hours RN hours UAP hours  13 8.09 3 Medical units, 1997 Nurse hours RN hours UAP hours  9.1 5.1 2 Medical units 1998 Nurse hours RN hours UAP hours  9.8 5.52 3 Surgical units, 1997 Nurse hours RN hours UAP hours  9.3 5.18 2 Surgical units, 1998 Nurse hours RN hours UAP hours  9.4 5.15 3 

Rate, UTI 2.64 ± 2.02 ± 2.17 ± 2.61 ± 1.87 ± 2.45 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-132

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Operations Benchmarking Database Reports; the office of the chief nurse executives; nursing survey; Hours Worked per patient day, RN hours worked per patient day, UAP hours worked per patient day 

Hospital nursing department, 1997 Nurse hours RN hours UAP hours  14 8.45 3 Hospital nursing department, 1998 Nurse hours RN hours UAP hours  13 8.09 3 Medical units, 1997 Nurse hours RN hours UAP hours  9.1 5.1 2 Medical units 1998 Nurse hours RN hours UAP hours 9.8 5.52 3 Surgical units, 1997 Nurse hours RN hours UAP hours  9.3 5.18 2 Surgical units, 1998 Nurse hours RN hours UAP hours  9.4 5.15 3 Hospital nursing department, 1997 Nurse hours RN hours UAP hours  14 8.45 3 Hospital nursing department, 1998 Nurse hours RN hours UAP hours  13 8.09 3 Medical units, 1997 Nurse hours RN hours UAP hours  9.1 5.1 2 Medical units 1998 Nurse hours RN hours UAP hours  9.8 5.52 3 Surgical units, 1997 Nurse hours RN hours UAP hours  9.3 5.18 2 Surgical units, 1998 Nurse hours RN hours UAP hours  9.4 5.15 3 

Falls 2.88 ± 2.95 ± 3.97 ± 4.11 ± 2.42 ± 2.69 ± Press3.53 ± 3.14 ± 2.61 ± 2.23 ± 2.68 ± 1.88 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-133

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Increase by 1 hour in RN hours Increase by 1 hour in total nursing hours Increase by 1 hour in total nursing hours Increase by 1 hour in total nursing hours 

Falls -0.43 UTI -0.65 Falls -0.33 Press-0.32 

Stegenga78Patients and laboratory records Nosocomial viral gastrointestinal infections (NVGIs) (CDC definition). Rate = number of NVGIs / 1,000 patient days. Administrative hospital records; Total nursing hours/patient day. Total hours included educational and overtime hours but not vacation. Total hours were calculated 72 hours before and after infection event 

Hospitals 1 Unit ICU Patients Medical 

 Nursing hours Preinfection night shifts 12.5 Postinfection night shifts 13 Nursing hours/patient days >10.5 12 Nursing hours/patient days <10.5 6.5 Nursing hours/patient days >10.5 12 Nursing hours/patient days <10.5 6.5 

Nosocpatien1.30 0.00 1.01 3.21 Relati1.00 2.94 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-134

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Stratton91

Medical records, hospital incidence and infection control records, surveys rate/1,000 patient days of respiratory, gastrointestinal, bloodstream and central line infections in hospitalized patients not present at time of admission; rate/1,000 patient days of bloodstream and central line infections in hospitalized patients not present at time of admission. Payroll records from the National Association of Children's Hospitals and Related Institutions (NACHRI); Average in each quarter 2002 of total hours of productive nursing care/patient day adjusted for short-stay patients 

Hospitals = 7 Units Medical/surgical units, quarter 1 Medical/surgical units, quarter 2 Medical/surgical units, quarter 3 Medical/surgical units, quarter 4 Oncology units, quarter 1Oncology units, quarter 2Oncology units, quarter 3Oncology units, quarter 4ICU units, quarter 1 ICU units, quarter 2 ICU units, quarter 3 ICU units, quarter 4 All units, quarter 1 All units, quarter 2 All units, quarter 3 All units, quarter 4 

Nursing hours RN hours LPN hours Aide hours  9.54 7.04 0.22 2.28  9.98 7.26 0.21 2.51  10.5 7.65 0.22 2.63  9.97 7.46 0.19 2.33  11.33 9.4 0.33 1.55  11.37 8.93 0.47 1.92  12.77 10.1 0.46 2.16  12.41 9.9 0.36 2.06  18.86 16.8 0.02 2.02  19.37 17.1 0.03 2.3  20.2 17.6 0.03 2.55  19.59 17.3 0.02 2.32  13.1  13.5  14.25  13.72 Increase by 1 hour in total nursing hours

NosocRate/0.75 ± 0.53 ± 0.71 ± 0.64 ± 0.65 ± 0.62 ± 0.71 ± 0.85 ± 0.73 ± 1.03 ± 0.80 ± 0.95 ± 0.51 ± 0.79 ± 0.66 ± 0.56 ± 0.01 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-135

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Tallier83

Hospital acquired retrospective data; Nosocomial urinary tract infection, incidence rate/1,000 patient day developed 72 hours after admission Pressure ulcers-Incidence rate/1,000 patient days developed more than 72 hours after admission. Nursing Care hours reports, Nursing Daily Staffing Sheets; total productive nursing hours/patient day 

Hospitals 1 Unit Combined Patients Medical 

Time Nurse hours RN hours LPN hours UAP hours2000, 4th quarter 5.84 

2001, 1st quarter 5.67 October 2000 6.2 5.85 0.87 3.58 November 2000 5.77 5.87 1 3.31 December 2000 5.76 5.5 0.93 3.29 January 2001 5.69 6.88 1.08 3.67 February 2001 5.27 6.64 1.04 3.29 

March 2001 6.05 6.83 1.11 3.41 2000, 4th quarter 5.84 

2001, 1st quarter 5.67 October 2000 6.2 5.85 0.87 3.58 November 2000 5.77 5.87 1 3.31 December 2000 5.76 5.5 0.93 3.29 January 2001 5.69 6.88 1.08 3.67 February 2001 5.27 6.64 1.04 3.29 

March 2001 6.05 6.83 1.11 3.41 

Rate/UTI 0.78 0.24 1.10 0.90 1.50 0.70 0.30 0.30 Press0.17 0.29 0.10 0.60 0.10 0.90 0.60 0.10 

Wan52Hospital records; Falls, incidence/1,000 patient days adjusted for severity of incident Hospital staffing records; Nursing hours/patient day, LPN hours/total nursing hours 

Hospitals 45 Unit Combined Patients Combined 

Increase by 1 hour in total nursing hours Nurse hours RN hours LPN hours  4.93 2.56 1.63 

Falls, 0.03 0.31 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-136

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Whitman36

Hospital discharge data; The number of hospitalacquired pressure ulcers (≥grade II) divided by the number of patients visually assessed by the nursing staff for skin breakdown; number of unplanned descents to the floor with or without injury times 1,000 divided by the total number of patient days on each unit; number of nosocomial CLI times 1,000 divided by the number of central catheter line days (the number of days central intravenous catheters were in place in patients). Hospitals system’s finance department; Total worked hours (paid hours minus sick, vacation, and holiday hours) for all personnel (RN, licensed practical nurses, nursing aides, secretaries): total worked hours/the monthly patient days for each unit

Hospitals: 10 Nurse hours 

Mean in noncardiac ICU 18.8 Mean in noncardiac ICU 18.9 Mean in noncardiac IMC 8.9 Mean in cardiac IMC 8.4 Mean in medical/surgical 4 Mean in noncardiac ICU 18.8 Mean in noncardiac ICU 18.9 Mean in noncardiac IMC 8.9 Mean in cardiac IMC 8.4 Mean in medical/surgical 4 

Rate/Falls 0.01 ± 0.07 ± 0.31 ± 0.35 ± 0.49 ± Press0.07 ± 0.11 ± 0.05 ± 0.03 ± 0.03 ± 
Table G11. Evidence of the association between nurse hours/patient day and patient outcomes (continued) 

G-137

Author, Source to Measure 

Patient Outcomes, 

Definition of Patient 

Outcomes, Source to 

Measure Nurse Staffing, 

Definition of Nurse Hours 

Number of Hospitals, 

Units, Patient Age, % 

of Whites, % of Males, 

% of Emergency 

Admissions 

Nurse Staffing Categories 

Zidek85

Patient records and chart audits New incidence of skin breakdown acquired over the course of the hospital stay, number of reported unplanned descent to the floor during the course of the hospital stay. Administrative records; total nursing hours/patient day calculated from % of RN FTE/ total FTE calculated from % of LPN FTE/total FTE calculated from % of UAP FTE/total FTE

Hospitals 1 Unit Combined Patients Medical and 

surgical 

 Nurse hours RN hours LPN hours UAP hours1999, 1st quarter 6.6 2.1 3.84 0.73 

1999, 2nd quarter 8.4 2.6 4.73 1.1 

1999, 3rd quarter 7.3 2 4.06 1.16 

1999, 4th t quarter 8.2 2.6 4.85 0.74 

2000, 1st quarter 6.9 2.1 4.14 0.69 2000, 2nd quarter 10.2 3.1 5.90 1.22 

2000, 3rd quarter 8.3 2.6 4.45 1.25 

2000, 4th quarter 9 3 5.13 0.9 

2001, 1st quarter 7.3 2.3 4.21 0.73 2001, 2nd quarter 8.8 2.7 5.09 0.96 

2001, 3rd quarter 11.2 3.7 6.17 1.35 

2001, 4th quarter 8.5 2.5 4.91 1.02 

Rate, Falls 0.59 0.45 0.83 0.52 0.28 0.25 0.23 0.63 0.61 0.62 0.66 0.66 

Dec Ulcer = Decubitus Ulcer; DRG = Diagnosis Related Group; DVT = Deep Vein Thrombosis; ICU = Intensive Care Unit; IMC = Interme

Licensed Practical Nurse; NICU = Neonatal Intensive Care Unit; NS = Not Significant; RN = Registered Nurse; RR = Relative Risk; SD = 

= Surgical Wound Infection; UAP = Unlicensed Assistive Personnel; UTI = Urinary Tract Infection
G-138 

Table G12. Patient outcomes corresponding to an increase by 1 nursing hour/patient day (calculated from 

published results, more studies contributed to pooled analysis) 

Studies Outcomes Measure Effect Significance 

Simmonds82 Nosocomial infection Rate NS 

Ritter-Teitel69 Pressure ulcers Rate 0.29 <.0001 

Ritter-Teitel69 Urinary tract infection Rate 0.30 <.0001 

Ritter-Teitel69 Falls Rate 0.08 <.0001 

Cho30 Sepsis Rate NS 

Cho30 Pressure ulcers Rate NS 

Cho30 Pneumonia Rate NS 

Cho30 Urinary tract infection Rate NS 

Cho30 Falls Rate NS 

Zidek85 Pressure ulcers Rate NS 

Zidek85 Falls Rate NS 

Tallier83 Pressure ulcers Rate* NS 

Tallier83 Urinary tract infection Rate* NS 

Cimiotti87 Sepsis Rate NS 

Cimiotti87 Nosocomial infection Rate NS 

Cimiotti87 Nosocomial infection Relative risk 0.92 0.001 

Cimiotti87 Pneumonia Rate NS 

Stratton91 Nosocomial infection Rate* 0.04 <.0001 

Blegen59 Nosocomial infection Rate* NS 

Blegen59 Urinary tract infection Rate* 0.24 0.010 

Blegen58 Falls Rate* NS 

Blegen58 CPR Rate* NS 

Robert6 Sepsis Rate* NS 

Robert6 Sepsis Relative risk NS 

Robert6 Nosocomial infection Rate* NS 

Robert6 Nosocomial infection Relative risk NS 

Blegen73 Falls Rate* 0.03 0.010 

Bolton26 Pressure ulcers Rate* NS 

Bolton26 Falls Rate* NS 

Sovie71 Pressure ulcers Rate 0.29 <.0001 

Sovie71 Urinary tract infection Rate 0.24 0.010 

Sovie71 Falls Rate NS 

Stegenga78 Nosocomial infection Rate* NS 

Stegenga78 Nosocomial infection Relative risk NS 

Whitman36 Pressure ulcers Rate* NS 

Whitman36 Falls Rate* -0.03 0.001 

Potter40 Falls Rate* NS 

Langemo41 Pressure ulcers Rate NS 

Seago93 Falls Rate* NS 

Donaldson9 Pressure ulcers Rate* NS 

Donaldson9 Falls Rate* -0.02 0.031 

Needleman28 Sepsis Rate NS 

Needleman28 Shock Rate NS 

Needleman28 Gastrointestinal bleeding Rate NS 

Needleman28 Pressure ulcers Rate NS 
Table G12. Patient outcomes corresponding to an increase by 1 nursing hour/patient day (calculated from 

published results, more studies contributed to pooled analysis) (continued) 

G-139 

Studies Outcomes Measure Effect Significance 

Needleman28 Surgical wound infection Relative risk NS 

Needleman28 Deep vein thrombosis Rate NS 

Needleman28 Pulmonary Failure Rate NS 

Needleman28 Pneumonia Rate NS 

Needleman28 Urinary tract infection Rate NS 

Needleman28 Failure to rescue Rate NS 

CPR = Cardiopulmonary Resuscitation; NS = Not Significant 

* Rate per 100 patient days
G-140

Table G13. Relative risk of patient outcomes corresponding to an increase by 1 nurse hour/patient day as reported by authors

Author Data 

Analytic 

unit Hospitals Unit Patients Outcome 

Relative 

Risk 95% CI 

Needleman28 Administrative Hospital 4,156 Medical Medical UTI 1.00 1.00; 1.01 Needleman28 Administrative Hospital 4,156 Surgical Surgical UTI 1.01 1.00; 1.02 Needleman28 Administrative Hospital 3,357 Medical Medical UTI 1.00 0.99; 1.01 Needleman28 Administrative Hospital 3,357 Surgical Surgical UTI 1.00 0.99; 1.02 Needleman28 Administrative Hospital 256 Medical Medical UTI 1.00 0.98; 1.01 Needleman28 Administrative Unit 256 Medical Medical UTI 0.99 0.97; 1.01 Needleman28 Administrative Hospital 256 Surgical Surgical UTI 1.00 0.98; 1.03 Needleman28 Administrative Unit 256 Surgical Surgical UTI 0.81 0.66; 0.98 Cho38 Administrative Patient 232 Combined Combined UTI 1.02 0.95; 1.08 Needleman28 Administrative Hospital 4,156 Medical Medical GIB 0.99 0.98; 1.01 Needleman28 Administrative Hospital 4,156 Surgical Surgical GIB 0.99 0.97; 1.01 Needleman28 Administrative Hospital 3,357 Medical Medical GIB 0.99 0.97; 1.00 Needleman28 Administrative Hospital 3,357 Surgical Surgical GIB 0.99 0.97; 1.02 Needleman28 Administrative Hospital 256 Medical Medical GIB 0.99 0.97; 1.01 Needleman28 Administrative Unit 256 Medical Medical GIB 0.99 0.96; 1.01 Needleman28 Administrative Hospital 256 Surgical Surgical GIB 0.85 0.67; 1.09 Needleman28 Administrative Unit 256 Surgical Surgical GIB 0.74 0.57’ 0.96 Needleman28 Administrative Hospital 4,156 Medical Medical Pneumonia 1.00 0.99; 1.01 Needleman28 Administrative Hospital 4,156 Surgical Surgical Pneumonia 1.02 1.00; 1.05 Needleman28 Administrative Hospital 3,357 Medical Medical Pneumonia 1.10 1.01; 1.19 Needleman28 Administrative Hospital 3,357 Surgical Surgical Pneumonia 1.03 1.00; 1.05 Needleman28 Administrative Hospital 256 Medical Medical Pneumonia 1.00 0.99; 1.01 Needleman28 Administrative Unit 256 Medical Medical Pneumonia 0.99 0.97; 1.01 Needleman28 Administrative Hospital 256 Surgical Surgical Pneumonia 1.03 1.01; 1.06 Needleman28 Administrative Unit 256 Surgical Surgical Pneumonia 1.03 0.99; 1.08 Cho38 Administrative Patient 232 Combined Combined Pneumonia 0.96 0.91; 1.01 Needleman28 Administrative Hospital 4,156 Medical Medical Shock 0.84 0.71; 0.99 Needleman28 Administrative Hospital 4,156 Surgical Surgical Shock 0.99 0.97; 1.01 Needleman28 Administrative Hospital 3,357 Medical Medical Shock 1.00 0.99; 1.02 Needleman28 Administrative Hospital 3,357 Surgical Surgical Shock 1.00 0.98; 1.03 Needleman28 Administrative Hospital 256 Medical Medical Shock 1.02 0.99; 1.04 
Table G13. Relative risk of patient outcomes corresponding to an increase by 1 nurse hour/patient day as reported by authors 

G-141

Author Data 

Analytic 

unit Hospitals Unit Patients Outcome 

Relative 

Risk 95% CI 

Needleman28 Administrative Unit 256 Medical Medical Shock 1.01 0.97; 1.05 Needleman28 Administrative Hospital 256 Surgical Surgical Shock 1.00 0.97; 1.03 Needleman28 Administrative Unit 256 Surgical Surgical Shock 1.01 0.97; 1.06 Needleman28 Administrative Hospital 4,156 Medical Medical Failure to rescue 1.01 1.00; 1.01 Needleman28 Administrative Hospital 4,156 Surgical Surgical Failure to rescue 0.99 0.98; 1.01 Needleman28 Administrative Hospital 3,357 Medical Medical Failure to rescue 1.01 1.00; 1.01 Needleman28 Administrative Hospital 3,357 Surgical Surgical Failure to rescue 0.99 0.97; 1.00 Needleman28 Administrative Hospital 256 Medical Medical Failure to rescue 1.01 0.99; 1.02 Needleman28 Administrative Unit 256 Medical Medical Failure to rescue 1.00 0.99; 1.02 Needleman28 Administrative Hospital 256 Surgical Surgical Failure to rescue 1.90 1.29; 2.79 Needleman28 Administrative Unit 256 Surgical Surgical Failure to rescue 0.98 0.95; 1.01 Cho38 Administrative Patient 232 Combined Combined Falls 1.08 0.99; 1.18 Needleman28 Administrative Hospital 4,156 Medical Medical Falls 1.00 0.99; 1.02 Needleman28 Administrative Hospital 4,156 Surgical Surgical Pressure ulcers 0.99 0.97; 1.02 Needleman28 Administrative Hospital 3,357 Surgical Surgical Pressure ulcers 0.99 0.97; 1.01 Needleman28 Administrative Hospital 256 Medical Medical Pressure ulcers 1.02 1.00; 1.04 Needleman28 Administrative Unit 256 Medical Medical Pressure ulcers 1.02 0.99; 1.05 Needleman28 Administrative Hospital 256 Surgical Surgical Pressure ulcers 0.82 0.64; 1.05 Needleman28 Administrative Unit 256 Surgical Surgical Pressure ulcers 0.64 0.46; 0.88 Needleman28 Administrative Hospital 4,156 Surgical Surgical SWI 1.00 0.99; 1.02 Needleman28 Administrative Hospital 3,357 Surgical Surgical SWI 1.01 0.99; 1.03 Cho38 Administrative Patient 232 Combined Surgical SWI 1.00 0.95; 1.06 Needleman28 Administrative Hospital 4,156 Medical Medical DVT 1.00 0.98; 1.02 Needleman28 Administrative Hospital 4,156 Surgical Surgical DVT 1.02 1.00; 1.05 Needleman28 Administrative Hospital 3,357 Medical Medical DVT 1.00 0.99; 1.02 Needleman28 Administrative Hospital 3,357 Surgical Surgical DVT 1.01 0.99; 1.04 Needleman28 Administrative Hospital 256 Medical Medical DVT 1.00 0.97; 1.02 Needleman28 Administrative Unit 256 Medical Medical DVT 1.02 0.98; 1.06 Needleman28 Administrative Hospital 256 Surgical Surgical DVT 1.06 1.02; 1.10 Needleman28 Administrative Unit 256 Surgical Surgical DVT 1.09 1.03; 1.15 Needleman28 Administrative Hospital 4,156 Surgical Surgical Complications 1.03 1.01; 1.06 Needleman28 Administrative Hospital 3,357 Medical Medical Complications 1.25 1.05; 1.50 Needleman28 Administrative Hospital 3,357 Surgical Surgical Complications 1.03 1.00; 1.06 
Table G13. Relative risk of patient outcomes corresponding to an increase by 1 nurse hour/patient day as reported by authors 

G-142

Author Data 

Analytic 

unit Hospitals Unit Patients Outcome 

Relative 

Risk 95% CI 

Needleman28 Administrative Hospital 256 Medical Medical Complications 1.02 0.99; 1.05 Needleman28 Administrative Unit 256 Medical Medical Complications 1.06 1.01; 1.10 Needleman28 Administrative Hospital 256 Surgical Surgical Complications 0.39 0.14; 1.13 Needleman28 Administrative Unit 256 Surgical Surgical Complications 1.10 1.03; 1.18 Needleman28 Administrative Hospital 4,156 Medical Medical Sepsis 1.00 0.98; 1.01 Needleman28 Administrative Hospital 4,156 Surgical Surgical Sepsis 1.00 0.98; 1.02 Needleman28 Administrative Hospital 3,357 Medical Medical Sepsis 0.99 0.98; 1.01 Needleman28 Administrative Hospital 3,357 Surgical Surgical Sepsis 0.99 0.97; 1.01 Needleman28 Administrative Hospital 256 Medical Medical Sepsis 1.01 0.99; 1.03 Needleman28 Administrative Unit 256 Medical Medical Sepsis 1.01 0.98; 1.04 Needleman28 Administrative Hospital 256 Surgical Surgical Sepsis 0.59 0.31; 1.14 Needleman28 Administrative Unit 256 Surgical Surgical Sepsis 1.03 0.99; 1.07 Cho38 Administrative Patient 232 Combined Medical Sepsis 1.01 0.95; 1.08 

DVT = Deep vein thrombosis; GIB = Gastrointestinal bleeding; SWI = Surgical wound infection; UTI = Urinary tract infection 
G-143 

Table G14. Patient outcomes corresponding to an increase by 1 RN hour/patient day (calculated from 

published results, more studies contributed to pooled analysis) 

Studies Outcomes Measure Effect Significance 

Simmonds82 Nosocomial infection Rate NS 

Ritter-Teitel69 Pressure ulcers Rate NS 

Ritter-Teitel69 Urinary tract infection Rate NS 

Ritter-Teitel69 Falls Rate NS 

Cho30 Sepsis Rate NS 

Cho30 Pressure ulcers Rate NS 

Cho30 Surgical wound infection Rate NS 

Cho30 Pneumonia Rate NS 

Cho30 Urinary tract infection Rate NS 

Cho30 Falls Rate NS 

Zidek85 Pressure ulcers Rate NS 

Zidek85 Falls Rate NS 

Tallier83 Pressure ulcers Rate* NS 

Tallier83 Urinary tract infection Rate* -0.70 0.019 

Cimiotti87 Sepsis Rate NS 

Cimiotti87 Nosocomial infection Rate NS 

Cimiotti87 Nosocomial infection Relative risk NS 

Cimiotti87 Pneumonia Rate NS 

Stratton91 Nosocomial infection Rate* 0.02 0.012 

Fridkin1 Sepsis Rate* NS 

Fridkin1 Sepsis Relative risk 0.71 <.0001 

Fridkin1 Nosocomial infection Rate* NS 

Fridkin1 Nosocomial infection Relative risk 0.71 <.0001 

Archibald57 Nosocomial infection Rate* NS 

Blegen58 Falls Rate* NS 

Blegen58 CPR Rate* 0.03 0.042 

Kovner22 Pulmonary failure Rate NS 

Kovner22 Pneumonia Rate NS 

Blegen73 Falls Rate* 0.04 0.010 

Bolton26 Pressure ulcers Rate* NS 

Bolton26 Falls Rate* NS 

Sovie71 Pressure ulcers Rate 0.32 0.032 

Sovie71 Urinary tract infection Rate NS 

Sovie71 Falls Rate NS 

Kovner35 Deep vein thrombosis Rate -0.11 <.0001 

Kovner35 Pulmonary failure Rate NS 

Kovner35 Pneumonia Rate NS 

Kovner35 Urinary tract infection Rate NS 

Kovner35 Urinary tract infection Relative risk NS 

Cho38 Sepsis Relative risk NS 

Cho38 Surgical wound infection Relative risk NS 

Cho38 Pulmonary failure Relative risk NS 

Cho38 Pneumonia Rate -0.16 <.0001 

Cho38 Pneumonia Relative risk NS 

Cho38 Urinary tract infection Relative risk NS 
Table G14. Patient outcomes corresponding to an increase by 1 RN hour/patient day (calculated from 

published results, more studies contributed to pooled analysis) (continued) 

G-144 

Studies Outcomes Measure Effect Significance 

Cho38 Falls Relative risk NS 

Potter40 Falls Rate* NS 

Langemo41 Pressure ulcers Rate NS 

Mark89 Pneumonia Relative risk NS 

Mark89 Urinary tract infection Relative risk NS 

Seago93 Falls Rate* NS 

Donaldson9 Pressure ulcers Rate* NS 

Donaldson9 Falls Rate* NS 

Needleman28 Sepsis Rate NS 

Needleman28 Shock Rate NS 

Needleman28 Gastrointestinal bleeding Rate NS 

Needleman28 Pressure ulcers Rate NS 

Needleman28 Surgical wound infection Rate NS 

Needleman28 Surgical wound infection Relative risk NS 

Needleman28 Deep vein thrombosis Rate NS 

Needleman28 Pulmonary failure Rate NS 

Needleman28 Pneumonia Rate NS 

Needleman28 Urinary tract infection Rate NS 

Needleman28 Failure to rescue Rate NS 

NS = Not significant 

* Rate per 100 patient days
G-145

Table G15. Relative risk of patient outcomes corresponding to an increase by 1 RN hour/patient day as reported by authors

Author Data 

Analytic 

Unit Hospitals Units Patients Outcomes 

Relative 

Risk 95% CI 

Berney84 Administrative Hospital 161 Medical Medical UTI 0.99 0.98; 1.01 Berney84 Administrative Hospital 161 Surgical Surgical UTI 0.98 0.96; 1.00 Needleman28 Administrative Hospital 4,156 Medical Medical UTI 0.99 0.98; 0.99 Needleman28 Administrative Hospital 4,156 Surgical Surgical UTI 1.00 0.98; 1.02 Needleman28 Administrative Hospital 3,,357 Medical Medical UTI 0.99 0.99; 1.00 Needleman28 Administrative Hospital 3,357 Surgical Surgical UTI 0.99 0.98; 1.00 Needleman28 Administrative Hospital 256 Medical Medical UTI 0.99 0.97; 1.00 Needleman28 Administrative Hospital 256 Medical Medical UTI 0.98 0.96; 1.00 Needleman28 Administrative Hospital 256 Surgical Surgical UTI 0.87 0.77; 0.99 Needleman28 Administrative Unit 256 Surgical Surgical UTI 0.77 0.59; 0.99 Cho38 Administrative Hospital 232 Combined Medical UTI 1.01 0.93; 1.08 Needleman28 Administrative Hospital 799 Combined Surgical UTI 1.00 0.98; 1.02 Needleman28 Administrative Hospital 799 Combined Medical UTI 0.99 0.98; 1.00 Berney84 Administrative Hospital 161 Surgical Surgical GIB 0.95 0.92; 0.99 Needleman28 Administrative Hospital 4,156 Medical Medical GIB 0.98 0.97; 0.99 Needleman28 Administrative Hospital 4,156 Surgical Surgical GIB 0.98 0.96; 1.01 Needleman28 Administrative Hospital 3,357 Medical Medical GIB 0.99 0.99; 1.00 Needleman28 Administrative Hospital 3,357 Surgical Surgical GIB 0.98 0.98; 0.99 Needleman28 Administrative Hospital 256 Medical Medical GIB 0.98 0.96; 1.00 Needleman28 Administrative Hospital 256 Medical Medical GIB 0.98 0.95; 1.01 Needleman28 Administrative Hospital 256 Surgical Surgical GIB 1.01 0.98; 1.05 Needleman28 Administrative Unit 256 Surgical Surgical GIB 1.03 0.98; 1.08 Needleman29 Administrative Hospital 799 Combined Medical GIB 0.98 0.97; 0.99 Needleman28 Administrative Hospital 4,156 Medical Medical Pneumonia 0.99 0.98; 1.00 Needleman28 Administrative Hospital 4,156 Surgical Surgical Pneumonia 1.00 0.98; 1.03 Needleman28 Administrative Hospital 3,357 Medical Medical Pneumonia 1.00 0.99; 1.00 Needleman28 Administrative Hospital 3,357 Surgical Surgical Pneumonia 0.99 0.98; 1.00 Needleman28 Administrative Hospital 256 Medical Medical Pneumonia 0.99 0.97; 1.01 
Table G15. Relative risk of patient outcomes corresponding to an increase by 1 RN hour/patient day as reported by authors (co

G-146

Author Data 

Analytic 

Unit Hospitals Units Patients Outcomes 

Relative 

Risk 95% CI 

Needleman28 Administrative Hospital 256 Medical Medical Pneumonia 0.98 0.96; 1.00 Needleman28 Administrative Hospital 256 Surgical Surgical Pneumonia 1.02 0.99; 1.04 Needleman28 Administrative Unit 256 Surgical Surgical Pneumonia 1.02 0.98; 1.07 Cho38 Administrative Hospital 232 Combined Medical Pneumonia 0.91 0.85; 0.97 Needleman29 Administrative Hospital 799 Combined Medical Pneumonia 0.99 0.98; 1.00 Needleman28 Administrative Hospital 4,156 Medical Medical Shock 0.98 0.96; 1.00 Needleman28 Administrative Hospital 4,156 Surgical Surgical Shock 0.99 0.96; 1.02 Needleman28 Administrative Hospital 3,357 Medical Medical Shock 0.99 0.98; 1.00 Needleman28 Administrative Hospital 3,357 Surgical Surgical Shock 0.99 0.98; 1.00 Needleman28 Administrative Hospital 256 Medical Medical Shock 0.97 0.94; 1.00 Needleman28 Administrative Hospital 256 Medical Medical Shock 0.97 0.92; 1.01 Needleman28 Administrative Hospital 256 Surgical Surgical Shock 0.97 0.94; 1.00 Needleman28 Administrative Unit 256 Surgical Surgical Shock 1.55 1.12; 2.15 Needleman29 Administrative Hospital 799 Combined Medical Shock 0.98 0.96; 1.01 Berney84 Administrative Hospital 161 Medical Medical Failure to rescue 0.98 0.97; 0.99 Berney84 Administrative Hospital 161 Surgical Surgical Failure to rescue 0.98 0.97; 0.99 Needleman28 Administrative Hospital 4,156 Medical Medical Failure to rescue 1.00 0.99; 1.01 Needleman28 Administrative Hospital 4,156 Surgical Surgical Failure to rescue 0.98 0.96; 0.99 Needleman28 Administrative Hospital 3,357 Medical Medical Failure to rescue 1.00 0.99; 1.00 Needleman28 Administrative Hospital 3,357 Surgical Surgical Failure to rescue 0.97 0.95; 1.00 Needleman28 Administrative Hospital 256 Medical Medical Failure to rescue 0.99 0.98; 1.00 Needleman28 Administrative Hospital 256 Medical Medical Failure to rescue 0.99 0.97; 1.01 Needleman28 Administrative Hospital 256 Surgical Surgical Failure to rescue 0.96 0.94; 0.99 Needleman28 Administrative Unit 256 Surgical Surgical Failure to rescue 0.96 0.92; 0.99 Needleman29 Administrative Hospital 799 Combined Surgical Failure to rescue 0.98 0.96; 0.99 Needleman29 Administrative Hospital 799 Combined Medical Failure to rescue 1.00 0.99; 1.01 Cho38 Administrative Hospital 232 Combined Medical Falls 1.07 0.96; 1.19 Needleman28 Administrative Hospital 4,156 Surgical Surgical Pulmonary failure 1.00 0.98; 1.02 Needleman28 Administrative Hospital 3,357 Surgical Surgical Pulmonary failure 1.00 0.99; 1.00 Needleman28 Administrative Hospital 256 Surgical Surgical Pulmonary failure 0.99 0.96; 1.02 
Table G15. Relative risk of patient outcomes corresponding to an increase by 1 RN hour/patient day as reported by authors (co

G-147

Author Data 

Analytic 

Unit Hospitals Units Patients Outcomes 

Relative 

Risk 95% CI 

Needleman28 Administrative Unit 256 Surgical Surgical Pulmonary failure 0.99 0.94; 1.04 Cho38 Administrative Hospital 232 Combined Combined Pulmonary failure 1.11 0.97; 1.27 Needleman28 Administrative Hospital 3,357 Surgical Surgical Pressure ulcers 0.99 0.97; 1.00 Needleman28 Administrative Hospital 256 Medical Medical Pressure ulcers 0.98 0.96; 1.01 Needleman28 Administrative Hospital 256 Medical Medical Pressure ulcers 0.99 0.98; 1.00 Needleman28 Administrative Hospital 256 Surgical Surgical Pressure ulcers 0.98 0.98; 0.99 Needleman28 Administrative Unit 256 Surgical Surgical Pressure ulcers 0.99 0.97; 1.02 Cho38 Administrative Hospital 232 Combined Medical Pressure ulcers 1.00 0.96; 1.03 Kovner35 Administrative Hospital 5,708 Surgical Surgical Pressure ulcers 0.87 0.75; 1.02 Needleman29 Administrative Hospital 799 Combined Surgical Pressure ulcers 1.04 0.99; 1.10 Needleman28 Administrative Hospital 4,156 Surgical Surgical SWI 1.00 0.99; 1.02 Needleman28 Administrative Hospital 3,357 Surgical Surgical SWI 1.02 1.01; 1.03 Cho38 Administrative Hospital 232 Combined Surgical SWI 0.97 0.91; 1.04 Needleman28 Administrative Hospital 4,156 Medical Medical DVT 1.01 0.99; 1.03 Needleman28 Administrative Hospital 4,156 Surgical Surgical DVT 1.03 1.00; 1.06 Needleman28 Administrative Hospital 3,357 Medical Medical DVT 1.00 0.99; 1.01 Needleman28 Administrative Hospital 3,357 Surgical Surgical DVT 1.00 0.99; 1.01 Needleman28 Administrative Hospital 256 Medical Medical DVT 1.00 0.98; 1.03 Needleman28 Administrative Hospital 256 Medical Medical DVT 1.02 0.98; 1.06 Needleman28 Administrative Hospital 256 Surgical Surgical DVT 1.07 1.03; 1.11 Needleman28 Administrative Unit 256 Surgical Surgical DVT 1.11 1.05; 1.17 Needleman28 Administrative Hospital 4,156 Surgical Surgical Complications 0.96 0.68; 1.35 Needleman28 Administrative Hospital 3,357 Medical Medical Complications 1.01 1.00; 1.02 Needleman28 Administrative Hospital 3,357 Surgical Surgical Complications 1.10 1.03; 1.19 Needleman28 Administrative Hospital 256 Medical Medical Complications 1.02 0.98; 1.05 Needleman28 Administrative Hospital 256 Medical Medical Complications 1.05 1.00; 1.10 Needleman28 Administrative Hospital 256 Surgical Surgical Complications 1.04 0.98; 1.10 Needleman28 Administrative Unit 256 Surgical Surgical Complications 1.10 1.02; 1.19 Berney84 Administrative Hospital 161 Medical Medical Sepsis 0.96 0.94; 0.98 Berney84 Administrative Hospital 161 Surgical Surgical Sepsis 0.97 0.95; 0.99 
Table G15. Relative risk of patient outcomes corresponding to an increase by 1 RN hour/patient day as reported by authors (co

G-148

Author Data 

Analytic 

Unit Hospitals Units Patients Outcomes 

Relative 

Risk 95% CI 

Needleman28 Administrative Hospital 4,156 Medical Medical Sepsis 1.04 1.01; 1.08 Needleman28 Administrative Hospital 4,156 Surgical Surgical Sepsis 1.01 0.98; 1.03 Needleman28 Administrative Hospital 3,357 Medical Medical Sepsis 1.00 0.99; 1.01 Needleman28 Administrative Hospital 3,357 Surgical Surgical Sepsis 0.99 0.98; 0.99 Needleman28 Administrative Hospital 256 Medical Medical Sepsis 1.01 0.99; 1.04 Needleman28 Administrative Hospital 256 Medical Medical Sepsis 1.02 0.98; 1.05 Needleman28 Administrative Hospital 256 Surgical Surgical Sepsis 1.01 0.98; 1.04 Needleman28 Administrative Unit 256 Surgical Surgical Sepsis 1.03 0.98; 1.08 Cho38 Administrative Hospital 232 Combined Medical Sepsis 1.02 0.95; 1.09 

DVT = Deep vein thrombosis; GIB = Gastrointestinal bleeding; SWI = Surgical wound infection; UTI = Urinary tract infection 
G-149 

Table G16. Patient outcomes corresponding to an increase by 1 LPN hour/patient day (effects reported by 

authors and calculated from published results, more studies contributed to pooled analysis) 

Studies Outcomes Measure Effect Significance 

Zidek85 Pressure ulcers Rate NS 

Zidek85 Falls Rate NS 

Tallier83 Pressure ulcers Rate* NS 

 Tallier83 Urinary tract infection Rate* NS 

Stratton91 Nosocomial Infection Rate* NS 

Bolton26 Pressure ulcers Rate* NS 

Bolton26 Falls Rate* NS 

Kovner35 Deep vein thrombosis Rate -0.31 0.003 

Kovner35 Pulmonary failure Rate -1.23 0.002 

Kovner35 Pneumonia Rate -1.69 0.002 

Kovner35 Urinary tract infection Rate NS 

Langemo41 Pressure ulcers Rate NS 

Mark89 Pneumonia Relative risk 0.13 0.004 

Mark89 Urinary tract infection Relative risk NS 

Needleman28 Sepsis Rate NS 

Needleman28 Gastrointestinal bleeding Rate NS 

Needleman28 Pressure ulcers Rate NS 

Needleman28 Surgical wound infection Rate NS 

Needleman28 Surgical wound infection Relative risk NS 

Needleman28 Deep vein thrombosis Rate NS 

Needleman28 Pulmonary failure Rate NS 

Needleman28 Pneumonia Rate 1.07 0.015 

Needleman28 Urinary tract infection Rate NS 

Needleman28 Failure to rescue Rate NS 

NS = Not significant 

* Rate per 100 patient days
G-150 

Table G17. Patient outcomes corresponding to an increase by 1 unlicensed assistive personnel hour/patient 

day (effects reported by authors and calculated from published results, more studies contributed to pooled 

analysis)

Studies Outcomes Measure Effect Significance 

Needleman28 Shock Rate NS 

Needleman28 Gastrointestinal bleeding Rate NS 

Ritter-Teitel69 Pressure ulcers Rate NS 

Zidek85 Pressure ulcers Rate NS 

Tallier83 Pressure ulcers Rate* NS 

Sovie71 Pressure ulcers Rate NS 

Needleman28 Pressure ulcers Rate NS 

Needleman28 Surgical wound infection Rate NS 

Needleman28 Surgical wound infection Relative risk NS 

Cimiotti87 Nosocomial infection rate NS 

Stratton91 Nosocomial infection Rate* NS 

Needleman28 Deep vein thrombosis Rate NS 

Needleman28 Pulmonary failure Rate NS 

Needleman28 Pneumonia Rate NS 

Cimiotti87 Pneumonia Rate NS 

Ritter-Teitel69 Urinary tract infection Rate 1.58 0.0001 

Tallier83 Urinary tract infection Rate* NS 

Sovie71 Urinary tract infection Rate NS 

Needleman28 Urinary tract infection Rate NS 

Needleman28 Failure to rescue Rate NS 

Ritter-Teitel69 Falls Rate NS 

Zidek85 Falls Rate NS 

Sovie71 Falls Rate NS 

NS = Not significant 

* Rate per 100 patient days
G-151

Table G18. Evidence of the association between nurse education and experience and patient outcomes 

Author, Definition of Patient 

Outcomes, Definition of Nurse 

Education and Experience 

Number of hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Education and Experience 

Categories 

Aiken39Failure to rescue: deaths within 30 days of admission among patients who experienced complications, Complications: the secondary diagnosis distinguished from preexisting co morbidities, Highest credential in nursing: a hospital school diploma, an associate degree, a bachelor's degree, a master's degree, or another degree; the mean number of years of experience working as an RN for nurses from each hospital 

Hospitals 168 Unit ICU Patients Surgical 

60% of hospital workforce with BSN or higher, 8 patients/day 40% of hospital workforce with BSN or higher, 4 patient/nurse 20% of hospital workforce with BSN or higher, 4 patients/nurse60% of hospital workforce with BSN or higher, 6 patients/nurse40% of hospital workforce with BSN or higher, 6 patients/nurse20% of hospital workforce with BSN or higher, 6 patients/nurse60% of hospital workforce with BSN or higher, 4 patients/nurse20-29% of hospital workforce with BSN or higher, experience 14.4 years <20% of hospital workforce with BSN or higher, 14.9 years 20% of hospital workforce with BSN or higher, 8 patients/nurse >50% of hospital workforce with BSN or higher, experience 12.5 years 40-49% of hospital workforce with BSN or higher, experience 14.3 years 30-39% of hospital workforce with BSN or higher, experience 14.0 years 40% of hospital workforce with BSN or higher 20-29% of hospital workforce with BSN or higher, experience 14.4 years <20% of hospital workforce with BSN or higher, 14.9 years >50% of hospital workforce with BSN or higher, experience 12.5 years 40-49% of hospital workforce with BSN or higher, experience 14.3 years 30-39% of hospital workforce with BSN or 

Falls, ra8.47 7.84 8.54 7.80 8.50 9.26 7.18 9.40 10.20 10.02 6.90 8.60 8.00 9.22 Complic22.90 22.90 25.20 22.00 22.80 
Table G18. Evidence of the association between nurse education and experience and patient outcomes (continued) 

G-152

Author, Definition of Patient 

Outcomes, Definition of Nurse 

Education and Experience 

Number of hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Education and Experience 

Categories 

higher, experience 14.0 years Increase by 1 year in nurse experience 10% increase in nurses with BSN degree

Failure t1.01 0.95 

Blegen73

The number of patient falls on the unit in quarter/1,000patient days, The proportion of RNs on the unit with BSN education, the proportion of RNs on the unit with more than 5 years experience or the average years of nursing experience of RNs on the unit 

Hospitals 11 Unit Combined Patients Combined 

Increase by 1 year in RN experience in unit Increase by 1% in proportion of RN with BSN Increase by 1% in proportion of RN with BSN Increase by 1% in proportion of RN with experience >5 years Nurse hours RN hours % BSN 10.7 7.704 47.00 

Falls, ra-0.04 0.01 -0.01 -0.01 0.27 ± 0

Langemo33

Any lesion which is caused by unrelieved pressure that results in damage to underlying tissues, unplanned descent to the floor recorded in incidence reports

Hospitals 6 Unit ICU Patients Medical Age 61.9 Sex 41 

Nurse hours RN hours % BSN Experience 10.9 5.42 59.5 11.0 

Pressur8.6 

Marcin3

Extubation – displacement of the endotracheal tube from the trachea by either the patient (self-extubation) or unplanned by medical personnel (e.g., when positioning a patient for a radiograph or procedure), The number of years of clinical experience in the PICU calculated from the time of starting work in the PICU to the middle of the study period 

Hospitals 1 Unit ICU Patients Combined Age 3.3 

1:2 nurse/patient ratio, experience 7.8 years 1:1 nurse/patient ratio, experience 7.0 years 7.8 years of nurse experience in ICU 7 years of nurse experience in ICU 

Relative 4.24 1.00 1.02 1.00 

Mark80

Number of incidents per 1,000 acuityadjusted patient days; average highest educational level attained by nurses on the unit; the average years of experience in nursing for nurses on the unit

Hospitals 64 Unit Combined Patients Medical 

% RN % BSN 58 21.00 

Falls, ra0.75 ± 0
Table G18. Evidence of the association between nurse education and experience and patient outcomes (continued) 

G-153

Author, Definition of Patient 

Outcomes, Definition of Nurse 

Education and Experience 

Number of hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Education and Experience 

Categories 

Sovie71Nosocomial urinary tract infection (not present at admission or within 72 hours after); the number of infections / number of patients discharged * 100 at hospital level; any fall or slip in which a patient came to rest unintentionally on the floor; the ratio of the number of falls in a unit (or area) to the number of patient days * 1,000; % of nurses with BSN; nursing experience in years 

Hospitals 29 Unit Combined Patients Combined Medical units Medical units Surgical units Surgical units Medical units Medical units Surgical units Surgical units Medical units Medical units Surgical units Surgical units 

 BS Years 1997 53.00 10.9 1998 52.70 11.2 1997 53.00 10.9 1998 52.70 11.2 1997 53.00 10.9 1998 52.70 11.2  BS Years 1997 53.00 10.9 1998 52.70 11.2 1997 53.00 10.9 1998 52.70 11.2  53.00 10.9  52.70 11.2  BS Years 1997 53.00 10.9 1998 52.70 11.2 1997 53.00 10.9 1998 52.70 11.2 1997 53.00 10.9 1998 52.70 11.2 

UTI, rate 2.64 ± 12.02 ± 12.17 ± 22.61 ± 21.87 ± 22.45 ± 2Falls, ra2.88 ± 12.95 ± 03.97 ± 24.11 ± 12.42 ± 12.69 ± 1Pressur3.53 ± 13.14 ± 22.61 ± 22.23 ± 12.68 ± 21.88 ± 1

BSN = Bachelor of Science in Nursing’ ICU = Intensive Care Unit; PICU = Pediatric Intensive Car Unit; RN = Registered Nurse; SD = Sta
G-154

Table G19. The association between nurse characteristics and patient outcomes 

Author, Definition of Nurse 

Characteristics and Patient 

Outcomes 

Unit, Number of Nurses, % of 

Whites, % of Females 

Nurse Categories Pa

Aiken4

Patient survey; patients satisfaction with nurse care in unit, nurses survey; burnout scale not reported on the article, nurses autonomy subscale

% of reported Burnout Adequate autonomy  26.73 70.8  21.48 75.45  21.9 84.8 

Patient satisScores ± SD 60.06 ± 8.09 64.41 ± 8.18 67.85 ± 9.08 

Dugan17

Incident reports; the number of reported patient falls occurred monthly during the study period; nurses survey to measure stress: a manifestation, evidences by behavioral, physical, and personal changes that were perceived by staff nurses and measured by the Stress Contunuum Scale (10 max stress) and Stress Survey Scores (max 268) 

Unit Nurses Combined 293 

% reported stress 20 45.5 53 58 63 68 85.5 

Falls, rate % 0.6 1 1.1 1.6 1.8 2.1 2.2 

Estabrooks50Hospital Inpatient Database, Alberta Health Care Insurance Plan Registry (AHCIPR) was linked to identify persons who died within 30 days of admission. Survey of RN (Alberta Association of Registered Nurses registry) working in acute care hospitals. Reponses for the Q "On the whole, how satisfied are you with your job?": 1. very dissatisfied; 2. a little dissatisfied; 3. moderately satisfied; 4. very satisfied); Q." Freedom to make important patient care and work decisions". Responses:1. Strongly disagree; 2. Somewhat disagree; 3. Somewhat agree; 4. strongly agree 

Unit Combined Nurses 4,799 

% satisfied % adequate autonomy  60.125  77.5  55.375  69.25 

Relative risk 1 0.85 1 0.79 
Table G19. The association between nurse characteristics and patient outcomes (continued) 

G-155

Author, Definition of Nurse 

Characteristics and Patient 

Outcomes 

Unit, Number of Nurses, % of 

Whites, % of Females 

Nurse Categories Pa

Halm51

The hospital's data warehouse with patient’s discharges; deaths within 30 days of admission, death following complications within 30 days). Survey of 140 staff nurses (42% response rate); Maslach Burnout Inventory Manual (max 6 scores) with 3 subscales of burnout: emotional exhaustion; depersonalization; personal accomplishment (feelings of competence and successful achievement in one's work), overall rating on a simple 4-point Likert scale, ranging from 1 (very dissatisfied) to 4 (very satisfied) and the likelihood to leave current position within the next 12 months, the 22-item Human Services Survey from the Maslach Burnout Inventory Manual to measure emotional exhaustion 

Unit Surgical Nurses 140 % females 96.4 

% Burnout % Satisfied % Stress  25 70 25 

Death rate % 1.2
Table G19. The association between nurse characteristics and patient outcomes (continued) 

G-156

Author, Definition of Nurse 

Characteristics and Patient 

Outcomes 

Unit, Number of Nurses, % of 

Whites, % of Females 

Nurse Categories Pa

Mark80

The hospital’s incident reporting system and patient survey; total patient days divided by the number of discharges. Patients’ satisfaction with nursing care; perceptions of the courtesy of the nursing staff; the ability of the doctors, nurses, and other staff to work together; their satisfaction with pain relief; and their level of comfort sharing concerns with nurses. Number of falls per 1,000 acuity-adjusted patient days. Administrative hospital data, nursing survey. Turnover as a ratio of the number of nurses who left during the period divided by the number of nurses employed at the end of the year; global satisfaction in the job (alpha = .84, a single factor explained 68% of the variance). Adequacy - the extent to which nurses on the unit felt free to engage in activities such as consulting with others about complex care problems, influencing standards of care, and acting on their own decisions related to caregiving. Availability of support services was evaluated with a 27-item, 3-point checklist 24 in which staff nurses (n = 1,682) indicated whether a variety of support services was available, not available, or inconsistently available (alpha =.85) 

Unit Medical Nurses 1,682 

Turnover Satisfaction Adequacy  17 54.25 47 Support Coordination Autonomy  50 50.33 73.2 

Length of st5.31 ± 1.47 % if satisfied 78.33 ± 7.5 Falls, rate/10.12 ± 0.09 
Table G19. The association between nurse characteristics and patient outcomes (continued) 

G-157

Author, Definition of Nurse 

Characteristics and Patient 

Outcomes 

Unit, Number of Nurses, % of 

Whites, % of Females 

Nurse Categories Pa

Minnick19

Patient survey with interviews within 26 days of hospital discharge using the Computer-Assisted Telephone Interview (CATI) system, reports about assistance with pain management. Unit labor quantity data and nurses survey: Manager's Ability to Involve Staff in Practice SelfGovernance. This variable is the average of the unit's RNs' rating (on a 5 point scale with 5 as most favorable) of the manager's ability to involve staff in setting patient care standards; the pay (score range 6-42), professional status (score 7-49), and task requirement attitude (score 6-42) scales (Stamps and Piedmonte) and the benefit (3 score 3-21) and schedule (score 4-28) scales (Minnick and Roberts); Central Hospital Support Systems Adequacy-the average of a RNs' ratings (on a 1 to 5 scale with 1 as least favorable) of hospital-wide support systems 

Increase in nurse job satisfaction by 10 scores

Patient satismanagemenRelative risk 1.22 

Ridge25

Patient survey 2 weeks after discharge with computerized phone interview system; length of stay in hospital; patient satisfaction measured with Likert-type 5 points scale from strongly disagree to agree for overall nursing care, pain management, overall hospital care. Hospital administrative database, finance reports, HCIA database, unit nurse manager reports; turnover - number of individual staff hired annually/total number of staff; staffing adequacy - RN worked hours/RN target hours 

Unit Surgical Nurses 22 % Females 92 

% Turnover 23.2 % Turnover 23.2 % Vacancy 9 % Turnover 23.2 % Vacancy 9 

Length of st4.1 ± 3.9 % satisfied 88 87.2 % satisfied 83.6 ± 16.6 83.2 ± 3.828 
Table G19. The association between nurse characteristics and patient outcomes (continued) 

G-158

Author, Definition of Nurse 

Characteristics and Patient 

Outcomes 

Unit, Number of Nurses, % of 

Whites, % of Females 

Nurse Categories Pa

Seago8Hospital incidence reports database at three time periods: time 1-third quarter fiscal year 1996 (FY96); time 2-second quarter fiscal year 1997 (FY97); and time 3-third quarter fiscal year 1997 (FY97) in three different cross-sections of patients, Patient satisfaction measured with Likert scale; the proportion of pressure ulcers per patient day; the proportion of falls per patient day. The nursing staffing system (ANSOS) and nursing survey at three time periods: time 1-third quarter fiscal year 1996 (FY96); time 2-second quarter fiscal year 1997 (FY97); and time 3-third quarter fiscal year 1997 (FY97).

% satisfied Coordination Autonomy  71 94.40  69 62.13 93.60  59 62.13 92.20 % satisfied Coordination Autonomy  71 94.40  69 62.13 93.60  59 62.13 92.20 

Relative risk Not significaFalls 0.29 0.27 0.23 

Sochalski45MedPAR dataset of hospital discharges; reported by RN frequency of medication errors and patients falls from “never in the past year” (score 1) to “occur frequently” (score 10). survey of RNs, the survey question “In general, how would you describe the quality of nursing care delivered to patients your unit on your last shift?,” and for which a 4-category response was available (poor, fair, good, excellent) 

Unit Combined Nurses 8,670 

Perceived quality of care, % satisfied 10 20 30 40 

Adverse eveRelative risk1.00 10.92 00.88 00.84 0
Table G19. The association between nurse characteristics and patient outcomes (continued) 

G-159

Author, Definition of Nurse 

Characteristics and Patient 

Outcomes 

Unit, Number of Nurses, % of 

Whites, % of Females 

Nurse Categories Pa

Sovie71Incident reports, patient survey 4 years after restructuring and reengineering in hospitals. The Picker Institute Patient Satisfaction Survey; the Press, Ganey Patient Satisfaction Survey. Dimensions: Pain management; Education; Attention to needs; Nursing care; Preparation for discharge. Nosocomial (not present at admission or within 72 hours after); the number of infections / number of patients discharged * 100 at hospital level; any fall or slip in which a patient came to rest unintentionally on the floor; the ratio of the number of falls in a unit (or area) to the number of patient days * 1,000. the MECONPEERx Operations Benchmarking Database Reports; the office of the chief nurse executives; nursing survey; achieving quality patient outcomes; ranged from 1 = strongly disagree to 5 = strongly agree 

Unit Nurses Age Sex Race Medical 347 36.9 92.8 79.6 Medical 298 36.7 92.3 82.4 Surgical 289 36.9 92.8 79.6 Surgical 239 36.7 92.3 82.4 

Management Quality Autonomy  66.8 74.4 47  66.8 72 47.25  65.6 74 49  65.6 72.2 49.25 Management Quality Autonomy  66.8 74.4 47  66.8 72 47.25  65.6 74 49  65.6 72.2 49.25 

% satisfied 83.6 ± 5.89 83.32 ± 5.67 82.82 ± 6.54 84.9 ± 6.99 

% satisfied w

83.04 ± 9.92 83.31 ± 7.82 85.55 ± 6.77 85.92 ± 4.63 

Vahey44

Conducted cross-sectional surveys of patients (621) satisfaction with nursing care using the La Monica-Oberst Patient Satisfaction Scale (LOPSS), 4 points scale. Conducted crosssectional surveys of nurses (N=820) with the Maslach Burnout Inventory (MBI);7 point scales, staffing adequacy , administrative support, 4 scores, emotional exhaustion, 7 point scales 

Unit Specialized Nurses 621 Age 34.6 Sex 7.4 Race 48.8 

Burnout Support Stress  80 20 20 Support 80 Burnout 20 Stress 80 

Patient satisReference 1.49 2.37 0.51 
Table G19. The association between nurse characteristics and patient outcomes (continued) 

G-160

Author, Definition of Nurse 

Characteristics and Patient 

Outcomes 

Unit, Number of Nurses, % of 

Whites, % of Females 

Nurse Categories Pa

Zidek85

Patient records and chart audits, individuals length of stay in the hospital, new incidence of skin breakdown acquired over the course of the hospital stay, number of reported unplanned descent to the floor during the course of the hospital stay, administrative records, quarterly turnover rate in % 

Unit Combined Nurses 1,759 

Turnover % 10.67 12.04 13.16 

Rate, % Falls Pre

2.79 1.58 2.95 

CI = Confidence Interval; RN = Registered Nurse; SD = Standard Deviation 
G-161

Table G20. The evidence of the association between nurse staffing and patient satisfaction 

Author, Measure of Patient 

Satisfaction 

Sample Size, Unit, Patients Nurse Categories Patient 

Aiken5

Twenty-one item scale based in part on the LaMonica/Oberst Patient Satisfaction Scale (LOPSS) 

Size 1,205 Unit Combined Patients Medical 

Increase by 1 RN Nurse control over practice setting Dedicated AIDS units AIDS hosp-scattered bed units Conventional scattered bed units 

Relative risk of bein3.0 0.0 343.8 1.4 1.4 2.5 3.6 0.3 41.3 0.1 0.0 2.0 1.0 1.0 1.0 

Aiken4

Patients satisfaction with nurse care in unit 

Size 1,205 Unit Spec Patients Medical 

Conventional general medical unit, Non-magnet hospital Specialized AIDS unit, non-magnet hospital General medical unit, magnet hospital 

% satisfied Scor74% 7.42 83% 8.29 85% 8.53 

Barkell77

Patient satisfaction: the patient’s perception of pain, and the frequency of documentation of pain scores measured by scores on the Parkside Patient Satisfaction Survey 

Size 96 Unit Surgical Patients Surgical 

Team nursing model with UAP assisting RNs in delivery of patient care (lower proportion of RN = 65.7%) Total patient care model (higher proportion of RNs = 78.5%) 

% Satisfied ± SD 83.4 ± 13 84.6± 13 

Blegen59

The number of patient complaints standardized as a rate per 1,000 patient days. 

Size 42 Unit Combined Patients Combined 

Increase by 1% in proportion of RNs Proportion of RNs >87.5% Increase by 1 hour in total nursing hours 10.74 nurse hours/patient day 

Rate of complains/100.46 ± 1.85 0.04 ± 0.07 0.02 ± 0.60 0.22 

Bolton42

The standardized Picker Institute inpatient questionnaire including respect patients’ values and preferences, coordination of care; information and education; pain management; emotional support, and transition and continuity to the home or community 

Size 113 Unit Combined Patients Combined 

Nurse hours/patient day 7.9 hours RN hours/patient day 4.4 hours % RN 56% 

% Satisfied with nurs86 ± 5% 
Table G20. The evidence of the association between nurse staffing and patient satisfaction (continued) 

G-162

Author, Measure of Patient 

Satisfaction 

Sample Size, Unit, Patients Nurse Categories Patient 

Langemo33

Patient’s satisfaction with nursing care and opinions of overall hospital care, pain management, and education from 42-item Patient Opinions of Nursing Care Survey 

Size 942 Unit ICU Patients Medical 

Nurse Hours/patient day 10.9 RN hours/patient day 5.42 % BSN 59.5 

Score for satisfaction 0.913 

Mark80

Patients’ satisfaction with nursing care; perceptions of the courtesy of the nursing staff; ability of the doctors, nurses, and other staff to work together; their satisfaction with pain relief; and their level of comfort sharing concerns with nurses 

Size 1,326 Unit Combined Patients Medical 

% RN 58 % BSN 21.00 

% Satisfied with care 78.33% Score of satisfaction 4.7 ± 0.45 

Minnick19

Reports about assistance with pain management; patient teaching was defined as reports of instruction that patients received about signs and symptoms that needed attention after hospital discharge 

Size 2,051 Unit Medical Patients Medical 

Patient satisfaction in units with >54% of RN with BSN vs. lower % of RN with BSN 

Relative risk of being 1.48 Relative risk of being management - Not s

Potter40

Eight Visual Analog Scale and post discharge (48 hour) satisfaction with seven satisfaction measures including communication, respect, coordination of care, nursing care, discharge process, advocating, and patient compassionate care (5 point Likert scale) 

Size 32 Unit ICU Patients Medical 

Nurse hours/patient day % RN 3.1 53.8 2.9 55.4 3 56.2 3.1 57.1 

% Satisfied with nurs75.4 74.2 77.3 75.6 
Table G20. The evidence of the association between nurse staffing and patient satisfaction (continued) 

G-163

Author, Measure of Patient 

Satisfaction 

Sample Size, Unit, Patients Nurse Categories Patient 

Ridge25

Likert-type 5-point scale from strongly disagree to agree for overall nursing care, pain management, and overall hospital care 

Size 1,076 Unit Surgical Patients Surgical 

% BSN Experience 44 8.70 Nurse hours/patient day % RN 6.9 67 Increase by 1 hour in LPN hours Increase by 1% in RN % BSN Experience 44 8.70 Nurse hours/patient day % RN 6.9 67 % BSN Experience 44 8.70 Nurse hours/patient day % RN 6.9 67 

Satisfaction with nurs4.3 ± 0.76 4.29 ± 0.14 0.65 0.893 % satisfied 88% 87.2% % satisfied with pain 84 ± 7 83 ± 3.8 

Ritter-Teitel69

satisfaction with nursing care and pain management during hospital stay (max 100 scores) 

Size 56 Unit Combined Patients Combined 

Nurse hours/patient day % RN 9.3 56.15 9.58 56.4 9.19 56.79 9.79 56.77 9.41 56.79 9.36 56.77 Increase by 1 hour in RN hours Nurse hours/patient day % RN 9.3 56.15 9.58 56.4 9.19 56.79 9.79 56.77 9.41 56.79 9.36 56.77 Increase by 1 hour in RN hours 

% satisfied with nurs82.68 ± 6.08% 84.38 ± 6.31% 83.29 ± 6.08% 83.82 ± 5.67% 82.08 ± 6.31% 84.9 ± 6.99% 1.18 ± 4.17% % satisfied with pain 84.1 ± 8.73% 84.6 ± 6.46% 83.1 ± 10.2% 83.3 ± 7.82% 85.3 ± 6.87% 85.9 ± 4.63% 1.50 ± 4.08% 

Seago8Patient satisfaction measured with Likert scale 

Size 89,256 Unit Combined Patients Medical 

Patient focused care % RN Before 63 After 61.5 After 62 

Relative risk of being Not significant Not significant Not significant 
Table G20. The evidence of the association between nurse staffing and patient satisfaction (continued) 

G-164

Author, Measure of Patient 

Satisfaction 

Sample Size, Unit, Patients Nurse Categories Patient 

Seago93

Patient satisfaction measured with Likert scale 

Size 1,012 Unit Combined Patients Medical 

Nurse hour %RN 8.1 75 8.3 96 7.49 72 Increase by 1 nurse hour Increase by 1% in RN Increase by 1 RN hour 

% satisfied with pain 84.2 ± 3.5% 89.3 ± 6.4% 80.5 ± 6.7% 2.44 ± 0.62 13.6 ± 3.6 2 ± 2 

Sovie71The Picker Institute Patient Satisfaction Survey; the Press, Ganey Patient Satisfaction Survey. Dimensions: pain management, education, Attention to needs, nursing care, preparation for discharge 

Size 29 Unit Combined Patients Medical Medical Surgical 

Nurse hour UAP hour % BSN 9.14 2.39 53.00 9.79 2.7 52.70 9.34 2.22 53.00 9.36 2.56 52.70 Increase by 1 RN hour Nurse hour UAP hour % BSN 9.14 2.39 53.00 9.79 2.7 52.70 9.34 2.22 53.00 9.36 2.56 52.70 Increase by 1 nurse hour Increase by 1 nurse hour 

% satisfied with nurs84 ± 5.9% 84 ± 5.7% 83 ± 6.5% 85 ± 7% 2.87 % satisfied with pain 83.04 ± 9.962 83.31 ± 7.862 85.55 ± 6.862 85.92 ± 4.662 -2.3 ± 1 -1.4 ± 0.3 

Tallier83

Patient opinion of care in hospital measured with Patient Satisfaction Survey (max 27 scores) 

Size 2,897 Unit Combined Patients Medical 

Nurse hours % RN 5.8 57 5.7 60 Nurse hours RN hours 6.2 5.9 5.8 5.9 5.8 5.5 5.7 6.9 5.3 6.6 6.1 6.8 

% satisfied 72% 72% 72% 72% 72% 77% 77% 77% 

RN = registered nurse; UAP = unlicensed assistive personnel; BSN = Bachelor of Science in Nursing; SD = Standard deviation 
G-165

Table G21. Research studies related to staffing ratios/hours/skill mix in acute care hospitals (not included in questions 1, 2, an

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Systematic reviews 

Lankshear 96 Assesses the 

evidence for a relationship between the nursing workforce and patient outcomes in acute hospitals through a systematic review of the literature 

22 international studies between 1990 and 2004 

Systematic review of literature 

Nurse staffing Patient outcomes 

22 studies remortality, faicommon comthat there is nurse staffinassociated woutcomes. Ncould not be association band patient oshow diminis

Lang97 Determine if peerreviewed literature 

supports minimum nurse-patient ratios for acute care hospitals and whether nurse staffing is associated with patient, nurse employee, and hospital outcomes 

43 studies between 1980 and 2003 

Systematic review of literature 

Nurse staffing Patient, nurse employee, and hospital outcomes 

43 studies rein-hospital arescue, inpapneumonia, pressure ulcoutcomes (nnurse burnodocumentatiabsenteeismprofessional(length of stastaffing modConcluded threlationships and failure to patients, inpevidence beand burnoutnurse documfinancial outcclinically signbetween nurstay. No supspecific, minratios, especadjustments 
Table G21. Research studies related to staffing ratios/hours/skill mix in acute care hospitals (not included in questions 1, 2, an

G-166

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Externally imposed staffing policies (mandated patient ratios) 

Seago98 Examine the 

relationship between nurse staffing and owner type or specific corporate entity 

Short-term general hospitals that reported in the California Office of Statewide Health Planning and Development’s (OSHPD) Hospital Disclosure report from 1997-1999 

Descriptive crosssectional design. Secondary data analysis using data from the California OSHPD Hospital Disclosure report (1997-1998). 

RN hours/patient day, RN-to-patient ratio, RN skill mix. LVN, aide, and total hours/patient day, patient days, discharges, RN/LPN/NA wages, percent Medicaid, Medicare case mix, length of stay, technology index, rural/urban location, proprietary status for hospital and system 

For profit hofewer RN promedical-surgdistinguished location, the longer signifRNs in for prdriven by onRN productivmore patient index and hi

Donaldson9 Examine the impact 

of mandated nurseto-patient ratios on unit-level nurse staffing, the incidence and patient outcomes 

California hospitals participating in the California Nursing Outcomes Coalition (CalNOC) N = 68 hospitals and 268 patient care units 

Descriptive, pre-post design CalNOC data collected at the point of service in real time by hospitals using current staffing data as well as the three patient outcomes. Pre-ratio baseline: first 6 months (2 quarters) of 2002 Post-ratio period: first 6 months (2 quarters) of 2004 following implementation of the licensed nurse-topatient ratios 

Nursing-care hours (RN, LVN, unlicensed productive hours); RN nursing care hours; LVN nursing care hours; non-RN and LVN caregiver care hours; contracted hours; skill mix; total patient days; patient falls incidence; hospital acquired pressure ulcer prevalence. 

Mean total Rpatient day imedical-surgimplementatratios; total nby 7.4%. Nulicensed nurimplementatnumber of padecreased bnoted to stepchanges in uChanges wehospital size There was nchange in ththe prevalenpressure ulcimplementatmandated ra
Table G21. Research studies related to staffing ratios/hours/skill mix in acute care hospitals (not included in questions 1, 2, an

G-167

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Hodge99 Develop baseline 

data on the characteristics, number, and distribution of licensed caregivers in specific units of acute care hospitals in California and determine how staffing varies across different types of acute care hospitals. 

Stratified random sample of general acute care hospitals in California. N = 80 hospitals; 2,298 nurses 

Cross-sectional descriptive design. Investigator developed survey instrument which was administered by RN surveyors. Data collected from hospital administrators, nurse managers, direct care staff nurses. 

Unit-related data: Duration of shifts, type of shifts, number of patients, nurses, unlicensed staff, admissions, discharges, patient care assignments, services provided by licensed nurses; experience, education, employment status and patient load of each nurse on duty on day of survey; staffing and skill mix data for all shift. 

Diverse nursCalifornia hoexperience, 50% of RNs baccalaureaproportion of unit ranging 84% (postpadiem and agmore than 20for emergenpost-partum academic mhospitals genpatients than hospital type

Studies with implications for staffing policies that were ineligible for meta-analysis 

McGillis Hall100 Evaluate the impact 

of different nurse staffing models selected patient outcomes. 

19 teaching hospitals in Ontario, Canada using adult medical-surgical and obstetric inpatients. N at admission: = 2,046 N at discharge = 1,811 N at 6 weeks post discharge = 1,483 

Repeated measure design Data collected from patients using a variety of instruments and data also collected by data collectors. Staffing data provided by nurse managers. Patient data collected at admission, discharge, and 6 weeks after discharge. 

Functional health outcomes (Functional Independence Measure; SF-36); Pain (Brief Pain Inventory Short Form); Patient perception of nursing care (Patient Judgment of Hospital Quality Questionnaire); Mix of staff on patient care units Continuity of patient care assignments 

A higher pronursing staff was associascores and bscores at hoNursing staff of RN/RPNspredictor of findependencfunctioning, with obstetric potential detoutcomes we
Table G21. Research studies related to staffing ratios/hours/skill mix in acute care hospitals (not included in questions 1, 2, an

G-168

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

McGillis Hall101 Determine if nurse 

staffing models and nursing demographic variables explain variation in quality outcomes. Determine if the influence of the nurse staffing model on the quality outcomes varies by type of care delivery model. 

77 adult medical, surgical and obstetrical patient care units in 19 urban teaching hospitals in Ontario, Canada. 1,116 nurses 

Descriptive correlational design Nurse staffing data collected through questionnaires to unit managers; Surveys distributed to RNs 

Nurse staff mix; Nursing care delivery models (total patient care, team nursing, primary nursing); Nurses’ perceptions of quality of care; Unit communication and coordination. 

There was a relationship staff models nurses’ perccare. A staff had a statistnegative influindividualizecoordination communicatopposite was that had both unregulated and URWs). 

McGillis Hall101 Examine the effect 

of different nurse staffing models on costs and patient outcomes. 

77 adult medical, surgical and obstetrical patient care units in 19 urban teaching hospitals in Ontario, Canada. 

Descriptive correlational design 

Four types of nursing staff mix (RN and RPN; all RN; proportion of URW to regulated workers (RNs and RPNs); RN/RPN//URW staff mix. Patient safety outcomes (patient falls, medication errors, wound infections, urinary tract infections); Case nursing hours (measure of nursing resource use); Patient complexity. 

Lower proponursing staff related to higmedication einfections. 

FIM = Functional independence measure; RN = Registered Nurse; RPN = Registered Practical Nurse; URW = unregulated workers 
G-169

Table G22. Research studies related to shift work of nurses (types of shifts; length of shifts) 

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Skipper102 Examine the 

relationship between the physical health and mental depression of nurse shift workers and relevant social and work related variables 

482 RNs working shifts in five hospitals in the southeastern region of the U.S. 

Descriptive survey Distributed questionnaires through the nurses’ hospital 

Physical health scale (e.g. quantity and quality of sleep; physical related problems); Depression measured by the CES-D scale; Family relation; Informal social participation (e.g. frequency visiting friends, relatives); Job performance measured by the SixDimension Scale of Nursing Performance; Job related stress scale. Covariates: age, marital status, number of children under age 6, education, work experiences, shift preferences, etc. 

When controvariables, thbetween diffshift work or and shift woassociated wparticipation shift nurses)activities (moshift nurses)(lowest percnurses workrelated stressignificantly rotating shiftstress). No abetween shifor depressiowith shift typsleep. Night least amountrouble sleep

Gold103 Examine the impact 

of work schedule on the sleep schedule, sleepiness, and accident rates of female nurses in a Massachusetts hospital based on a self-administered questionnaire administered in 1986. 

687 RNs and LPNs employed in one hospital 

Cross-sectional Self-administered questionnaire in which nurses kept records for two weeks regarding their work schedules and sleep patterns 

Nurses’ record of shifts worked for two weeks and sleep and wake times for the same two weeks. Nurses’ self-assessments of quality of sleep, sleepiness, automobile accidents or other injuries, medication, and procedural errors. 

Night nurses shifts (rotatopoorer qualitsleeping mereporting any higher for rodays or even
Table G22. Research studies related to shift work of nurses (types of shifts; length of shifts) (continued) 

G-170

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Ruggiero104 To determine 

variables contributing to chronic fatigue in critical care nurses and to determine if there are differences between critical care nurses working day and night shifts in regards to fatigue, depression anxiety, and quality of sleep. 

Subjects were members of the American Association of Critical Care Nurses. 67 worked the day shift and 75 worked the night shift. 

Descriptive, survey; two-group comparison Mailed survey 

Chronic shift worker fatigue measured by the Standard Shiftwork Index Chronic Fatigue Scale;Global sleep quality measured by the Pittsburgh Sleep Quality Index; Depression measured with the Beck Depresssion Inventory-II;Anxiety measured with the Beck Anxiety Inventory. Demographic data obtained regarding age, gender, shift, and schedule details. 

Permanent nmore depressleep qualitybetween day chronic fatigvariance in cexplained by sleep quality

Rogers105 To examine the 

work patterns of hospital staff nurses and determine if there is a relationship between hours worked and frequency of errors. 

393 RNs who were members of the American Nurses Association. Unit of analysis was number of shifts worked (5,317) over a 28-day reporting period. 

Descriptive; survey Mailed log book 

Nurse-reported data regarding hours worked (scheduled and actual), time of day worked, overtime, days off, sleep/wake patterns, mood, caffeine intake, errors and near errors. 

Participants minutes longday. Almost overtime 10 day period. Orespondents per week for day period. Mreported worleast once dwere 199 repreported neathe errors anmedication rmaking an ework hours awhen nurses hours or moovertime incat least one long the shif(OR = 2.06). increases whafter longer stype of unit derrors or nea
Table G22. Research studies related to shift work of nurses (types of shifts; length of shifts) (continued) 

G-171

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Trinkoff106 To describe the 

nature and prevalence of extended work schedules of nurses 

2,273 randomly selected RNs who participated in the NIOSH Nurses Worklife and Health Study 

Cross-sectional survey Mailed survey 

Work-schedule variables derived from the Standard Shiftwork Index hours worked per day and week; weekends worked/ month; days worked in a row; work more than one job; how off shifts are organized). Mandatory overtime requirement. Demographic characteristics.

When compahospital staff work 12 or mlikely to work more likely to Similarly, nuworked more more consecold and oldedays and wework days orequired to wcall requiremamong hosp

Havlovic107 Examine the impact 

of work schedule congruence on personal life interference and service to patients; examine the combined effects of the rotating shift and the compressed work week 

520 randomly selected nurses in British Columbia that returned the mailed survey. Nurses were members of the nurses’ union. 

Descriptive correlational Mailed survey 

Subscales from the Comprehensive WorkSchedule Survey (CWSS): Current Schedule Interference with Activities with Family & Friends; General Affect Toward Current Schedule; Service to External Constituents; Interference with Rest and Sleep. Nurse characteristics included full/part time status, shift and schedule currently working and preferred. 

Over 40% of compressed 47% were wshift and wotheir preferrepreferred weinterference positive geneschedule ansleep and rewas not signdependent vrotating comschedule expwith their pepatterns as wactivities, anwith their schquality servicNurses who (hospital factinterference rest and sleeNurses that hospital (nurto report negwork schedu
Table G22. Research studies related to shift work of nurses (types of shifts; length of shifts) (continued) 

G-172

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Hoffman108 Examine the 

variation in role stress and career satisfaction among hospital-based RNs by work shift length 

Probability sample of 208 nurses who were members of the Michigan Nurses Association (50.4% response rate). N = 99 working predominantly 8-hour shift pattern; N = 105 working 12 hours shifts or a combination of 8, 10, and 12 hour shifts. 

Descriptive comparative study Mailed questionnaires 

Role stress (Nursing Stress Scale) Career satisfaction (Index of Work Satisfaction) 

No significanbetween groshifts experielevels of strehour shifts; hfor nursing estress were fgroups were satisfaction acareer satisfwere significtheir current derived more professional 
G-173

Table G23. Research studies related to use of agency/contract nursing staff in hospitals 

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Hughes109 Examine differences 

between agency and hospital nurses as related to recruitment, retention, and compensation. 

6,895 staff nurses responding to a survey sent by a state’s Board of Nursing. Primary employer a staffing agency: n=3,360 Primary employer a hospital: n=3,535 (randomly selected) 

Descriptive; survey Survey sent out with nurses’ renewal of their license. 

Items from the survey regarding nurses’ nonsalary compensation package; issues related to recruitment and retention; conditions for willingness or need to increase current work hours. 

Hospital nursreceive pensdental insuracontinuing ecare servicenurses receihourly wagemore likely to benefits wouchange jobs were more liincreased audifference beterms of chascheduling, ssalary. Half oindicated thefor increased difference behospital nurswere willing hours for incincreases, chimprove relascheduling, pand improvenurses were their workloa
Table G23. Research studies related to use of agency/contract nursing staff in hospitals (continued) 

G-174

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Hughes110 Examine the 

sociodemographic characteristics of agency and hospital staff nurses and determine if there are differences in their work schedules and clinical practice. 

6,895 staff nurses responding to a survey sent by a state’s Board of Nursing. Primary employer a staffing agency: n=3,360 Primary employer a hospital: n=3,535 (randomly selected) 

Descriptive; survey Survey sent out with nurses’ renewal of their license. 

Items from the survey regarding nurses’ work schedules, practice activities/use of clinical skills, and perception of nurses regarding opportunities in their jobs to use the clinical skills. 

Agency nursmale, unmarminority groudegree, whewere more lieducation prAgency nurswork evening as weekend per week thanurses. Therdifferences iboth groups. performing mpsychologicagreater percAgency nursoutcomes, ddiagnoses amore patientdiffered signnurses in rega very or fairtheir skills; wfelt they had Agency nurssignificantly hospital nurs
Table G23. Research studies related to use of agency/contract nursing staff in hospitals (continued) 

G-175

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Warren111 To examine nurse 

managers’ use, perceptions of costs, benefits and quality of care of supplemental nursing staff. 

89 nurses in management positions in two urban and two rural hospitals randomly selected from 32 hospitals in a southeastern state. 

Descriptive; survey Mailed questionnaire 

Investigator developed questionnaire that queried the use of supplemental staffing and perceptions of the quality of care provided by supplemental staff nurses. Supplemental staff could be either agency-based or hospital-pool. 

While the mabelieved thanurses would they did not effective prarespondents staffing. The use was percare. Those supplementaresulted in reworkload for covering for absenteeismManagers’ pof supplemehospital pooversus agen

Strzalka112 To compare float 

pool nurses (FPN), agency nurses (AN), and unit-hired nurses (UHN) on selected clinical indicators. 

Over the course of 8 months, medical records associated with nurses on one nursing unit from each of the three groups were reviewed. 150 records were reviewed—50 from each group. Study was conducted in a large teaching hospital in the southeastern U.S. 

Descriptive comparative design 

Two clinical aspects of care were monitored: patient safety measures to prevent falls and assessment and management of bowel function. Patient flow sheets in the patients’ medical records were reviewed. 

Float pool nuof documentnurses and tThere were sdifferences bfor 3 of 5 indand a statistdifference be1 of 3 indicamanagemenANs and FPbowel mana
Table G23. Research studies related to use of agency/contract nursing staff in hospitals (continued) 

G-176

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Bloom18 Assess the effect of 

four nurse staffing patterns on the efficiency of patient care delivery: RNs from temporary agencies; part-time career RNs; RN rich skill mix; and organizationally experienced RNs 

Random sample of 1,222 hospitals selected; 583 hospitals in sample 

Descriptive correlational 

Nursing Personnel Survey which includes information about full and part time staff, use of agency staff, RN mix and experience. Merged data from the American Hospital Association’s annual survey of hospitals and the Area Resource File. Hospital efficiency was the dependent variable and measured as personnel costs per adjusted admission and total non-personnel operating costs per adjusted hospital admission. Control variables: hospital size, ownership/control; teaching status; occupancy rate; length of stay; geographic region; urban/rural status; regulatory intensity by state; local economic climate; hospital wage rates; hospital competition within a service area; supply of nursing labor within the community. 

Use of part-tlower personskill mix was and hospital RNs was nocosts but wahospital ope
G-177

Table G24. Research studies related to full- and part-time nursing staff 

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Jolma113 Examine the 

relationship between nursing workload and turnover. 

Randomly selected sample of medicalsurgical staff nurses employed in Arizona (n=270). 123 respondents with usable questionnaires. 

Descriptive correlational Mailed questionnaire 

Nursing workload was measured by the Role Overload subscale and intent to turnover was measured by the Intention to Turnover subscale, both part of the Michigan Organizational Assessment Questionnaire.Demographic questionnaire including information on full- and part-time status.

Full-time stand large uwith higher turnover in

Wetzel114 Comparison of 

personal and job characteristics and work-related attitudes of full-time and part-time registered nurses. 

Full and part time RNs employed in three large urban hospitals in a Canadian province. Stratified sampling technique to ensure representation of full- and part-time RNs. Questionnaire sent to 930 nurses with 634 responding. Eliminated nurses with less than a year of employment resulting in a final sample of 595. 

Descriptive comparative design Mailed questionnaires 

Job characteristics and work related attitude measures: organizational commitment; professionalism; job involvement; extrinsic and intrinsic job satisfaction, satisfaction with supervisor; difficulty leaving job; influence on decision making. No description provided of the questionnaire, reliability and validity. 

Part-time nmarried, haorganizatioStatistically job involvepart-time nwere signifThere was full- and paother work-

Porter115 Determine if there 

were self-image differences between beginning and expert nurses, caregivers and noncaregivers, educational levels of nursing and full-time and part-time staff. 

363 nurses in a midwestern hospital responding to a survey. 

Descriptive; comparative Method for distributing questionnaires not provided. 

Self image measured by Porter Nursing Image Scale (3 factors: interpersonal power; interpersonal relations; interpersonal ability) and demographic questionnaire 

More positfactors werversus parta statisticafor the inte(e.g. leadeindepende
Table G24. Research studies related to full- and part-time nursing staff (continued) 

G-178

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Bloom18 Assess the effect of 

four nurse staffing patterns on the efficiency of patient care delivery: RNs from temporary agencies; part-time career RNs; RN rich skill mix; and organizationally experience RNs 

Random sample of 1,222 hospitals selected; 583 hospitals in sample 

Descriptive correlational Secondary data 

Nursing Personnel Survey which includes information about full- and part-time staff, use of agency staff, RN mix and experience. Merged data from the American Hospital Association’s annual survey of hospitals and the Area Resource File. Hospital efficiency was the dependent variable and measured as personnel costs per adjusted admission and total nonpersonnel operating costs per adjusted hospital admission. Control variables: hospital size, ownership/control; teaching status; occupancy rate; length of stay; geographic region; urban/rural status; regulatory intensity by state; local economic climate; hospital wage rates; hospital competition within a service area; supply of nursing labor within the community. 

Use of partlower persoskill mix waand hospitaRNs was ncosts but whospital op
Table G24. Research studies related to full- and part-time nursing staff (continued) 

G-179

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Burke116 Examine the effects 

of hospital restructuring and downsizing on fulland part-time nursing staff. 

Randomly selected nurses employed in Ontario hospitals and members of a nurses union. N=1,362 Part time: 700 Full time: 645 

Descriptive, correlational Mailed questionnaire 

Personnel and situational characteristics which included whether the respondent worked full or part time. Restructuring and downsizing measures (extent of restructuring; workload; staff bumping; impact of generic workers). Threats to security (e.g. layoff, change of employment status to part time). Impact on staff and institutions (job insecurity feelings; impact of restructuring on hospital functioning; impact on hospital facilities). Implementation and management measures (fairness, communication, vision, staff participation, revitalization). Organizational support. Work outcomes (job satisfaction, intent to quit and absenteeism). Psychological well-being indicators (emotional exhaustion, cynicism, professional efficacy, psychosomatic symptoms, physical health, medication use, lifestyle habits) 

Full- and psignificantly demographcharacterismore expemore hours levels of edmarried). Teffects of drestructurintime nurses heavier wosimilar in rebut full-time to be abseFull-time nsignificantly exhaustionprofessionaburnout). Tto report pogreater melifestyles (p
Table G24. Research studies related to full- and part-time nursing staff (continued) 

G-180

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Havlovic107 Examine the impact 

of work schedule congruence on personal life interference and service to patients; examine the combined effects of the rotating shift and the compressed work week. 

520 randomly selected nurses in British Columbia that returned the mailed survey. Nurses were members of the nurses’ union. 

Descriptive correlational Mailed survey 

Subscales from the Comprehensive WorkSchedule Survey (CWSS): Current schedule Interference with activities with family & friends; general affect toward current schedule; Service to external constituents; interference with rest and sleep. Nurse characteristics including full- and part-time status, shift and schedule currently working and preferred 

Specific to of nurses, ntime reportquality servpresent woexperiencebetween thactivities. Ntime on a chave these 
G-181

Table G25. Research studies related to internationally educated nurses (IEN) 

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Crawford117 Compare processes 

of U.S. and IEN nurses’ experience to acquire licensure, and compare practice settings of U.S. nurses and IENs. 

Stratified random sample of 1,000 RNs educated in the U.S. and 1,000 RNs educated in targeted foreign countries (10% Philippines, 20% India, 10% Canada, 10% South Korea, 10% Nigeria, 10% England, 10% USSR, and 10% China) and who had successfully completed the NCLEX-RN examination. U.S. response rate = 570 (58.7%) IEN response rate = 401 (45.5%) 

Descriptive survey Potential responders were selected from the nurses who had successfully completed the NCLEX-RN examination between September 1 and November 30, 2002. A 4-stage mailing process was used to engage participants. Selected potential responders were sent the Practice and Professional Issues Survey (PPI) which is routinely used by the National Council of State Boards of Nurses to collect information from entry-level nurses of practice activities. 

Demographic data; description of process experienced by nurses to complete the application for U.S. RN licensure and secure a job; work settings, geographic locations. 

35% of IENwhen compnursing liceof time to creceive a Uwas 23 mothose using RNs secureU.S. before their home more likely care (29.8 units (42.7%work in meand nursing 

DiCicco-Bloom118 To describe the 

experiences of a group of immigrant women nurses regarding their life and work in a culture other than their own. 

Snowball sample initiated with the South Asian Nurses Association in New York state. 10 participants educated in India between the ages of 40-50, married, and lived in either Pennsylvania (n=3) or New Jersey (n=7). All were educated in India. 

Descriptive, qualitative design. Semi structured interviews with openended questions were used to evaluate for themes of life and work as reported by the female immigrants from India. 

Descriptive experiences of nurses educated in India and living and working in the U.S. as RNs 

The themeinterviews challenges cultures anexperiencetheir experfemale nur
Table G25. Research studies related to internationally educated nurses (IEN) (continued) 

G-182

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Flynn119 Examine differences, 

between cultures of the U.S. and international nurses regarding core values of nursing (autonomy, control over practice, and relationship with physicians); job satisfaction; and levels of burnout 

820 nurses who worked at least 16 hours per week on one of the 40 study units. N=252 international in origin N=547 U.S. in origin 

Comparative descriptive study using secondary data collected in 1991 from 40 inpatient care units in 20 hospitals located in 11 U.S. cities with a high incidence of AIDS. 

Country of origin (IV); values related to the professional nursing practice environment (Nursing Work Index-6 subscales); emotional exhaustion (Maslach Burnout Inventory) 

124 of the received thoutside of tNo differencountry of osubscales (control ovewith physichierarchy). found for th(autonomycollectivismprofessionaa significanexhaustioninternationa

Pizer120 Compare job 

satisfaction and demographics for U.S. and IEN in six New York City pubic hospitals. 

857 direct care nurses from six public hospitals in New York City. N=857 IEN nurses N=535 U.S. nurses 

Comparaitive study design. A two-part survey was developed for study by the Institute for Health Policy distributed to nurses. 

Demographics (e.g. education, shift worked, overtime, age, experience, unit type). Job satisfaction (Nurse Job Satisfaction Survey) 

Internationyounger andegree. Thmale, have and more ounits, and hRN that U.SNo differenwere found 

to do the joquality of cprovide. Thdifference fU.S. nurseenjoyment. disappearewho had poadministratdirect care Being a IEN explanation subscales 
Table G25. Research studies related to internationally educated nurses (IEN) (continued) 

G-183

Author, Year, 

Publication Type 

Aim of the Study Sample Study Design and 

Method 

Variables 

Xu121 Describe the 

demographic, educational, and employment characteristics of Internationally Educated Nurses (IENs) with comparison to U.S. trained nurses. 

35,579 nurses from the 2000 National Sample Survey of Registered Nurses; 3.7% of sample (1,300) were IENs. 

Descriptive study using secondary data from the 2000 National Sample Survey of Registered Nurses (NSSRN), 

Age, gender, education, employment (full time vs. part time; work hours) work setting and unit; position; income; job satisfaction, reasons for not working. 

IENs were nurses. Mo(38.9%), foIndia (10.9are more liprepared orespectivelfull time (73the IENs wtime and thwork part tidifference ithe two groleft nursing nurses (2.3

Yi122 Investigate how 

Korean nurses adjust to the U.S. hospital settings, the processes by which they adjust, and how their cultural background affects their adjustment process. 

Purposive sample of 12 Korean nurses working in the U.S. 

Exploratory study using a grounded theory method using semi-structured, indepth interviews. 

Experience of Korean nurses’ adjustment to U.S. hospitals. 

Adjustmentwo stagesis 2-3 years relieving psovercoming accepting Uyears for twU.S. styles strategies; interperson

USNs = U.S. trained nurses 
G-184

Table G26. Research related to nursing staff overtime 

Author, Year, 

Publication Type 

Aim of the 

Study 

Sample Study Design and 

Method 

Variables 

Shader123 Examine the 

relations between work satisfaction, stress, age, cohesion, work schedule, and anticipated turnover 

Staff nurses and nurse managers from 12 units in a 908-bed university hospital in the southeastern U.S. N = 241 

Descriptive study using a crosssectional survey design. Questionnaire distributed directly to nurses during work hours. 

Nurse work satisfaction (Index of Work Satisfaction) Job stress (modified version of the Job Stress Scale). Group cohesion (Bryne Group Cohesion Scale). Anticipated turnover (Anticipated Turnover Scale). Actual turnover (calculated as a ratio of the number of people who resigned to the average number of staff working for one year) Unit demographics (e.g., size of the unit, turnover data, patient satisfaction scores, overtime, acuity, ADC, staffing mix, and reallocation). Nurse demographics (e.g., age, gender, position, years of experience, tenure, education, shift worked). 

Specific tsatisfactiostress, anpredicted and expla
Table G26. Research related to nursing staff overtime (continued) 

G-185

Author, Year, 

Publication Type 

Aim of the 

Study 

Sample Study Design and 

Method 

Variables 

Berney124 To determine 

factors that influence overtime use among various hospitals and within the same hospitals from year to year 

General acute care hospitals in New York state that filed Institutional Cost Reports (ICR) 1995 to 2000. Over the five years, hospitals included in analysis ranged from 167 to 174 hospitals. Observations represented hospital years and varied from 1,008 to 1,028. 

Secondary data from cost reports 

Straight time and overtime hours; proportion of RN hours for acute inpatients that were overtime hours; ownership; location; teaching; unionization. 

RNs, on atheir total 2 hours/wweek. Mufound thaincrease time per pwith a 10% Occupancand hours week werovertime controlling variations hospital, hwere signhigher RN increase associateovertime. used 44% for-profit aHaving unassociateof overtim
Table G26. Research related to nursing staff overtime (continued) 

G-186

Author, Year, 

Publication Type 

Aim of the 

Study 

Sample Study Design and 

Method 

Variables 

Rogers105 To examine the 

work patterns of hospital staff nurses and determine if there is a relationship between hours worked and frequency of errors. 

393 RNs who were members of the American Nurses Association. Unit of analysis was number of shifts worked (5,317) over a 28 day reporting period. 

Descriptive; survey Mailed log book 

Nurse-reported data regarding hours worked (scheduled and actual), time of day worked, overtime, days off, sleep/wake patterns, mood, caffeine intake, errors and near errors. 

Participanminutes loeach dayworked ovduring the quarter of more than two or moperiod. Mreported wovertime days. Theerrors and More than near errorelated. Terror increhours and when nur12.5 hourWorking oodds of mregardlesoriginally risk of mawhen nurlonger shtype of unon errors 
Table G26. Research related to nursing staff overtime (continued) 

G-187

Author, Year, 

Publication Type 

Aim of the 

Study 

Sample Study Design and 

Method 

Variables 

Trinkoff106 To describe the 

nature and prevalence of extended work schedules of nurses. 

2,273 randomlyselected RNs who participated in the NIOSH Nurses Worklife and Health Study. 

Cross-sectional survey Mailed survey 

Work-schedule variables derived from the Standard Shiftwork Index hours worked per day and week; weekends worked/month; days worked in a row; work more than one job; how off shifts are organized). Mandatory overtime requirement. Demographic characteristics.

When comsample, hmost likelhours/day6-7 days/Similarly, one job wweek as wdays. Nurless likely were the days onlyrequired tovertime do so with There weprevalencamong howith the oworking mthose 50 parents wjobs with Those whmandatorsignificanrequiremeamong ho
Table G26. Research related to nursing staff overtime (continued) 

G-188

Author, Year, 

Publication Type 

Aim of the 

Study 

Sample Study Design and 

Method 

Variables 

O”Brien-Pallas125 Determine 

factors contributing to high RN injury claim rates in Canadian hospitals. 

127 hospitals in Ontario, Canada N = 8,044 RNs 

Cross-sectional study Secondary data (1998-99) 

Workload and staffing data (mandatory annual Ontario Ministry of Health and Long Term Care hospital submissions; Nursing lost-time injury claims data (Ontario Workplace Safety and Insurance Board database); Organizational (job dissatisfaction), nurse characteristics (age, health, missed shifts, emotional exhaustion, autonomy in practice, control over practice, nurse-physician relationships). 

High hosprates wereach quapercentagthan one 

Berney126 Examine trends 

in the use of overtime by hospitals to determine whether overtime has been increasing more rapidly in some kinds of hospitals than in others. 

150 hospitals in New York State 

Secondary data from cost reports 

Straight time and overtime hours; proportion of RN hours for acute inpatients that were overtime hours; ownership; location; teaching; unionization. 

Overtime 1995-200more in nhospitals hospitals. 
G-189

Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes 

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

ANA56An average hospital rate of nosocomial pneumonia, urinary tract infections, postoperative infections as secondary diagnoses in surgical patients; % RN Hours/total nursing hours 

Hospitals 131 Unit Combined Patients Combined Increase by 1% in RNs in New York, 1992 

Increase by 1% in RNs in New York, 1994 Increase by 1% in RNs in California, 1992 Increase by 1% in RNs in California, 1994 Increase by 1% in RNs in New York, 1992 Increase by 1% in RNs in New York, 1994 Increase by 1% in RNs in California, 1992 Increase by 1% in RNs in California, 1994 Increase by 1% in RNs in New York, 1992 Increase by 1% in RNs in New York, 1994 Increase by 1% in RNs in California, 1992 Increase by 1% in RNs in California, 1994 Increase by 1% in RNs in New York, 1992 Increase by 1% in RNs in New York, 1994 Increase by 1% in RNs in California, 1992 Increase by 1% in RNs in California, 1994 

ReU1.0.0.0.PnRa0.0.-0-0PrRa-1-1-0-1NoRa0.0.-0-0
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-190

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Barkell77

The incidence of urinary tract infection: a) presence of white blood cells >100/high-powered field (HPF) on urinalysis, b) bacteria 3+/ high-powered field F or 4+/ high-powered field on urinalysis, and c) urine culture showing >100,000 colonies of one or two (not three or more) organisms; the incidence of pneumonia; proportion of RN/ total nursing staff.

Hospitals 1 Unit Surgical Patients Surgical Race 88.1 Sex 40.7 

Team nursing model with patient care associate assisting RNs in delivery of patient care (lower proportion of RN: 65.8%) Total patient care model, higher proportion of RN: 78.6%) 

Pn5.0 

Berney84

Actual number of urinary tract infections, gastrointestinal bleeding, and sepsis events identified as secondary DRG; RN acute hours/(RN + LPN acute hours)

Hospitals 161 

1% increase in RN hours/total licensed hours, medical patients 1% increase in RN hours/total licensed hours, surgical patients 1% increase in RN hours/total licensed hours, medical patients 1% increase in RN hours/total licensed hours, surgical patients 1% increase in RN hours/total licensed hours, medical patients 1% increase in RN hours/total licensed hours, surgical patients 

ReU1.1.G1.1.Se1.1.

Blegen58

The number of patient falls on the unit in quarter/1,000 patient days; the number of CPR on the unit in quarte/1,000 patient days; RN hours per patient day divided by all hours per patient day

Hospitals 11 Unit Combined Patients Combined 

Increase by 1% in proportion of RN Increase by 1% in proportion of RN 

RaSD Fa-0C-0
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-191

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Blegen73

The number of patient falls on the unit in quarter/1,000patient days; RN hours per patient day divided by all hours per patient day

Proportion of BSN 73% 72% 

RaFa0.0.

Blegen59

New incidences of skin breakdown secondary to pressure or exposure to urine or feces; suddenly and involuntarily leaving a position and coming to rest on the floor or some object. All reported falls were included whether or not injuries resulted. RN hours per patient day divided by all hours per patient day 

Hospitals 1 Unit Combined Patients Combined Increase by 1% in proportion of RN nurses 

Proportion of RN >87.5% Increase by 1% in proportion of RN nurses Proportion of RN >87.5% Increase by 1% in proportion of RN nurses Proportion of RN >87.5% 

RaDe-10.Fa0.-0No-10.

Bolton26

Hospital-acquired pressure ulcers; the monthly rate per 1,000 patient days for each nursing unit and each hospital. Data are collected at the patient level and aggregated by CalNOC staff to the unit level. Unplanned descent to the floor in adult patients; the monthly fall rate per 1,000 patient days for each nursing unit and each hospital; % of RN hours/total nursing hours.

Hospitals 38 % RN 

Medical-surgical units 59 Critical care units 91 

RaFa3.0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-192

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Cheung32Pressure ulcers, patient falls coded as secondary diagnosis, primary bloodstream infections after admitting the unit, ratio of RN and LPN among to unlicensed nursing personnel 

Hospitals 1 Unit Combined Patients Medical 

Increase by 1% of licensed nurses 

ReulnoNo

Cho38

ICD-9-CM for urinary tract infections ICD-9-CM for pressure ulcers ICD-9-CM for falls and injury ICD-9-CM for surgical wound infection ICD-9-CM for sepsis ICD-9-CM for adverse drug event. RN Hours divided by all hours 

Unit Combined Patients Combined Hospitals 48 48 79 79 48 48 48 48 48 79 12 12 12 79 12 12 12 48 48 48 232 

% RN 70 50 60 90 60 60 80 90 50 70 50 80 50 60 70 80 90 80 90 70 100% increase in RN hours 100% increase in RN hours 100% increase in RN hours 

Pn1.2.1.1.1.1.1.1.2.1.2.1.1.1.1.1.1.1.1.1.ReU0.Pn0.Fa0.Pu
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-193

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

100% increase in RN hours 100% increase in RN hours 100% increase in RN hours 

0.Su0.Se1.

Cho30

The same study 

Unit Combined Patients Combined Age 67.9 Race 79.3 Sex 48.9 Severity 49.7 

% RN 76.5 68.1 72.4 72.7 76.5 68.1 72.4 72.7 76.5 68.1 72.4 72.7 76.5 68.1 72.4 72.7 76.5 68.1 72.4 72.7 76.5 68.1 72.4 72.7 

Ra2.1.2.2.Pn3.2.2.2.Fa0.0.0.0.Pr0.0.0.0.Su1.1.1.1.Se1.0.1.1.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-194

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Cimiotti87

Infections occurring in an infant 48 hours or longer after admission to the Neonatal Intensive Care Unit including bloodstream infections, device associated pneumonia, Central nervous System and skin infections, conjunctivitis. % of RN hours among total nursing hours adjusted for nursing intensity weights

Hospitals 1 Unit Neonatal Patients Medical 

% RN 100 96 100 96 

RaPn 0.0.Se105.

Donaldson9

Total number of patients with Stage I-IV pressure ulcers regardless of whether ulcer was acquired during hospitalization or present on admission; %/total number of surveyed patients; unplanned descent to the floor; rate/1,000 patient days; % of RN hours/total nursing care hours; % of licensed hours/total nursing care hours.

Hospitals 68 Patients Medical Unit Combined  Combined  ICU  ICU 

% RN % licensed nurses 59.2 67.52 66.67 74.29 68.79 72.99 72.19 75.54 59.2 67.52 66.67 74.29 68.79 72.99 72.19 75.54 

RaFa0.0.0.0.Pr14141316

Donaldson95Patients’ unplanned descent to the hospital floor; were analyzed as 7 day aggregate per unit; also actually number per unit; the number of falls/1,000 patient days, the % of RN hours / total care hours per day, per unit.

Hospitals 25 Unit Combined Patients Medical Increase by 1% in RN hours of care 

Increase by 1% licensed hours of care 

RaFa-0-0
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-195

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Flood53infections including urinary tract infection and gangrene; Complications: congestive heart failure and arrhythmias, gastrointestinal bleeding 

Hospitals 1 Unit Combined Patients Medical Sex 60 

 % RN Understaffed unit 60.45 Normally staffed unit 42.32 Understaffed unit 60.45 Normally staffed unit 42.32 

RaNo0.0.Co64 71 

Grillo-Peck10

The number of reported monthly incidents in the unit, total number of infected patients per month of the entire unit census. Decrease in % of RNs in the unit within new partnership model with increase patient care technicians and service associates. RN spent more time on direct patient care.

Hospitals 1 Unit Specialty Patients Medical Sex 43.7 

% RN 80 60 80 60 

RaFa8.3.No1610

Halm51

Failure to rescue: death following complications within 30 days 

Hospitals 1 Unit Surgical Patients Surgical Age 55.6 Sex 37.4 Severity 22.7

Increase by 1 unit in RN/patient ratio Fa

risNS 

Hope86

Incidence rate of urinary tract infection, ventilator associated pneumonia, surgical site infections, and infections that occurred after 72 hours of hospitalization; incidence rate of positive culture with known pathogen or two or more positive cultures with pathogens (one can be considered as contaminant); proportion of RN hours/total 

Hospitals 1 Sex 44.99 Units Surgical Surgical Surgical Surgical Medical Medical Medical Medical Medical Medical 

% RN 83.65 84.26 81.73 85.09 98.81 77.28 76.48 89.7 98.6 80.4 78.12 

RaNo3.204.100.6.1.1.0.0.3.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-196

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

nursing hours/patient day 4-10 days before the event occurred 

Medical Medical Specialty ICU ICU Surgical Neonatal Surgical Surgical Surgical Surgical Medical Medical Medical Medical Medical Medical Medical Spec ICU ICU Surgical Neonatal 

76.23 98.75 94.48 99.56 99.11 92.11 83.65 84.26 81.73 85.09 98.81 77.28 76.48 89.7 80.4 78.12 76.23 98.75 94.48 99.56 99.11 92.11 Increase by 1% in proportion of RN Increase by 1% in proportion of RN Increase by 1% in proportion of RN Increase by 1% in proportion of RN Increase by 1% in proportion of RN

100.331.3.0.Se7.110.4.0.7.2.1.7.8.6.1.239.4.2.ReU1.Pn1.No1.Su1.Se1.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-197

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Houser49

Failure to rescue: death/1,000 patients who developed complications of care during hospitalization; cases of decubitus ulcer/1,000 discharges identified as secondary diagnosis; cases of acute respiratory failure/1,000 surgical discharges; cases of deep vein thrombosis or pulmonary embolism/1,000 surgical discharges. Reported by hospitals ratio reported RN FTE/RN+LPN 

Unit Combined Patients Medical Age 55.08 Race 51 Sex 42 Hospitals 170 172 174 171 39 14 8 

% RN 79 86 87 88 88 88 86 79 86 87 88 88 88 86 79 86 87 88 88 88 86 79 86 87 88 88 88 86

RaFa111312109.9.5.De2.2.2.1.1.1.2.Pu0.0.0.0.0.0.0.De0.0.0.0.0.0.0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-198

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Langemo41

% of patients who had a pressure ulcer on a given day to all patients assessed for a pressure ulcer, pressure ulcers that occurred post admission were documented as hospitalacquired. Number of productive hours worked by RN divided by total staff hours.

Hospitals 1 % RN 

Medical-surgical units in hospitals with <100 beds 53.4 ICU in hospitals with 200-299 beds 99.4 ICU units in hospitals <100 beds 60.6 Medical-surgical units in hospitals with 200-299 beds 61.5 

Ra4.0.130.

Lichtig63

Likely adverse patient outcomes of the hospital stay, secondary diagnoses of urinary tract infection, pneumonia, pressure ulcers, infection in surgical patients. RN hours as a percentage of total nursing hours per nursing intensity weight-adjusted patient day 

Hospitals Unit 352 Surgical 295 Surgical 126 Surgical 131 Surgical 

Increase by 1% in proportion of RNs: California, 1992 California, 1994 New York,1992 New York, 1994 California, 1992 California, 1994 California, 1992 California, 1994 New York,1992 New York, 1994 

RaPr-0-1-1-1Pn-0-0Su-0-0Repnan

Needleman28

Urinary tract infection in discharge abstract as secondary diagnosis; acute gastric ulcer, duodenal ulcer, peptic ulcer, gastrojejunal ulcer, hemorrhagic gastritis, erosive gastritis, unspecified GIhemorrhage, esophageal hemorrhage coded in discharge abstract as secondary diagnosis; aspiration pneumonia, postoperative 

Hospitals Patients 4,156 Medical 4,156 Surgical 4,156 Medical 4,156 Surgical 3,357 Medical 3,357 Medical 3,357 Surgical 3,357 Surgical 256 Medical 

Increase by 1% in RNs/total nursing hours Increase by 1% in RNs/total nursing hours increase by 1% of RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total nurse hours Increase by 1% in RN hours/licensed hours Increase by 1% in RN hours/total nursing hours Increase by 1% in RN hours/total nursing hours, hospital level analysis, California hospitals Increase by 1% of RN hours/total licensed hours, hospital 

ReU0.0.0.0.0.0.0.1.0.0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-199

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

pneumonia, hypostatic pneumonia, bacterial pneumonia, bronchopneumonia coded in discharge abstract as secondary diagnosis; cardiac arrest; shock without mention of trauma; cardiogenic shock; respiratory arrest, nonmechanical methods of resuscitation, cardiopulmonary resuscitation, failure to rescue: death in patients with sepsis, pneumonia, gastrointestinal bleeding, shock or deep vein thrombosis coded in discharge abstract as secondary diagnosis; pressure ulcers, posttraumatic surgical wound infection and postoperative surgical wound infection; % of RN hours/total nursing hours; % of licensed hours/total nursing hours 

256 Medical 256 Medical 256 Medical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 799 Medical 799 Surgical 799 Surgical 799 Surgical 799 Medical 799 Medical 799 Medical 799 Surgical 4156 Medical 4156 Surgical 4156 Medical 4156 Surgical 3,357 Medical 3,357 Medical 3357 Surgical 3357 Surgical 256 Medical 256 Medical 256 Medical 256 Medical 

level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, unit level analysis, California hospitals Increase by 1% of RN hours/licensed hours, unit level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, California hospitals Increase by 1% in RN hours/licensed hours, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in proportion of RN/total nursing personnel Increase by 1% in RN/total nursing hours Increase by 1% in RN/total nursing hours increase by 1% of RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total nurse hours Increase by 1% in RN hours/licensed hours Increase by 1% in RN hours/total nursing hours Increase by 1% in RN hours/total nursing, hospital level analysis, California hospitals Increase by 1% of RN hours/total licensed hours, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, unit level analysis, California hospitals 

Increase by 1% of RN h/licensed hours, unit level analysis, California hospitals 

0.0.0.0.0.0.0.0.0.0.0.0.0.0.G0.0.0.0.0.0.0.0.0.0.1.0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-200

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

256 Surgical 256 Surgical 256 Surgical 256 Surgical 799 Medical 799 Surgical 799 Surgical 799 Surgical 799 Medical 799 Medical 799 Medical 4156 Medical 4156 Surgical 4156 Medical 4156 Surgical 3,357 Medical 3,357 Medical 3357 Surgical 3357 Surgical 256 Medical 256 Medical 256 Medical 256 Medical 256 Surgical 256 Surgical 256 Surgical 

Increase by 1% in RN h/total nursing hours, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, California hospitals Increase by 1% in RN hours/licensed hours, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours Increase by 1% in RN/total nursing hours Increase by 1% in RN/total nursing hours increase by 1% of RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total nurse hours Increase by 1% in RN hours/licensed hours Increase by 1% in RN hours/total nursing hours Increase by 1% in RN hours/total nursing, hospital level analysis, California hospitals Increase by 1% of RN h/total licensed hours, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, unit level analysis, California hospitals Increase by 1% of RN hours/licensed hours, unit level analysis, California hospitals Increase by 1% in RN h/total nursing hours, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, California hospitals 

0.0.0.0.0.0.0.0.0.0.0.Pn0.

0.0.0.0.0.0.0.0.0.1.0.0.0.0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-201

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

256 Surgical 799 Medical 799 Surgical 799 Surgical 799 Surgical 799 Medical 799 Medical 799 Medical 4156 Medical 4156 Surgical 4156 Medical 4156 Surgical 3,357 Medical 3,357 Medical 3357 Surgical 3357 Surgical 256 Medical 256 Medical 256 Medical 256 Medical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 799 Medical 799 Surgical 799 Surgical 799 Surgical 

Increase by 1% in RN hours/licensed hours, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours Increase by 1% in RN/total nursing hours Increase by 1% in RN/total nursing hours increase by 1% of RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total nurse hours Increase by 1% in RN hours/licensed hours Increase by 1% in RN hours/total nursing hours Increase by 1% in RN hours/total nursing, hospital level analysis, California hospitals Increase by 1% of RN hours/total licensed hours, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, unit level analysis, California hospitals Increase by 1% of RN hours/licensed hours, unit level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, California hospitals Increase by 1% in RN hours/licensed hours, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 

0.0.0.0.0.1.0.0.Sh0.1.0.0.0.0.0.0.0.

0.0.0.0.0.0.0.0.0.0.0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-202

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

799 Medical 799 Medical 799 Medical 4156 Medical 4156 Surgical 4156 Medical 4156 Surgical 3,357 Medical 3,357 Medical 3357 Surgical 3357 Surgical 256 Medical 256 Medical 256 Medical 256 Medical 256 Surgical 256 Surgical 256 Surgical 256 Surgical 799 Medical 799 Surgical 799 Surgical 799 Surgical 799 Medical 799 Medical 799 Medical 799 Surgical 

1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours Increase by 1% in RN/total nursing hours Increase by 1% in RN/total nursing hours increase by 1% of RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total licensed hours Increase by 1% in RN hours/total nurse hours Increase by 1% in RN hours/licensed hours Increase by 1% in RN hours/total nursing hours Increase by 1% in RN hours/total nursing , hospital level analysis, California hospitals Increase by 1% of RN hours/total licensed hours, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, unit level analysis, California hospitals Increase by 1% of RN hours/licensed hours, unit level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, hospital level analysis, California hospitals Increase by 1% in RN hours/licensed hours, hospital level analysis, California hospitals Increase by 1% in RN hours/total nursing hours, California hospitals Increase by 1% in RN hours/licensed hours, unit level analysis, California hospitals 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in RN hours/total licensed hours 1% increase in proportion of RN/total nursing personnel

1.0.0.Fa0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.

0.0.0.0.0.0.1.0.0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-203

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Potter40

(Number of falls on a unit/number of patient days) * 1,000 

Hospitals 1 Unit ICU Patients Medical 

% RN 53.8 55.4 56.2 57.1 

Fa0.0.0.0.

Ritter-Teitel69

Hospital Incidence reports; % of patients with urinary tract infection not presented at admission among total discharged or sampled patients; % of patients with pressure ulcers, number of events/1,000 patient days, % of RNs among total nursing personnel 

Hospitals 28 % RN 

56.15 56.4 56.79 56.77 56.79 56.77 Increase by 1 hour in RN hours % RN 56.15 56.4 56.79 56.77 56.79 56.77 Increase by 1 hour in RN hours % RN 56.15 56.4 56.79 56.77 56.79 56.77 Increase by 1 hour in RN hours Increase by 1 hour in RN hours in medical units Increase by 1 hour in RN hours in surgical units

Ra2.2.2.2.1.2.-0Pr2.2.2.2.2.1.-0Fa0.0.0.0.0.0.-0-0-0

Seago8The proportion of pressure ulcers per patient day; the proportion of falls per patient day; RN hours/total hours.

Hospitals 1 Unit Combined Patients Medical 

% RN 63 61.5 62 

RaFa0.0.0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-204

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Seago93

The proportion of pressure ulcers per patient day, the proportion of falls per patient day, RN hours/total hours 

Hospitals 1 Unit Combined Patients Medical 

% RN 75 96 72 75 96 72

RaDe0.0.0.Fa0.0.0.

Simmonds82

% of patients with positive colonization of vancomycinresistant enterococci 48 hours after admission to the hospital and after surgery; 100% of nursing care provided by a licensed practical nurse

Hospitals 1 Unit Specialty Patients Medical Age 68.75 Sex 55.8 

% RN 76.83 75.51 74.19 72.87 76.83 75.51 74.19 72.87 

RaNo1.3.4.6.2.3.4.1.

Stratton91

Rate/1,000 patient days of respiratory, gastrointestinal, bloodstream and central line infections in hospitalized patients not present at time of admission; rate/1,000 patient days of bloodstream and central line infections in hospitalized patients not present at time of admission. average % of RN productive hours/total nursing hours/ patient day 

Hospitals 7 Unit Patients Combined Combined Combined Combined Combined Combined Combined Combined Spec Surgical Spec Surgical Spec Surgical Spec Surgical ICU Medical ICU Medical ICU Medical ICU Medical Combined Medical Combined Medical Combined Medical Combined Medical Combined Medical 

% RN 73.41 72.06 72.41 74 83.2 79 79.6 80.2 89 88.17 87.5 88.5 80.35 78.76 78.79 80.03 Increase by 1 hour in total nursing hours 

RaNo0.0.0.0.0.0.0.0.0.1.0.0.0.0.0.0.0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-205

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Combined Medical Combined Medical Combined Medical 

Increase by 1% in RN hours increase by 1% in overtime RN hours Increase by 1% in temporary nurses 

0.-00.

Tallier83

Incidence rate/1,000 patient days of pressure ulcers developed 72 hours after admission, % of productive hours in direct patient care worked by RN

Hospitals 1 Unit Combined Patients Medical 

% RN 57 60 

RaPr0.0.

Unruh81

Yearly number of occurrences of pneumonia, falls, and decubitus ulcers per hospital 

Hospitals 1477 Unit Combined Patients Medical 1% increase in proportion of licensed nurses/total nursing 

personnel 1% increase in proportion of licensed nurses/total nursing personnel 1% increase in proportion of licensed nurses/total nursing personnel 

RePn0.De0.Fa1.

Unruh66

Nosocomial urinary tract infection as secondary diagnosis when primary diagnosis is not disorders of kidneys, urinary and reproductive tracts and systems; hospital acquired pneumonia as secondary diagnosis when primary diagnosis is not respiratory disorders and adult atelectasis; secondary diagnosis of decubitus ulcer in patients not transferred from another hospital; falls in hospital when a primary diagnosis was not fracture or injury; adult 

Hospitals 211 Unit Combined Patients Combined Race 45.37 Sex 42.43 

% RN 68.5 69.2 70.2 71.2 71.5 71.4 71.8 70 63 70 63 Increase by 1% in RN proportion Increase by 1% in RN proportion in small hospitals Increase by 1% in RN proportion in medium hospitals Increase by 1% in RN proportion in large hospitals 68.5 

De0.0.0.0.0.0.0.0.0.0.0.-0-0-00.Su0.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-206

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

atelectasis as secondary diagnosis when primary diagnosis is not respiratory disorders, secondary diagnosis of post surgical infections; cardiac arrest as secondary diagnosis when primary diagnosis is not circulatory disorder, % of RN FTE/total nurses FTE 

69.2 70.2 71.2 71.5 71.4 71.8 70 63 70 63 Increase by 1% in RN proportion Increase by 1% in RN proportion in small hospitals Increase by 1% in RN proportion in medium hospitals Increase by 1% in RN proportion in large hospitals 68.5 69.2 70.2 71.2 71.5 71.4 71.8 Increase by 1% in RN proportion Increase by 1% in RN proportion in small hospitals Increase by 1% in RN proportion in medium hospitals Increase by 1% in RN proportion in large hospitals 68.5 69.2 70.2 71.2 71.5 71.4 71.8 Increase by 1% in RN proportion Increase by 1% in RN proportion in small hospitals Increase by 1% in RN proportion in medium hospitals Increase by 1% in RN proportion in large hospitals 

0.0.0.0.0.0.0.0.0.0.0.0.0.0.Pn0.0.0.1.1.1.1.-0-0-0-0Fa0.0.0.0.0.0.0.0.0.-00.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-207

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

68.5 69.2 70.2 71.2 71.5 71.4 71.8 Increase by 1% in RN proportion Increase by 1% in RN proportion in small hospitals Increase by 1% in RN proportion in medium hospitals Increase by 1% in RN proportion in large hospitals 68.5 69.2 70.2 71.2 71.5 71.4 71.8 Increase by 1% in RN proportion Increase by 1% in RN proportion in small hospitals Increase by 1% in RN proportion in medium hospitals Increase by 1% in RN proportion in large hospitals Increase by 1% in RN proportion Increase by 1% in RN proportion in small hospitals Increase by 1% in RN proportion in medium hospitals Increase by 1% in RN proportion in large hospitals

Pu0.0.0.0.0.0.0.-00.-00.C0.0.0.0.0.0.0.0.0.0.0.Pr-0-00.-0

Wan52Incidence/1,000 patient days of falls adjusted for severity of incident, RN hours/total nursing hours

Hospitals 45 Unit Combined Patients Combined 

Increase by 1% of RNs/total nursing hours 52% of RNs 

Fa-00.
Table G27. Evidence of the association between nurse skill mix (proportion of registered nurses) and patient outcomes (contin

G-208

Author, Source to Measure 

Patient Outcomes, Definition 

of Patient Outcomes 

Source to Measure Nurse 

Skill Mix, Definition of Nurse 

Skill Mix 

Number of Hospitals, Units, 

Patient Age, % of Whites, % of 

Males, % of Emergency 

Admissions 

Nurse Staffing Categories 

Zidek85

New incidence of skin breakdown acquired over the course of the hospital stay; number of reported unplanned descents to the floor during the course of the hospital stay. % of RN FTE/total nursing FTE 

Hospitals 1 Unit Combined Patients Medical-surgical 

% RN 31 31 28 32 30 30 31 33 32 31 33 30 

RaFa0.0.0.0.0.0.0.0.0.0.0.0.

BSN = Bachelor of Science in Nursing; CPR = Cardio Pulmonary Resuscitation; DRG = Diagnosis Related Group; HPF = high-powere

Care Unit; LPN = Licensed Practical Nurse; NS = Not Significant; RN = Registered Nurse; SD = Standard Deviation; SWI = Surgical Wo

Urinary Tract Infection
G-209

Table G28. Relative risk of patient outcomes corresponding to an increase by 1% of RNs in nurse skill mix as reported by auth

Author Data 

Analytic 

Unit Hospitals Unit Patients Outcomes 

Relative 

Risk 95

Needleman28 Administrative Hospital 4,156 Medical Medical Urinary tract infection 0.40 0.29Needleman28 Administrative Hospital 4,156 Surgical Surgical Urinary tract infection 0.58 0.36Needleman28 Administrative Hospital 3,357 Medical Medical Urinary tract infection 0.46 0.34Needleman28 Administrative Hospital 3,357 Surgical Surgical Urinary tract infection 1.02 0.73Needleman28 Administrative Hospital 256 Medical Medical Urinary tract infection 0.33 0.18Needleman28 Administrative Unit 256 Medical Medical Urinary tract infection 0.50 0.30Needleman28 Administrative Hospital 256 Surgical Surgical Urinary tract infection 0.82 0.47Needleman28 Administrative Unit 256 Surgical Surgical Urinary tract infection 0.09 0.01Needleman29 Administrative Hospital 799 Combined Surgical Urinary tract infection 0.67 0.46Hope86 Administrative Patient 1 Combined Medical Urinary tract infection 1.01 1.00Needleman28 Administrative Hospital 4,156 Medical Medical Gastrointestinal bleeding 0.60 0.36Needleman28 Administrative Hospital 4,156 Surgical Surgical Gastrointestinal bleeding 0.45 0.18Needleman28 Administrative Hospital 3,357 Medical Medical Gastrointestinal bleeding 0.81 0.58Needleman28 Administrative Hospital 3,357 Surgical Surgical Gastrointestinal bleeding 0.27 0.09Needleman28 Administrative Hospital 256 Medical Medical Gastrointestinal bleeding 0.89 0.52Needleman28 Administrative Unit 256 Medical Medical Gastrointestinal bleeding 0.93 0.56Needleman28 Administrative Hospital 256 Surgical Surgical Gastrointestinal bleeding 0.02 0.00Needleman28 Administrative Unit 256 Surgical Surgical Gastrointestinal bleeding 0.04 0.00Needleman28 Administrative Hospital 4,156 Medical Medical Pneumonia 0.52 0.35Needleman28 Administrative Hospital 4,156 Surgical Surgical Pneumonia 0.41 0.19Needleman28 Administrative Hospital 3,357 Medical Medical Pneumonia 0.49 0.32Needleman28 Administrative Hospital 3,357 Surgical Surgical Pneumonia 0.23 0.10Needleman28 Administrative Hospital 256 Medical Medical Pneumonia 0.44 0.22Needleman28 Administrative Unit 256 Medical Medical Pneumonia 1.02 0.72Needleman28 Administrative Hospital 256 Surgical Surgical Pneumonia 0.61 0.30Needleman28 Administrative Unit 256 Surgical Surgical Pneumonia 0.78 0.40Hope86 Administrative Patient 1 Combined Medical Pneumonia 1.06 0.93Needleman28 Administrative Hospital 4,156 Medical Medical Shock 0.84 0.71Needleman28 Administrative Hospital 4,156 Surgical Surgical Shock 1.08 0.60Needleman28 Administrative Hospital 3,357 Medical Medical Shock 0.52 0.31Needleman28 Administrative Hospital 3,357 Surgical Surgical Shock 0.36 0.14Needleman28 Administrative Hospital 256 Medical Medical Shock 0.30 0.12Needleman28 Administrative Unit 256 Medical Medical Shock 0.34 0.16Needleman28 Administrative Hospital 256 Surgical Surgical Shock 0.14 0.05Needleman28 Administrative Unit 256 Surgical Surgical Shock 0.17 0.06Needleman28 Administrative Hospital 4,156 Medical Medical Failure to rescue 0.85 0.70Needleman28 Administrative Hospital 4,156 Surgical Surgical Failure to rescue 0.64 0.44Needleman28 Administrative Hospital 3,357 Medical Medical Failure to rescue 0.85 0.70Needleman28 Administrative Hospital 3,357 Surgical Surgical Failure to rescue 0.69 0.45
Table G28. Relative risk of patient outcomes corresponding to an increase by 1% of RNs in nurse skill mix as reported by auth

G-210

Author Data 

Analytic 

Unit Hospitals Unit Patients Outcomes 

Relative 

Risk 95

Needleman28 Administrative Hospital 256 Medical Medical Failure to rescue 0.63 0.47Needleman28 Administrative Unit 256 Medical Medical Failure to rescue 0.70 0.54Needleman28 Administrative Hospital 256 Surgical Surgical Failure to rescue 0.36 0.14Needleman28 Administrative Unit 256 Surgical Surgical Failure to rescue 0.44 0.20Needleman29 Administrative Hospital 799 Combined Surgical Failure to rescue 0.73 0.49Needleman28 Administrative Hospital 4,156 Surgical Surgical Pulmonary failure 0.94 0.56Needleman28 Administrative Hospital 3,357 Surgical Surgical Pulmonary failure 0.76 0.43Needleman28 Administrative Hospital 256 Surgical Surgical Pulmonary failure 0.81 0.41Needleman28 Administrative Unit 256 Surgical Surgical Pulmonary failure 0.86 0.46Needleman28 Administrative Hospital 3,357 Surgical Surgical Pressure ulcers 0.44 0.23Needleman28 Administrative Hospital 256 Medical Medical Pressure ulcers 0.27 0.09Needleman28 Administrative Unit 256 Medical Medical Pressure ulcers 0.65 0.36Needleman28 Administrative Hospital 256 Surgical Surgical Pressure ulcers 0.01 0.00Needleman28 Administrative Unit 256 Surgical Surgical Pressure ulcers 0.00 0.00Hope86 Administrative Patient 1 Combined Combined Nosocomial infections 1.06 1.03Needleman28 Administrative Hospital 4,156 Surgical Surgical Surgical wound infection 1.03 0.66Needleman28 Administrative Hospital 3,357 Surgical Surgical Surgical wound infection 1.31 0.73Hope86 Administrative Patient 1 Combined Surgical Surgical wound infection 1.03 0.99Needleman28 Administrative Hospital 3,357 Medical Medical Deep vein thrombosis 1.05 0.64Needleman28 Administrative Hospital 3,357 Surgical Surgical Deep vein thrombosis 1.39 0.66Needleman28 Administrative Hospital 256 Medical Medical Deep vein thrombosis 0.78 0.39Needleman28 Administrative Unit 256 Medical Medical Deep vein thrombosis 0.75 0.40Needleman28 Administrative Hospital 256 Surgical Surgical Deep vein thrombosis 1.55 0.51Needleman28 Administrative Unit 256 Surgical Surgical Deep vein thrombosis 1.87 0.69Needleman28 Administrative Hospital 4,156 Surgical Surgical Complications 3.06 0.94Needleman28 Administrative Hospital 3,357 Medical Medical Complications 18.55 1.22; Needleman28 Administrative Hospital 3,357 Surgical Surgical Complications 1.68 0.66Needleman28 Administrative Hospital 256 Medical Medical Complications 0.68 0.29Needleman28 Administrative Unit 256 Medical Medical Complications 0.74 0.32Needleman28 Administrative Hospital 256 Surgical Surgical Complications 0.57 0.17Needleman28 Administrative Unit 256 Surgical Surgical Complications 0.71 0.20Needleman28 Administrative Hospital 4,156 Medical Medical Sepsis 1.55 0.93Needleman28 Administrative Hospital 4,156 Surgical Surgical Sepsis 1.15 0.72Needleman28 Administrative Hospital 3,357 Medical Medical Sepsis 0.83 0.56Needleman28 Administrative Hospital 3,357 Surgical Surgical Sepsis 0.74 0.43Needleman28 Administrative Hospital 256 Medical Medical Sepsis 1.08 0.61Needleman28 Administrative Unit 256 Medical Medical Sepsis 1.03 0.61Needleman28 Administrative Hospital 256 Surgical Surgical Sepsis 0.00 0.00Needleman28 Administrative Unit 256 Surgical Surgical Sepsis 0.99 0.51Hope86 Administrative Patient 1 Combined Medical Sepsis 1.05 1.04
G-211

Table G29. Evidence of the association between nurse strategies (overtime hours, temporary nurse hours, full-time hours) and 

Author, Definition of Patient 

Outcomes, Definition of Nurse 

Strategies 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories P

Alonso-Echanove79Bloodstream infections as secondary diagnosis after CVC, duration of CVC, number of days from the placement date to the day when bloodstream infection occurred or to the day of CVC removal, % of temporary nurses/ float nurses in unit each day; float nurse = a nurse not permanently assigned to the participating ICU, agency nurses, and nurses from other units or hospital areas who had been working in the participating ICU less than a year 

Hospitals 6 Unit ICU Patients Medical Race 61 Sex 54 

Patients cared for by float nurse, days >60% Patients cared by float nurse, days >60% Patients cared for by float nurse, days <60% 

Relative riNosocomi2.75 1.2.61 1.1.00 1.

Berney84

Actual number of events identified as secondary DRG: urinary tract infection, gastrointestinal bleeding, pneumonia, shock, failure to rescue, sepsis 

Hospitals 161 Unit Patients Surgical Surgical Medical Medical Medical Medical Medical Medical Surgical Surgical Surgical Surgical Surgical Surgical Medical Medical Medical Medical Medical Medical Surgical Surgical Surgical Surgical Surgical Surgical Medical Medical Medical Medical Medical Medical Surgical Surgical Surgical Surgical Surgical Surgical Medical Medical 

1% increase in RN overtime hours 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours .00% 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours .00% 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours .00% 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours 1st (low overtime) quartile 1.6% 

Relative riUrinary tra1.01 01.00 01.00 11.01 11.01 01.00 1Gastrointe1.02 00.98 01.00 11.01 01.00 01.00 1Pneumoni1.02 11.01 01.00 11.01 11.01 01.00 1Shock 1.01 01.01 0
Table G29. Evidence of the association between nurse strategies (overtime hours, temporary nurse hours, full-time hours) and 

(continued) 

G-212

Author, Definition of Patient 

Outcomes, Definition of Nurse 

Strategies 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories P

Medical Medical Medical Medical Surgical Surgical Surgical Surgical Surgical Surgical Medical Medical Medical Medical Medical Medical Surgical Surgical Surgical Surgical Surgical Surgical Medical Medical Medical Medical Medical Medical Surgical Surgical Surgical Surgical

4th (high overtime) quartile 7.4% 1% increase in RN overtime hours 00% 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours .00% 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 1% increase in RN overtime hours .00% 1st (low overtime) quartile 1.6% 4th (high overtime) quartile 7.4% 

1.00 11.02 11.00 01.00 1Failure to 1.00 01.00 01.00 11.00 11.00 01.00 1Sepsis 1.02 11.01 01.00 11.03 11.02 11.00 1
Table G29. Evidence of the association between nurse strategies (overtime hours, temporary nurse hours, full-time hours) and 

(continued) 

G-213

Author, Definition of Patient 

Outcomes, Definition of Nurse 

Strategies 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories P

Cho30

ICD-9-CM for urinary tract infection, pressure ulcers, falls and injury, surgical wound infection, and sepsis; Contracted hours = productive nursing hours (direct care to patient) worked by nursing personnel contracted on a temporary basis. Contract hours * % of RN 

Unit Combined Patients Combined Age 67.9 Race 79.3 Sex 48.9 Severity 49.7 

% Contract hours % of RN 3.60 76.5 3.30 68.1 3.20 72.4 5.00 72.7 3.60 76.5 3.30 68.1 3.20 72.4 5.00 72.7 3.60 76.5 3.30 68.1 3.20 72.4 5.00 72.7 3.60 76.5 3.30 68.1 3.20 72.4 5.00 72.7 3.60 76.5 3.30 68.1 3.20 72.4 5.00 72.7 3.60 76.5 3.30 68.1 3.20 72.4 5.00 72.7 

Rate, % ± Urinary tra2.50 ± 1.31.60 ± 1.42.00 ± 1.02.10 ± 1.8Pneumoni3.10 ± 1.92.70 ± 2.22.80 ± 1.32.80 ± 2.0Falls 0.20 ± 0.20.20 ± 0.30.20 ± 0.20.10 ± 0.2Pressure u0.10 ± 0.30.30 ± 0.60.30 ± 0.50.20 ± 0.4Surgical w1.60 ± 1.01.10 ± 1.11.50 ± 0.71.10 ± 1.0Sepsis 1.20 ± 0.70.80 ± 0.81.10 ± 0.61.00 ± 1.1
Table G29. Evidence of the association between nurse strategies (overtime hours, temporary nurse hours, full-time hours) and 

(continued) 

G-214

Author, Definition of Patient 

Outcomes, Definition of Nurse 

Strategies 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories P

Cimiotti87

Infections occurring in an infant 48 hours or longer after admission to the NICU including bloodstream infections, device associated pneumonia, CNS and skin infections, conjunctivitis; hours/patient day worked by float pool and agency RN not regularly assigned to the NICU 

Hospitals 1 Unit Neonatal Patients Medical 0.19% of float nurses 

24.07% of float nurse 0.19% of float nurses 24.07% of float nurse Mean staffing levels 12.13% Low % of pooled nurses 14.19% High % of pooled nurses 12.13% Mean staffing levels 12.13% Low % of pooled nurses 14.19% High % of pooled nurses 12.13% 

Rate, % Pneumoni0.50 0.90 Sepsis 10.50 5.50 Relative riNosocomiReference 1.30 1.30 Sepsis rat1.00 2.01 2.06 

Donaldson9

Total number of patients with Stage IIV pressure ulcers regardless of whether ulcer was acquired during hospitalization or present on admission; % total number of surveyed patients; unplanned descent to the floor; rate/1,000 patient days, total number of productive hours worked only by those with direct patient care responsibilities who are contract staff (registry, travelers). It does not include internal float staff 

Hospitals 68 % contract hours % RN 

8.43 59.2 8.04 66.67 9.22 68.79 10.74 72.19 

Rate/100 p0.31 ± 0.20.32 ± 0.10.30 ± 0.20.26 ± 0.1

Donaldson95Hospital acquired pressure related skin injury controlling for date of admission, % of all patients on the day of prevalence study, patient’s unplanned descent to the hospital floor; were analyzed as 7 day aggregate per unit; also actually number per unit; the number of falls/1,000 patient days, percent of contacted or agency staff.

Hospitals 25 Unit Combined Patients Medical Increase by 1% contracted hours of care 

Rate/100 pFalls -0.001 ± 0
Table G29. Evidence of the association between nurse strategies (overtime hours, temporary nurse hours, full-time hours) and 

(continued) 

G-215

Author, Definition of Patient 

Outcomes, Definition of Nurse 

Strategies 

Number of Hospitals, Units, Patient 

Age, % of Whites, % of Males, % of 

Emergency Admissions 

Nurse Staffing Categories P

Potter40

 (Number of falls on a unit/number of patient days) * 1,000, an average % of float nurses in day shift provided by nurses from other units or outside the hospital 

Hospitals 1 Unit ICU Patients Medical 

% float hours % RN 7.30 53.8 11.00 55.4 8.80 56.2 10.10 57.1 

Rate/100 pFalls 0.30 0.29 0.30 0.23 

Robert6

Primary bloodstream infections (BSIs) (CDC). Index date for cases, the day of 1 positive blood culture; for controls = (cases LOS before BSI/total cases LOS) * control total LOS, % of pool staff - not regular full-time employees of the hospital assigned to SICU.

Hospitals 1 Unit ICU Patients Surgical 

% of contract hours 17.19 32.59 17.19 32.59 

Nosocomipatient da0.28 0.76 Relative ri1.00 1.3.20 1.

Stratton91

Rate/1,000 patient days of respiratory, gastrointestinal, bloodstream and central line infections in hospitalized patients not present at time of admission, rate/1,000 patient days of bloodstream and central line infections in hospitalized patients not present at time of admission, % of total productive overtime nursing hours worked by RN, LPN, and UAP in each quarter 2002, % of RN productive hours worked by supplemental nurse staffing (total nursing overtime hours and percentages of hours from float/agency/traveler RN hours) 

Hospitals 7 

% hours overtime contract RN 18.06 14.05 73.41 17.59 13.91 72.06 17.59 14.03 72.41 14.71 11.53 74 17.20 17.95 83.2 16.20 17.53 79 17.20 17.93 79.6 16.80 18.08 80.2 16.92 12.72 89 15.67 12.03 88.17 15.92 11.67 87.5 16.58 12.52 88.5 4.08 14.04 80.35 3.84 13.67 78.76 4.00 13.64 78.79 3.52 12.68 80.03 Increase by 1% in overtime RN hours Increase by 1% in temporary nurses

Rate/100 pNosocomi0.75 ± 0.60.53 ± 0.60.71 ± 0.70.64 ± 0.40.65 ± 0.20.62 ± 0.30.71 ± 0.50.85 ± 0.50.73 ± 0.51.03 ± 0.90.80 ± 0.60.95 ± 0.70.51 ± 0.00.79 ± 0.10.66 ± 0.10.56 ± 0.1-0.01 ± 0.00.00380 ± 

Tourangeau76

30 day mortality, % of full time nurses 

Hospitals 75 Unit Combined Patients Medical 

% fulltime % RN 0.67 85 0.55 71 0.62 79 

Rate, % 14.02 15.27 15.05 

BSI = Bloodstream infection; CNS = Central nervous system; CVC = Central venous catheter DRG = Diagnosis related group; ICU = InteLength of stay; NISU = Neonatal intensive care unit; RN = Registered Nurse; SD = Standard deviation; SICU = Surgical intensive care u
G-216 

Table G30. The significant effect modification by the study design of the association between nurse staffing 

and patient outcomes 

Outcomes Rates 

(N=16) 

Outcomes Relative Risk 

(N=19)

Quality scores % Significant interactions % Significant interactions

Patients/RN/shift 12.5 21.1 

RN FTE/patient day 12.5 15.8 

Patients/LPN 31.3 5.3 

Total nurse hours 6.3 0 

RN hours/patient day 12.5 21.1 

LPN hours 31.3 0 

UAP hours 6.3 0 
G-217 

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