Chapter 25. Nurse Staffing and Patient Care Quality 

and Safety 

Sean P. Clarke, Nancy E. Donaldson 

The importance of nurse staffing to the delivery of high-quality patient care was a principle 

finding in the landmark report of the Institute of Medicine’s (IOM) Committee on the Adequacy 

of Nurse Staffing in Hospitals and Nursing Homes: “Nursing is a critical factor in determining 

the quality of care in hospitals and the nature of patient outcomes”1 (p. 92). Nurse staffing is a 

crucial health policy issue on which there is a great deal of consensus on an abstract level (that 

nurses are an important component of the health care delivery system and that nurse staffing has 

impacts on safety), much less agreement on exactly what research data have and have not 

established, and active disagreement about the appropriate policy directions to protect public 

safety. 

The purpose of this chapter is to summarize and discuss the state of the science examining 

the impact of nurse staffing in hospitals and other health care organizations on patient care 

quality, as well as safety-focused outcomes. To address some of the inconsistencies and 

limitations in existing studies, design issues and limitations of current methods and measures will 

be presented. The chapter concludes with a discussion of implications for future research, the 

management of patient care and public policy. 

Background

For several decades, health services researchers have reported associations between nurse 

staffing and the outcomes of hospital care.2–4 However, in many of these studies, nursing care 

and nurse staffing were primarily background variables and not the primary focus of study.5 In 

the 1990s, the National Center for Nursing Research, the precursor to the National Institute of 

Nursing Research, convened an invitational conference on patient outcomes research from the 

perspective of the effectiveness of nursing practice.6

 It was hoped that as methods for capturing 

the quality of patient care quantitatively became more sophisticated, evidence linking the 

structure of nurse staffing (i.e., hours of care, skill mix) to patient care quality and safety would 

grow. However, 5 years later, the 1996 IOM report articulating the importance of nurses and 

nurse staffing on outcomes concluded that, at that time, there was essentially no evidence that 

staffing exerted an effect on acute care hospital patients’ outcomes and limited evidence of its 

impact on long-term care outcomes.1

 

There has been remarkable growth in this body of literature since the 1996 IOM report. Over 

the course of the last decade, hospital restructuring, spurred in part by a move to managed care 

payment structures and development of market competition among health care delivery 

organizations, led to aggressive cost cutting. Human resources, historically a major cost center 

for hospitals, and nurse staffing in particular, were often the focus of work redesign and 

workforce reduction efforts. Cuts in nursing staff led to heavier workloads, which heightened 

concern about the adequacy of staffing levels in hospitals.7, 8 Concurrently, public and 

professional concerns regarding the quality and safety of patient care were sparked by research 

and policy reports (among them, the IOM’s To Err is Human9

), and then fueled by the popular 

1 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

media. A few years ago, reports began documenting a new, unprecedented shortage of nurses 

linked to growing demand for services, as well as drops in both graduations from prelicensure 

nursing education programs and workforce participation by licensed nurses, linked by at least 

some researchers to deteriorating working conditions in hospitals.10, 11 These converging health 

care finance, labor market, and professional and public policy forces stimulated a new focus of 

study within health services research examining the impact of nurse staffing on the quality and 

safety of patient care. An expected deepening of the shortage in coming years12 has increased the 

urgency of understanding the staffing-outcomes relationship and offering nurses and health care 

leaders evidence about the impacts of providing care under variable nurse staffing conditions. 

This chapter includes a review of related literature from early 2007. 

Identifying Nurse-Sensitive Outcomes 

The availability of data on measures of quality that can be reasonably attributed to nurses, 

nursing care, and the environments in which care is delivered has constrained research studying 

the link between staffing and outcomes. While nurse leaders have been discussing the need to 

measure outcomes sensitive to nursing practice back to at least the 1960s, widespread use of the 

terms “nurse/nursing-sensitive outcomes” and “patient outcomes potentially sensitive to nursing” 

is a relatively recent development. Nurse-sensitive measures have been defined as “processes 

and outcomes that are affected, provided, and/or influenced by nursing personnel, but for which 

nursing is not exclusively responsible.”13, 14 While some scholars feel the term “nurse-sensitive 

measure” is fundamentally incorrect because patient outcomes are influenced by so many 

factors, health care is practiced in a multidisciplinary context, and few aspects of patient care are 

the sole purview of nurses, there is a broad recognition that some outcomes reflect differences in 

the quality of nursing care patients receive and therefore presumably respond to the 

characteristics of the environments in which care is provided (including staffing levels). 

No matter what label these measures are given, measures that have conceptual and clinical 

links to the practice of nursing and are sensitive to variations in the structure and processes of 

nursing care are an essential ingredient in this area of research. Data sources from which to 

construct these measures must be identified, and exact definitions indicating how measures are to 

be calculated must be drafted. This is particularly critical if different individuals or groups are 

involved in compiling quality measures. There have been calls for standardization of measures of 

the quality of health care for some time,1, 15 along with outcome measures related to the quality 

of nursing care. Inconsistent definitions have slowed progress in research and interfered with 

comparability of results across studies. A paper, now under review, examines and compares 

common measures of adult, acute care nurse staffing, including unit-level hospital-generated data 

gleaned from the California Nursing Outcomes dataset, hospital-level payroll accounting data 

obtained from the California Office of Statewide Health Planning and Development, hospitallevel personnel data submitted to the American Hospital Association, and investigator research 

data obtained from the California Workforce Initiative Survey. Findings reveal important 

differences between measures that may explain at least some inconsistencies in results across the 

literature (Spetz, Donaldson, Aydin, personal communication February, 2007). 

Efforts to address the standardization imperative began with the American Nurses 

Association’s (ANA) first national nursing quality report card initiative. This initiative began 

with a literature search to identify potential nurse-sensitive quality indicators. Next, expert 

reviewers examined and validated a smaller, selected group of indicators and measures from 

2 
Staffing

among these.16 The ANA then funded six initial nursing quality report card indicator feasibility 

studies, which developed and refined these first sets of measures, documenting the quality of 

nursing care in acute care settings. The California Nursing Outcomes Coalition (CalNOC) was 

among the first State-based feasibility projects conducted by the ANA that ultimately served as 

the basis for the National Database for Nursing Quality Indicators (NDNQI) established in 1997. 

Maintaining an informal collaboration with the NDNQI, CalNOC continues to function as a 

regional nursing quality database, and more recently, CalNOC methods have been adapted by 

both the emerging Military Nursing Outcomes Database and VA Nursing Outcomes Database 

projects. All four groups currently collect and analyze unit-level data related to the associations 

between nurse staffing and the quality and safety of patient care. Together, they have formed an 

unofficial collaborative of nursing quality database projects.17–21 

The most recent initiative in standardizing staffing and outcomes measures for quality 

improvement and research purposes was undertaken by the National Quality Forum (NQF). The 

mission of the NQF is to improve American health care through consensus-based standards for 

quality measurement and public reporting related to whether health care services are safe, timely, 

beneficial, patient centered, equitable, and efficient. To advance standardization of nursesensitive quality measures and respond to authoritative recommendations from multiple IOM and 

Federal reports,9, 15, 22 the NQF convened an expert panel and established a rigorous consensus 

process to generate the Nation’s first panel of nursing-sensitive measures for public reporting. 

The aim of the expert panel was to explicate and endorse national voluntary consensus standards 

as a framework for measuring nursing-sensitive care and to inform related research. Potential 

nursing-sensitive performance measures were subjected to a rigorous and systematic vetting 

under the terms of the NQF Consensus Development Process, which included a thorough 

examination of evidence substantiating each measure’s sensitivity to nursing factors, alignment 

with existing requirements being made of providers, and validation/recommendations of 

advisory bodies to Federal agencies. As illustrated in Figure 1, the resulting first 15 NQF 

nursing-sensitive measurement standards were informed by earlier work by the NDNQI and 

CalNOC, as well as measures arising from formal research studies. 

3 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

Figure 1. Standardizing Nursing’s Quality Indicators 

Notes: CMS = Centers for Medicare and Medicaid Services; EHR = electronic health record; JCAHO = Joint 

Commission on Accreditation of Healthcare Organizations, now known as the Joint Commission; OMB = Office of 

Management and Budget. 

These measures represent a first (but by no means final) attempt to make nurse-sensitive 

outcomes visible to the broader community of payers and policymakers. The first 15 voluntary 

consensus standards for nursing-sensitive care intended for use in public reporting and policy 

initiatives included23 

1. Failure to rescue 

2. Pressure ulcer prevalence 

3. Falls 

4. Falls with injury 

5. Restraint (vest and limb) prevalence 

6. Urinary catheter-associated urinary tract infections (intensive care unit, ICU) 

7. Central line catheter-associated bloodstream infections (ICU) 

8. Ventilator-associated pneumonia (ICU) 

9. Smoking cessation counseling for acute myocardial infarction 

10. Smoking cessation counseling for pneumonia 

11. Smoking cessation counseling for heart failure 

12. Skill mix 

13. Nursing hours per patient day 

14. Practice Environment Scale-Nursing Work Index 

15. Voluntary turnover 

4 
Staffing

A Framework Relating Nurse Staffing to 

Patient Care Quality and Safety 

Figure 2 illustrates a set of conceptual relationships between the key variables in this review, 

including influences on staffing levels and factors influencing outcomes. These relationships 

form a set of interrelated pathways that link nurse staffing to patient care quality, safety, and 

outcomes. Notable is that each of the elements enclosed in a box—specifically administrative 

decisions, quality of nursing care, care needs, and safety and clinical outcomes—is influenced by 

a host of factors that are not detailed in the diagram and could each be the subject of its own 

literature review. 

Figure 2. Nurse Staffing, Quality of Care, and Outcomes 

• Staffing levels are set by administrators and are affected by forces that include budgetary 

considerations and features of local nurse labor markets. Administrative practices result 

in a structure of the nursing staff of an agency (nature of supervision) and staff or staff 

hours assigned to different subunits in a facility. These practices also affect the mix and 

characteristics of the nurse workforce, the model of care used in assigning staff and in 

providing care, and a wide range of workplace environments that affect how nurses 

practice. Other characteristics of the workplace environments noted in the literature 

included the physical environment, communication systems and collaboration, 

information systems, and relevant support services. All of these factors ultimately 

influence the “dose” or quantity of nursing time, as well as the quality of nursing care. 

• Variables included in the category of care needs of the patient include the acuity and 

complexity of the patient’s health status, as well as the patient’s comorbid medical 

conditions, functional status, family needs/resources, and capacity for self-care. The 

vulnerabilities of patients for adverse events varies and changes over the course of a 

hospital stay or episode of care. 

• The quality of nursing care relates to the appropriate execution of assessments and 

interventions intended to optimize patient outcomes and prevent adverse events. For 

5 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

example, the extent to which nurses assess the risk for falls in hospital patients upon 

admission, implement evidence-based fall-prevention protocols, and sustain such 

preventive interventions could each be developed into measures of nursing care quality. 

The quality of nursing care also includes attention to safety issues, for example, the 

accuracy of medication administration. Safe care also entails consistent monitoring 

tailored to patients’ conditions to guarantee early recognition of patient deterioration and, 

if problems are identified, benefit from a rapid, appropriate interdisciplinary team 

response to these issues.24 

The quality of care that nurses provide is influenced by individual nurse characteristics such 

as knowledge and experience, as well as human factors such as fatigue. The quality of care is 

also influenced by the systems nurses work in, which involve not only staffing levels, but also 

the needs of all the patients a nurse or nursing staff is responsible for, the availability and 

organization of other staff and support services, and the climate and culture created by leaders in 

that setting. The same nurse may provide care of differing quality to patients with similar needs 

under variable staffing conditions and in different work environments. 

• Safety outcomes include rates of errors in care as well as potentially preventable 

complications in at-risk patients. Safe practices that avoid errors and foreseeable 

complications of care can be thought of as either a basic element of or a precondition for 

delivering high-quality care, but are generally thought of as only one component of 

quality.

• Clinical outcomes (endpoints) of importance vary from patient to patient or by clinical 

population and include mortality, length of stay, self-care ability, adherence to treatment 

plans, and maintenance or improvement in functional status. Serious errors or 

complications often lead to poor clinical outcomes. So far, very few positive clinical 

outcomes have been studied by staffing-outcomes researchers, probably because of 

limited measures and data sources. 

The sheer number of variables and myriad linkages depicted suggest why precise evidencebased formulas for deploying nursing staff to ensure safe, high-quality patient care are 

impossible based on the knowledge on hand. In fact, such prescriptions may never be possible. 

Certainly, evidence-based guidelines for allocating resources to ensure optimal outcomes in 

acute care and other health care settings cannot be offered until working environments, staffing 

(beyond head counts and skill mix), patient needs, processes, and outcomes of care can be 

measured with precision.

Research investigating links between hospital nurse staffing and patient outcomes began with 

studies examining patient mortality. Reviews now include research examining a broad range of 

outcomes, including specific adverse events other than mortality. Although many studies support 

a link between lower nurse staffing and higher rates of negative nurse-sensitive safety 

outcomes,25–27 reviews of two decades of research revealed inconsistent results across studies.25–30 

State of Science on the Relationship Between 

Nurse Staffing and Patient Outcomes 

Before examining the state of the scientific literature on the relationship between nurse 

staffing and clinical outcomes, it is important to consider common challenges of research in this 

arena. Investigators face at least two fundamental problems when designing staffing-outcomes 

studies: first, finding suitable data sources and measures for staffing and patient outcomes, and 

6 
Staffing

second, linking the two types of variables to reach valid conclusions. As noted earlier in this 

chapter, because of limitations in measures, data sources, and analytic methods, researchers 

generally ask a different question in their studies (Is there a correlation between staffing and 

patient care outcomes?) than the questions that are of primary concern to patients, clinicians, 

managers, and policymakers (What staffing levels are safe under a specific set of 

circumstances?).31 Nonetheless, researchers in this field deserve a great deal of credit for making 

creative use of a variety of data sources not originally developed for research (or research on 

staffing and outcomes) to generate a great deal of evidence that has fueled discussion in the 

practice, management, and policy communities. 

Data Sources, Measures, and Challenges 

As clinical trials or controlled experiments are difficult if not impossible to conduct in this 

area, observational designs must be optimized as much as possible. When outcomes are 

compared across hospitals or other health care organizations as a whole or their clinical units or 

microsystems, frequently the research design that results from data linkages and analyses is 

cross-sectional and correlational in nature. Staffing levels and patient outcomes from 

approximately the same time are analyzed to determine whether a correlation exists between the 

two. As all students of research methods know, correlational designs are more limited than 

experiments for determining the extent to which causal links exist between staffing levels and 

outcomes. Factors other than nurse staffing can vary alongside staffing levels, so whether or not 

certain different staffing levels directly lead to better or worse outcomes cannot be determined 

with certainty from correlational designs. Such factors include other aspects of the environment 

in which care is provided (for example the availability of supplies, quality of physician care 

and/or other services and supports). Statistical methods can control for obvious factors that 

influence or are otherwise associated with staffing levels (such as hospital size, academic 

affiliation, or rural-urban location). Nonetheless, it is impossible to measure and account for all 

possible confounding variables (or competing explanations for findings) in the typical designs of 

these studies. Maximizing returns on correlational research designs involving staffing requires 

careful selection of variables and clearly articulating the theoretical and/or empirical bases for 

choosing them.

Tables 1 and 2 provide brief overviews of types of measures and the questions consumers of 

staffing outcomes research might consider in appraising individual studies. The discussion that 

follows is intended to emphasize a few fundamental points before turning to the findings in the 

literature itself. 

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Patient Safety and Quality: An Evidence-Based Handbook for Nurses

Table 1. A Typology of Measures in the Staffing-Outcomes Literature 

Variable Sources of Data Types 

Staffing • Records from health care facility 

operations (assignment sheets, 

scheduling grids) 

• Data submitted to regulatory 

bodies 

• Surveys of staff regarding 

staffing levels and/or workload 

Major types 

• Staff/staffed hours divided by patient/service volume 

• Credentials/qualifications of nursing staff (higher or lower in 

relation to total): licensed vs. unlicensed; level of licensure; 

highest degree, professional certification; years of 

experience 

• Voluntary turnover 

• Use of contract or agency staff 

Important distinctions 

• Level of measurement within the organization (whole 

facility/department vs. unit) 

• Roles of staff measured (such as staff involved in “direct 

patient care” vs. all nursing staff) 

• Time frame (shift/day/week/month/quarter/year) 

Outcome • Patient records, discharge 

abstracts, incident reports, or 

other byproducts of care 

delivery (including 

reimbursement) 

• Prospective surveillance for 

specific events (such as falls 

and pressure ulcers) 

• Surveys of patients/families and 

providers 

Occurrence of events suggestive of poor (or less commonly, 

high) quality of care or nurse work-related outcomes 

Level of measurement 

• Individual patients/nurses 

• Subunits (e.g., nursing units) of organizations 

• Entire facilities 

Table 2. Major Methodological Considerations in This Literature 

Design Feature Questions to Ask 

Measurement of staffing Do the staffing measures reflect the type and “dose” of staff actually caring for the 

patients being studied? 

Were the staffing measures collected in a consistent manner (using common 

definitions) across the organizational units/time periods? 

Measurement of outcomes Were outcomes assessed in comparable ways across patients and across settings 

(units or institutions or time periods)? 

Do data sources allow a distinction between complicating conditions present when 

care was undertaken (which should be considered in the analyses in risk adjustment 

(below)) from conditions that appeared during care (that are potentially outcomes of 

nursing care during the hospitalization)? 

Were outcomes assessed completely/comprehensively for all patients? What evidence 

is there regarding the consistency of documentation for the outcomes in question in 

the data sources? 

Does the outcome in question have a plausible association with nursing practice, or is 

it primarily/entirely associated with factors outside the control of providers? 

Risk adjustment Have the authors conducted fair comparisons between rates of adverse events across 

hospitals units or time periods by considering potentially important differences in the 

patients treated across those settings and/or over time? 

8 
Staffing

Design Feature Questions to Ask 

Data linkage To what extent do staffing measures represent conditions at the times and places 

where nursing care affecting the outcomes and measured for this study is given? 

Are outcomes attributed to the locations of care where nursing services actually 

influence the outcome, or do they also reflect the place where detection of the 

outcome occurs? 

Control for confounding 

factors 

Have other aspects of the environments in which patients are cared for that might 

affect the outcomes been measured and analyzed? 

E.g., availability of equipment/supplies, quality of physician care, other types of facility 

personnel, hospital size, academic affiliation, rural-urban location 

Statistical modeling If the study examines an outcome that is rare in the patient population, has this been 

considered in any modeling? How is skewness of the data managed? 

If the subjects of the study are grouped or nested within larger organizational units 

(e.g., patients within nursing units within hospitals), has this been handled by the 

analytic strategy? 

Do at least some of the analyses presented depict the complexity of associations 

between the factors involved through some type of statistical modeling that evaluates 

impacts of variables simultaneously? 

Staffing 

Staffing levels can be reported or calculated for an entire health care organization or for an 

operational level within an organization (a specific unit, department, or division). Specific time 

frames (at the shift level and as a daily, weekly, or yearly average) must be identified to ensure 

common meaning among collectors of the data, those analyzing it, and individuals attempting to 

interpret results of analyses. 

In many cases, staffing measures are calculated for entire hospitals over a 1-year period. It is 

fairly common to average (or aggregate) staffing across all shifts, for instance, or across all day 

shifts in a month, quarter, or year and sometimes also across all the units of hospitals. The 

resulting measures, while giving an imprecise idea of what specific conditions nurses and 

patients experienced at particular points, are general indicators of facilities’ investments in 

staffing. However, staffing levels on different units reflect differences in patient populations and 

illness severity (the most striking of which are seen between general care and critical care units). 

Furthermore, in practice, staffing is managed on a unit-by-unit, day-by-day, and shift-by-shift 

basis, with budgeting obviously done on a longer time horizon. For these reasons, some 

researchers argue that at least some research should be conducted where staffing is measured on 

a shift-specific and unit-specific basis instead of on a yearly, hospitalwide basis. A distinct, but 

growing, group of studies examined staffing conditions in subunits or microsystems of 

organizations (such as nursing units within hospitals) over shorter periods of time (for example, 

monthly or quarterly).17, 32–34

In addition to three sources of staffing data, there are also two basic types of staffing 

measures or variables. The first type divides a volume of nurses or nursing services by a quantity 

of patient care services. Common examples include patient-to-nurse ratios, hours of nursing care 

delivered by various subtypes of personnel per patient day (HPPD), and full-time equivalent 

(FTE) positions worked in relation to average patient census (ADC) over a particular time 

period. Patient-to-nurse ratios, HPPD figures, or FTE:ADC measures have the potential to both 

9 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

systematically overestimate or underestimate nurse workloads and the attention given to specific 

patients in relation to those patients’ needs, conditions, and clinical trajectories across units or 

institutions or over time.31 

The second major type of measure examines the credentials or qualifications of those staff 

members and expresses them as a proportion of staff with more versus less training (or viceversa). Commonly, the composition of the nursing staff employed on a unit or in a hospital in 

terms of unlicensed personnel, practical or vocational nurses, and registered nurses (RNs) is 

calculated. The specific types of educational preparation held by RNs (baccalaureate degrees 

versus associate degrees and diplomas) have also begun to be studied. Additional staffing-related 

characteristics studied include years of experience and professional certification. The incidence 

of voluntary turnover and the extent to which contract or agency staff provide care have also 

been studied. As will be discussed, the majority of the evidence related to hospital nurse staffing 

focuses on RNs rather than other types of personnel. 

For the most common measures, ratios and skill-mix, determining which staff members 

should be included in the calculations is important, given the diversity of staffing models in 

hospitals. Most researchers feel these statistics should reflect personnel who deliver direct care 

relevant to the patient outcomes studied. Whether or not to count charge nurses, nurse educators 

involved in bedside care, and nurses not assigned a patient load (but who nevertheless deliver 

important clinical services) can present problems, if not in principle, then in the reality of data 

that institutions actually collect. Outcomes research examining the use of advanced practice 

nurses in acute care—for instance, nurse practitioners and nurse anesthetists—to provide types of 

care traditionally delivered by medical staff and medical trainees has been done in a different 

tradition (analyzing the experiences of individual patients cared for by specific providers) and 

does not tend to focus on outcomes relevant to staff nurse practice; therefore these studies are not 

reviewed here. No studies were found that examined advanced practice nurse-to-patient ratios or 

skill mix in predicting acute care patient outcomes. There have been calls to examine advanced 

practice nurses supporting frontline nurses in resource roles (for instance, clinical nurse 

specialists who consult and assist in daily nursing care, staff development, and quality assurance) 

and their potential impact on patient outcomes. No empirical evidence of this type was found. 

Outcomes 

Clearly, capturing data about patient outcomes prospectively (i.e., as care is delivered) is the 

best option for obtaining precise, comprehensive, consistently collected data. This approach is 

the most challenging because of practical, ethical, and financial considerations. However, 

researchers can sometimes capitalize on prospective data collections already in progress. For 

instance, hospital-associated pressure ulcer prevalence surveys and patient falls incidence are 

commonly collected as part of standard patient care quality and safety activities at the level of 

individual nursing units in many institutions.18, 32 Many, but by no means all, studies in this area 

use secondary data not specifically intended for research purposes, such as patient medical 

records. Outcomes researchers often use condensed or abstracted versions of hospital patients’ 

records in the form of discharge abstracts, which contain data extracted from health care records 

about clinical diagnoses, comorbidities, procedures, and the disposition of patients at discharge.35

As there are concerns that the quality and reliability of clinical documentation varies widely,35

one author suggested that only a form of electronic medical record that forces contemporaneous 

recording of assessment data and interventions will permit true performance measurement in 

10 
Staffing

health care.36 Wider application of information technology in health care settings, anticipated to 

facilitate care delivery and improve quality and safety, is also expected to provide richer, higherquality data sources for strategic performance improvement that can be leveraged by outcomes 

researchers. 

Patients are not all at equal risk of experiencing negative outcomes. Elderly, chronically ill, 

and physiologically unstable patients, as well as those undergoing lengthy or complex treatment, 

are at much greater risk of experiencing various types of adverse events in care. For instance, 

data on falls may be consistently collected for all hospitalized patients but may not be 

particularly meaningful for obstetrical patients. Accurately interpreting differences in rates 

across health care settings or over time requires understanding the baseline risks patients have for 

various negative outcomes that are beyond the control of the health care providers. Ultimately 

this understanding is incorporated into research and evaluation efforts through risk adjustment 

methods, usually in two phases: (1) carefully defining the patient populations at risk—the 

denominator in rates; and (2) gathering reliable and valid data about baseline risk factors and 

analyzing them. Without sound risk adjustment, any associations between staffing and outcomes 

may be spurious; what may appear to be favorable or unfavorable rates of outcomes in different 

institutions may no longer seem so once the complexity or frailty of the patients being treated is 

considered.35 

The focus of this review is on staffing and safety outcomes. However, as was noted earlier, 

quality of care and clinical outcomes (and by extension, the larger domain of nursing-sensitive 

outcomes) include not only processes and outcomes related to avoiding negative health states, 

but also a broad category of positive impacts of sound nursing care. Knowledge about positive 

outcomes of care that are less likely to occur under low staffing conditions (or are more likely 

under higher levels) is extremely limited. The findings linking functional status, psychosocial 

adaptation to illness, and self-care capacities in acute care patients are at a very early stage37 but 

eventually will become an important part of this literature and the business case for investments 

in nurse staffing and care environments. 

Linkage 

In staffing-outcomes studies, researchers must match information from data sources about the 

conditions under which patients were cared for with clinical outcomes data on a patient-bypatient basis or in the form of an event rate for an organization or organizational subunit during a 

specific period of time. Ideally, errors or omissions in care would be observed and accurately 

tracked to a particular unit on a particular shift for which staffing data were also available. Most, 

but not all, large-scale studies have been hospital-level analyses of staffing and outcomes on an 

annual basis and have used large public data sources. 

Linkages of staffing with outcomes data involve both a temporal (time) component and a 

departmental or unit component. Many outcomes (endpoints) examined by staffing researchers 

are believed to reflect compounded errors and/or omissions over time across different 

departments of an institutions. These include some types of complications as well as patient 

deaths. Attribution of outcomes is complicated by the reality that patients are often exposed to 

more than one area of a hospital. For instance, they are sometimes initially treated in the 

emergency department, undergo surgery, and either experience postanesthesia care on a 

specialized unit or stay in an intensive care unit before receiving care on a general unit. If such a 

patient develops a pressure ulcer, at what point did low staffing and/or poor care lead to the 

11 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

pressure ulcer? Unfortunately, in hospital-level datasets, it is impossible to pinpoint the times 

and locations of the errors or omissions most responsible for a clinical endpoint. In the end, if 

outcomes information is available only for the hospital as a whole (which is the case in discharge 

abstracts, for instance), data linkage can happen only at the hospital level, even if staffing data 

were available for each unit in a facility. Similarly, if staffing data are available only as yearly 

averages, linkage can be done only on an annual basis, even if outcomes data are available daily 

or weekly. Linkages can be done only at the broadest levels (on the least-detailed basis or at the 

highest level of the organization) available in a dataset. Many patient outcomes measures (such 

as potentially preventable mortality) may actually be more meaningful if studied at the hospital 

level, while others (such as falls) may be appropriately examined at the unit level. 

One should recognize that common mismatches between the precision of staffing measures 

and the precision of outcome measures (i.e., the staffing across an entire year across all units in a 

hospital used as a predictor of outcomes for a patient treated for a short time in only a fraction of 

these units) compromise the likelihood that valid statistically significant associations will be 

found. This finding is particularly relevant when staffing statistics span a long time frame and 

therefore contain a great deal of noise—information about times other than the ones during 

which particular patients were being treated. High-quality staffing data, as well as patient 

assessment and intervention data—all of which are accurately date-stamped and available for 

many patients, units, and hospitals—will be necessary to overcome these linkage problems. Such 

advances may come in the next decades with increased automation of staffing functions and the 

evolution of the electronic medical record. 

Recent prospective unit-level analyses, now possible with datasets developed and maintained 

by the NDNQI, CalNOC, and the military hospital systems, make it possible to overcome some 

of these issues. These databases, although not risk adjusted, stratify data by unit type and hospital 

size and have adopted standardized measures of nurse staffing and quality of care. The resulting 

datasets provide opportunities to study how variations in unit-level staffing characteristics over 

time can influence patient outcomes (for instance, pressure ulcers and falls, as discussed later). 

As data sources do not exist for all types of staffing and outcomes measures at all levels of 

hospital organization (nor will they ever), research at both the unit level and the hospital level 

will continue, and both types of studies have the potential to inform understanding of the 

staffing-outcomes relationship. 

Research Evidence 

Perhaps staffing and outcomes research has such importance and relevance for clinicians and 

educators as well as for managers and policymakers, staffing-outcomes research is a frequently 

reviewed area of literature. As was just detailed, a diversity of study designs, data sources, and 

operational definitions of the key variables is characteristic of this literature, which makes 

synthesis of results challenging. Many judgments must be made about which studies are 

comparable, which findings (if any) contribute significantly to a conclusion about what this 

literature says, and perhaps regarding how to transform similar measures collected differently so 

they can be read side by side. The review of evidence here builds on a series of recent systematic 

reviews with well-defined search criteria.25, 27, 30, 38 At least one group of researchers conducted a 

formal meta-analysis that integrated the bulk of empirical findings in the hospital staffing 

literature and summarized effect sizes for specific staffing measures, outcomes, and clinical 

populations.30 This review was the most up-to-date identified within this search. 

12 
Staffing

Evidence Related to Acute Care Hospitals

Many researchers have identified higher levels of adverse patient events (mortality and 

complications, for instance) and negative nurse job outcomes (such as burnout) under poorer 

staffing conditions (specifically, thinner staffing coverage or fewer nurses per unit of patient care 

and, somewhat less commonly in these studies, lower skill mix/education level of staff). These 

findings have appeared in studies conducted using a variety of designs and examining hospital 

care in different geographical areas and over different time periods. On the whole, while some 

researchers have identified effects of 20 percent and greater reductions in negative outcomes 

associated with increased/improved (or the most generous) staffing, most studies in this literature 

show much smaller reductions in negative outcomes (under 10 percent and often much smaller 

ones) associated with the most favorable staffing conditions they observe.30 Given the relative 

rarity of some outcomes, these are subtle enough changes in outcomes to require observing many 

thousands, if not hundreds of thousands, of patients to identify staffing effects on the reduction 

of negative patient outcomes. Again, because of the tremendous number of factors involved in 

staffing decisions and their effects on patient care, and limitations in assessing patient 

characteristics, the specific staffing thresholds applicable to managers’ decisionmaking below 

which outcomes are demonstrably worse cannot be identified using this literature—a point 

emphasized in many reviews.24, 26 

The evidence table summarizes four major systematic reviews of the literature, approaches, 

and conclusions regarding the state of the evidence for specific outcomes or outcome types. In 

these papers, reviewers identify specific measurement types and established criteria for study 

inclusion in terms of design and reporting and examined a relatively complete group of the 

studies one by one to provide an overview of the state of findings as an integrated whole. 

The contrasts in the conclusions are interesting but are probably less important than the 

overall trend: research results point persuasively to a correlation of staffing with outcomes, but 

not all outcomes or datasets show such a connection. An additional important point is that nearly 

all studies connecting staffing parameters with outcomes have been conducted at the hospital 

(rather than the unit) level. 

Recent results emerging from the Agency for Healthcare Research and Quality (AHRQ) 

Patient Safety Working Conditions Program (2001–2005) offer some examples of recent unitlevel studies of staffing and its impacts on outcomes. In a 2-year AHRQ Working Conditions and 

Patient Safety study built on the work of CalNOC, Donaldson and colleagues17 engaged acute 

care hospitals using ANA nursing indicators for reporting staffing, patient safety, and quality 

indicators in a research, repository development, and benchmarking project. Data were drawn 

from 25 acute care, not-for-profit California hospital participants in the regional CalNOC. The 

sample included urban and rural hospitals with an average daily census from 100 to more than 

400 patients. Most patients’ principal diagnoses were medical (66 percent). The aims of the study 

were to test associations between daily nurse staffing on adult medical-surgical units and 

hospital-acquired pressure ulcers, patient falls, and other significant adverse events, if they were 

of sufficient volume to analyze. A prospective, descriptive, correlational design tested 

associations between patient outcome measures and daily unit-level nurse staffing, skill mix, 

hours of care (along with hours covered by supplemental agency staff), and workload. Falls were 

defined as “unplanned descents to the floor.” RN hours of care were significantly associated with 

the two focal outcomes. Unit activity index and hospital complexity (measured by bed size) were 

also significant predictors of falls. 

13 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

In another analysis, Donaldson and colleagues39 traced daily, unit-level direct care nurse 

staffing in 77 units across 25 hospitals over a 2-month period using data on staffing effectiveness 

(the match between hours of care and hours provided). By law in California, each hospital unit 

uses an institutionally selected, acuity-based workload measurement system to determine 

required hours of care for each patient. For each patient-care unit, the ratio of actual to required 

hours of care, was expressed as both a mean ratio and as a percentage of days on which required 

hours exceeded actual hours over the 7 days prior to a pressure ulcer prevalence study. Using 

Spearman rank correlations, the percentage of patients with hospital-associated pressure ulcers 

was significantly associated with the mean actual/required hours ratio for the prior 7 days (r’s = -

0.25, 63 df, P < 0.05), and with the percent days with the actual/required ratio <100 percent for 

the prior 7 days (r’s = 0.25, 63 df, P < 0.05). Larger actual/required ratios and actual/required 

ratios closer to 100 percent were associated with a lower percentage of patients with hospitalassociated pressure ulcers. These analyses linked unit-level staffing and safety-related outcomes 

data, and measured for time periods at the unit level closely and logically connected (staffing 

measures relevant to conditions before the outcome occurred). The findings are intriguing and 

suggest that the impact on patients of “short” staffing appeared a number of days later, as one 

would expect given the pathophysiology of pressure ulcers (since it takes a number of days of 

unrelieved pressure on a vulnerable area for tissue damage to occur). Both researchers and 

research consumers need to reflect on the time frames involved in the evolution of various 

outcomes when assessing the validity of data linkages across time and units. For instance, in 

contrast to the lags between quality problems in care and evidence of their impact on outcomes 

such as infections and pressure ulcers, practice conditions will tend to have more immediately 

observable impacts on outcomes like falls with injury and most adverse drug reactions. 

Recent legislation in California that introduced mandated nurse-to-patient ratios at the unit 

level provides an interesting context for studying the association of staffing and outcomes. 

CalNOC has reported early comparisons of staffing and outcomes in 268 medical-surgical and 

step-down units in 68 California hospitals during two 6-month intervals (Q1 and Q2 of 2002 and 

Q1 and Q2 of 2004) before and after introduction of the ratios. Data were stratified by hospital 

size and unit type. On medical-surgical units, mean total RN hours per patient day increased by 

20.8 percent, total nursing hours increased by 7.4 percent, the number of patients per licensed 

nurse decreased by 16.0 percent, and the portion of nonlicensed nursing hours decreased by 20.8 

percent. However, there were no statistically significant changes in the rate of patient falls or 

pressure ulcers on these units.40 These early data suggested that the introduction of mandated 

ratios may have led to changes in staffing metrics in California hospitals without yet attaining the 

goal of improving patient outcomes. 

Summary and Comment 

Researchers have generally found that lower staffing levels are associated with heightened 

risks of poor patient outcomes. Staffing levels, particularly those related to nurse workload, also 

appear related to occupational health issues (like back injuries and needlestick injuries) and 

psychological states and experiences (like burnout) that may represent precursors for nurse 

turnover from specific jobs as well as the profession. 

Associations are not identified every time they are expected in this area of research. Other 

aspects of hospital working conditions beyond staffing, as well individual nurse and patient 

14 
Staffing

characteristics, affect outcomes since negative outcomes are relatively uncommon even at the 

extremes of staffing and do not occur in every circumstance where staffing is low. 

A critical mass of studies established that nurse staffing is one of a number of variables 

worthy of attention in safety practice and research. There is little question that staffing influences 

at least some patient outcomes under at least some circumstances. Future research will clarify 

more subtle issues, such as the preferred methods for measuring staffing and the precise 

mechanisms through which the staffing-outcomes relationship operates in practice. 

Areas Where the Evidence Base Is Currently Limited 

Nurse executives and frontline managers make decisions about numbers of staff to assign to 

the various areas of their facilities. They also establish models of care to be used in caring for 

patients in terms of the constellation of nursing staff and distribution of responsibilities among 

professional nurses and other types of nursing staff. Patients and their families want assurances 

that enough staff are on duty to ensure that care is safe and meets patients’ needs. Policymakers 

want assurances that the nursing workforce in their jurisdictions is adequate; they also want to 

know whether or not regulatory intervention is necessary to ensure acceptable staffing levels and 

desirable patient outcomes. Staffing researchers are ultimately constrained by the limitations of 

their data in answering many questions of relevance to the real worlds of health care delivery and 

public policy. Investigators most commonly examined the correlations of complex patient 

outcomes with staffing measures derived at some distance from the delivery of care (perhaps 

aggregated over time). Researchers then asked whether measures of staffing and outcomes were 

statistically associated with each other. A clear distinction between direct conclusions from 

research findings and the opinions of particular authors or interest groups must be made.

It is impossible to specify parameters for staffing that will ensure safety based on current 

evidence without many qualifiers. The adequacy of staffing (the degree to which staffing covers 

patient needs) even for the same patients and nurses may change from hour to hour, particularly 

in acute care settings. Nurse-to-patient ratios and skill mixes in specific settings that are too low 

for safety still cannot be identified on the basis of the research literature, but decisions must be 

made on the basis of the judgments by frontline staff and their managers. On a related note, the 

specific nursing care processes that are more likely to be omitted or rendered less safe under 

different staffing conditions are not well understood, empirically speaking, and deserve further 

attention. 

A number of other areas identified in the staffing literature are relatively underdeveloped. 

Most research on staffing has been conducted in acute care settings; however, not all clinical 

areas within acute care have been equally well studied. A number of observers remarked that for 

the most part, the state of evidence regarding staffing’s impact on specialties outside of adult 

medical-surgical care is very limited. Data regarding settings for the care of children, 

childbearing families, and patients with mental health problems are currently very thin.25

Difficulties in collecting reliable, valid outcomes indicators that are potentially sensitive to 

nursing care in these other settings is probably at least partly to blame. 

The majority of nurses working in hospitals in the United States are, of course, registered 

nurses. Available evidence suggested that patients in hospitals that use more licensed practical 

nurses (LPNs) or vocational nurses may see worse outcomes.30, 40 Indeed, at least one costbenefit analysis of drawing on findings from one of the largest studies in the field40 suggested 

that increasing the proportion of RNs (and decreasing the proportion of practical nurses) in the 

15 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

composition of hospital staffs may be a more cost-effective measure and could have a bigger 

impact on outcomes than increasing hours of nursing care per patient day.41 Likewise, most 

reports in the literature dealing with unlicensed assistive personnel (UAPs) either failed to find 

associations with this type of staff or suggested worse outcomes in institutions with high levels 

of such personnel. There is no direct evidence that it is unsafe to employ LPNs in acute care 

settings,42, 43 nor is there empirical support that the use of unlicensed personnel is intrinsically 

related to poor outcomes. Use of practical nurses and UAPs can be driven by any and all of the 

factors outlined in Figure 2. Nonetheless, anecdotal evidence suggests that inadequately trained 

and/or supervised personnel of all kinds at times provide unsafe care; that operational problems 

having related, but distinct, causes and consequences can lead to substituting other types of 

workers for RNs and to safety problems; and that the savings associated with using lesser-trained 

workers sometimes prove to be false economies. The models of care under which LPNs and 

unlicensed care providers are employed (i.e., the exact roles of non-RN personnel and degree of 

oversight provided by RNs) has not been considered in research. While RNs have the broadest 

scope of practice of frontline nursing workers, it is far from established that 100 percent RN 

staffing is effective in all situations. Future research needs to identify the circumstances under 

which LPNs and UAPs can be used safely. Until then (and even when it does), local labor market 

realities, experience, and judgment will need to be used by leaders to establish skill mix and to 

define the models of care under which RNs, LPNs, and UAPs work. 

Early studies have offered early, tantalizing insights regarding a number of variables 

conceptually close to staffing. These findings include the educational preparation of RN staff in 

hospitals. Two recent studies44, 45 found that mortality in surgical and medical patients was lower 

in hospitals where higher proportions of staff nurses held baccalaureate degrees. The AHRQsponsored studies of California hospitals discussed above also suggested that a higher percentage 

of nurses holding bachelor’s and higher degrees was associated with lower fall rates. 

Additionally, in this latter work, units where higher percentages of RNs held specialty 

certification had lower proportions of restrained patients. Should these findings be borne out in 

future studies, there are important potential local and national policy implications. There is a 

clear need for more research. Similarly, while many feel experience and specialty training have 

logical associations with quality of care and patient safety, empirical data regarding their impact 

are very limited at present. 

Yet another area where data related to patient outcomes are thin relates to the impact of 

specific types of work environments on nurse-sensitive outcomes, and in particular the impact of 

the Magnet hospital model, which has been argued to produce superior patient outcomes (and 

safer care).46, 47 Such connections would make intuitive sense, since current Magnet criteria 

require adherence to many best practices in nursing management, including selection of a wellarticulated staffing model driven by data. To our knowledge, there are no studies yet to directly 

support a connection between safety and specific managerial approaches or to link Magnet status 

with patient outcomes in the current era of certification. However, early findings with respect to 

questions around the outcomes of the program are expected in the coming years. 

Evidence Related to Other Settings 

There has been intense interest in identifying staffing-outcomes relationships in long-term 

care settings. RNs are, of course, in the minority among the nursing staff in long-term care, with 

unlicensed providers providing the bulk of physical care in these facilities. There are many 

16 
Staffing

challenges in using existing documentation and databases to measure outcomes in long-term care 

facilities,48 some of which are shared with outcomes measurement in acute care. Long-term care 

researchers face special issues, specifically with respect to data reliability and measure stability, 

skewedness of measures, and selection and ascertainment bias (where types of patients at high 

risk for poor outcomes or who are more closely observed are concentrated in certain nursing 

homes).48

Despite these problems, a critical mass of studies suggests that long-term care facilities with 

the lowest licensed and unlicensed staffing levels among their peers show disproportionately 

worse patient outcomes. A study sponsored by the Centers for Medicare and Medicaid Services 

(CMS) suggested that among short-stay patients, skilled nursing facilities with the lowest 

staffing levels were 30 percent more likely to fall in the worst 10 percent of facilities for 

transfers to acute care for acute heart failure, electrolyte imbalances, sepsis, respiratory infection, 

and urinary tract infection. Facilities with staffing below thresholds of 2.78 hours of aide time 

and 0.75 hours of RN time had greater probability of having the worst outcome rates for longstay patients, including pressure ulcers, skin trauma, and weight loss.49 Similar conclusions were 

reached in a secondary analysis of data from a pressure ulcers study. In 1,376 residents of 82 

long-term care facilities, patients in facilities with more direct RN time (30–40 minutes per 

patient day and more) had fewer pressure ulcers, acute care hospitalizations, urinary tract 

infections, and urinary catheters, and less deterioration in ability to perform activities of daily 

living.50 In a national sample of nursing homes from 45 States, those that met CMS guidelines 

for RN and unlicensed hours per patient-day had statistically lower rates of lawsuits after 

controlling for a multitude of structural, market, and patient factors.51 Not all studies report such 

findings. Rantz and colleagues’52 analysis of outcomes in 92 nursing homes found that staffing 

levels did not predict facilities’ classification as having generally good, mediocre, or poor 

outcomes and found that on average, costs were somewhat higher in poor-outcome facilities. 

These researchers suggested that administrative practices other than staffing may play an 

important role in determining long-term care quality.

Home health is a growing sector in U.S. health care. Staffing models fall somewhere between 

acute care hospitals and long-term care in terms of the proportions of unlicensed personnel and 

practical nurses. Allocation of nursing time to patients presumably influences quality and 

thoroughness of nursing acts and assessments. There may be skill-mix issues as well. However, 

to date there have been no studies of home health agency staffing models, nurse workloads, or 

skill mix. OASIS (Outcomes Assessment and Information Set) data gathered by home health 

providers by mandate from the Medicare program, skillfully analyzed and interpreted, will offer 

opportunities to examine safety in home care in relation to staffing decisions.53 Similar 

statements can be made about nurse staffing in most other ambulatory and community settings as 

well. 

Summary of Current Best Practices 

The general conclusion of these studies conducted in various settings is that differences in 

outcomes are often observed between situations or institutions where staffing is high and those 

where it is low. A critical mass of data suggests that staffing at the lower end of the continuum 

may place patients and nurses at heightened risk of poor outcomes. Therefore, it appears 

hazardous to patients and staff to staff at the lowest levels relative to peer units and health care 

organizations. 

17 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

Limitations of cross-sectional observational designs that predominate in this literature have 

been reviewed extensively in the chapter. Prominent among these is that there is no guarantee 

that increasing staffing alone improves the process or outcomes of care. Nonetheless, it would 

appear wise to continue the widespread practice of adjusting staffing levels for setting, specialty, 

model of care, client needs, special circumstances, and trends in the frequency of outcomes 

potentially sensitive to nurse staffing. 

Evidence-Based Practice Implications 

A key implication arising from this review is that as much as possible, investigators should 

align their studies with emerging taxonomies and specifications of measures promulgated by 

authoritative sources (e.g., the Joint Commission). Continued proliferation of measures is 

slowing progress in this field. Standardized measurement will advance meta-analytic efforts and 

facilitate aggregation of data across studies. As hospitals and health systems are inundated with 

data-reporting demands, wise investigators will leverage ongoing measurement efforts by 

selecting core measures and common metrics already collected by hospitals. There is value for 

researchers to forge strategic partnerships with professional sponsors of public and private data 

repositories. Agencies and researchers alike will be served well by study designs that use already 

de-identified data and make minimal use of protected health information, particularly since the 

Health Insurance Portability and Accountability Act took effect in 2004. 

Likewise, both researchers and clinical administrators must fully harness the potential of new 

health information systems to capture clinical data. High-quality data on clinical performance 

will drive both scientific understanding and organizations’ strategic quests for excellence. Some 

authors suggested that competing on the analytics is a characteristic of high-performing 

organizations.54 

Leaders at all levels in the health care system must decide how to apply the findings of this 

literature. It is impossible to read and discuss this area of research without considering whether 

regulation of nurse staffing is a valid application of the findings, especially in the current climate 

in health care. As mentioned earlier, there are no evidence-based minimum staffing ratios,27, 55

although clinicians and managers set operating ratios every day, largely on the basis of their 

experience and, to a lesser extent, from extrapolations of researchers’ findings. As in all aspects 

of health care management, empirical evidence needs to be interpreted in the context of local 

data and experience. Although unsatisfying to proponents and opponents of regulation, it bears 

mentioning that a like or dislike of minimum ratios is often based on one’s values and opinions 

about the capacity and inclination of health care leaders to make responsible staffing decisions 

autonomously. 

Even absent any specific legal mandates to do so, benchmarking staffing and outcomes 

against peers and attempting to avoid extremes of low staffing and high adverse events, keeping 

in mind important contextual factors when making comparisons, is undoubtedly the best 

administrative practice. Keeping in mind that there are many factors affecting the outcomes of 

care (see Figure 2), a range of efforts needs to be undertaken to increase the quality of clinical 

practice or reliability, defined by the Institute for Healthcare Improvement as “the number of 

actions that achieve the intended result divided by the number of actions taken during a target 

time period.”56

Executives and managers make a host of decisions beyond those involving staffing that affect 

the clinical effectiveness of nursing staff. Thought leaders in the arena of patient safety practices 

18 
Staffing

have identified a number of organizational strategies that may constitute better practice in 

managing the impact of nurse staffing on patient care quality and safety. For example, efforts to 

optimize clinical, throughput flow and reduce practice variability may reduce threats to staff and 

patients due to system and personnel overload.57 Managing supply and demand in health care 

settings by smoothing peaks and valleys of patient flow,58 as well as staffing levels, may be 

effective in modulating workflow extremes that cause staff distress and might pose risks to 

patients. Implementing systems that enable staff to standardize high-volume common practices 

(such as patient education, discharge planning, and risk assessments) may be expected to 

increase efficiency, while enabling staff to customize these highly effective interventions to the 

unique characteristics of the patient/family. Engaging staff in self-governance related to patient 

flow has also been cited as a promising best practice. Considered key to safe staffing, 

professional judgment as the gold standard establishes the threshold for safe patient care in a 

given clinical setting,59 as nurses use a systematic decision matrix to determine if the staff on a 

particular unit can accept responsibility for additional patients. Informed by understanding of 

scientific conclusions linking staffing and patient outcomes in comparable settings, the selfgoverning and administrative teams of the future may use internally generated data to support 

decisions related to staffing adequacy and effectiveness.60 Through systematic microsystem 

(unit) assessment, combined with concurrent measurement tracing structure, processes, and 

outcomes of care, it is possible to calibrate the expertise and dose of the nurse and individualize 

interventions to the unique characteristics and needs of the patient, optimizing patient care.61 

As clinicians and administrators in clinical settings gain greater access to real-time data that 

enable them to explore links between structure, process, and outcomes, increasingly 

sophisticated tools such as virtual dashboards are promising.18 Despite a tradition in nursing that 

has emphasized scientific inquiry as a fundamental source of evidence for practice, there is 

growing awareness that data that emerge from practice and practitioners (particularly when 

collected using systematic methods and with high-quality measures) may be a vital source of 

material for research in this and other areas of policy-relevant inquiry.62 

Research Implications 

There are a great many questions in this field that are still unanswered. There is a clear need 

to investigate processes of care that are specific to nursing that are associated with safer patient 

care as well as safer, more efficient interdisciplinary team functioning. Data issues (a lack of 

measures and of data sources) are a major barrier to work on care delivery. In a discussion of 

nursing workload measurement tools, the International Council of Nurses noted that “existing 

tools are unable to capture more than 40 percent of nursing work”63 (p. 16). Future research must 

tackle the black box of nursing practice by acknowledging the complexity of nursing assessment, 

planning, intervention, and evaluation. Addressing variance in the quality of patient care 

performed by nurses is key to interpreting inconsistencies in the nurse staffing literature and 

perhaps at the heart of efforts to improve patient care outcomes. Ultimately, it is a priority for 

future research to explicate links between structure, process, and outcome in nursing practice and 

patient care.64

As indicated before, study of models of care using non-RN staff in acute care, of the impacts 

of high levels of staffing on health-promoting nursing interventions and nurse-sensitive 

outcomes, and of staffing and outcomes in understudied specialties in acute care and in nonacute 

care settings is vital. Ultimately, research in this area is on a track to assist in establishing 

19 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

evidence-based management54 that complements the profession’s ongoing efforts in evidencebased practice. 

Conclusion 

From a research tradition in which nurse staffing factors were primarily background 

variables, the study of nurse staffing and patient outcomes has emerged as a legitimate and 

strategically crucial field of inquiry. However, despite significant growth in the number and 

sophistication of studies responding to public policy and provider demand for these findings, 

results have been inconsistent. This chapter highlights the methodologic challenges inherent in 

this area of inquiry and explicates how the diversity in measures and units of analyses confound 

literature synthesis. In the face of myriad pressures to adopt a position for or against mandated 

nurse-to-patient ratios, the state of the young science does not permit precision in prescribing 

safe ratios. In fact, it may be concluded that further research is crucial to tease out the nuances in 

the staffing-outcomes equation. It is essential to advancing the field that future studies replicate, 

extend, and refine the current body of knowledge, making explicit how characteristics of the 

workforce, now barely considered (for example, years of experience or professional 

certification), in addition to the “dose” of the nurse, are linked to processes of care that 

ultimately result in clinical outcomes (both desirable and adverse). Until then, selected better 

practices have been noted, with the potential to contribute to pragmatic efforts to improve patient 

care quality and safety in hospitals. 

Search Strategy 

The literature on nurse staffing and patient safety is rapidly evolving, very heterogeneous in 

terms of measures and methods, and equivocal in terms of many of its conclusions regarding 

specific measures. Our aim was to describe broad trends in this literature, and to this end, we 

based our work on four systematic, integrated reviews that contained detailed search criteria and 

clearly-articulated inclusion criteria and provided detailed syntheses of findings. Three of these 

four reviews were drawn from AHRQ publications, the most recent of which30 included articles 

we had identified in our own searches of PubMed® and CINAHL® databases since 2002 and 

2003 using the terms “nurse staffing,” “safety,” and “outcomes.” 

Author Affiliations 

Sean P. Clarke, R.N., Ph.D., C.R.N.P., F.A.A.N., associate professor, University of 

Pennsylvania School of Nursing. E-mail: sclarke@nursing.upenn.edu.

Nancy E. Donaldson, R.N., D.N.Sc., F.A.A.N., clinical professor, University of California, 

San Francisco, School of Nursing. E-mail: nancy.donaldson@nursing.ucsf.edu. 

20 
Staffing

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Patient Safety and Quality: An Evidence-Based Handbook for Nurses

Evidence Table. Major Integrative Reviews of the Staffing-Outcomes Literature 

Study Methods Outcomes Associated 

With Staffing 

Outcomes for Which Data 

Considered Limited or Mixed 

Seago 200125 16 studies dealing with 

staffing-safety outcomes 

relationships, 1990–2000 

Grading of design and 

outcome measures 

NPR: 

Length of stay 

Nosocomial infections (UTI, 

postoperative infections, 

pneumonia) 

Pressure ulcers 

NPR: 

Mortality 

Unplanned readmissions 

Failure to rescue 

Skill mix: 

Negative patient outcomes 

Hickam 200338 26 studies examining nurse 

workload/staffing ratios and 

safety outcomes, 1980–

2002 (22 published 1996 or 

later) 

Grading of design 

appropriateness and 

execution 

Workload and skill mix: 

Nonfatal adverse events 

Workload: 

Medication errors 

Mortality 

Recognition of errors 

Probability that errors will affect 

outcomes 

Lang 200427 43 studies examining effects 

of nurse staffing on patient, 

nurse, and hospital 

outcomes, 1980-2003, 

excluding studies of ICUs 

and long-term care facilities 

General comments on 

methods limitations for all 

studies; grading of effect 

sizes 

Patient outcomes: 

Failure to rescue 

Mortality 

Shock in medical patients; 

gastrointestinal 

hemorrhage 

Nurse outcomes: 

Nurse needlestick injuries 

Burnout 

Institutional outcomes: 

Documentation quality 

Extended length of stay 

Patient outcomes: 

Pneumonia 

UTIs 

Falls 

Nosocomial infections 

Medication errors 

Pressure ulcers 

Patient satisfaction 

Morbidity 

Adverse drug events 

Intravenous errors 

Cardiac arrests 

Patient injuries 

Nurse outcomes: 

Nurse job satisfaction 

Absenteeism 

Institutional outcomes: 

Assaults on psychiatric units 

Hospital financial outcomes 

24 
Staffing

Study Methods Outcomes Associated 

With Staffing 

Outcomes for Which Data 

Considered Limited or Mixed 

Kane 200730 94 studies examining 

associations of nurse-topatient and hours per 

patient-day on patient 

outcomes in hospital 

practice from the United 

States and Canada, 1987-

2005 

Formal meta-analysis 

(calculation of pooled effect 

sizes across studies and 

subpopulations) 

incorporating evaluation of 

methodological quality 

RN NPR: 

Hospital-related mortality 

Failure to rescue+ 

Medical complications 

Unplanned extubation* 

Pulmonary failure*+ 

Hospital-acquired 

pneumonia* 

Bloodstream infections+ 

Cardiopulmonary 

resuscitation*+ 

Extended length of stay 

* Evidence of a stronger effect 

or more consistent evidence in 

ICUs 

+ Evidence of a stronger effect 

or more consistent evidence in 

surgical patients 

HPPD (all staff types)

Mortality 

Shock 

Upper gastrointestinal 

bleeding 

Nosocomial infection 

Extended length of stay 

RN HPPD: 

Limited support 

LPN and UAP NPR and HPPD: 

Trend toward association of 

worse outcomes with higher 

use/levels 

NPR: Nurse-to-patient ratios 

ICU: Intensive care unit 

RN: Registered nurse 

LPN: Licensed practical nurse 

UAP: Unlicensed assistive personnel 

HPPD: Hours of care per patient-day 

UTI: Urinary tract infection

25