The context of an organization is made up of

the external and internal environment in which it operates. If the nursing unit is considered to be the focal

unit of interest, the external environment encompasses

factors outside the boundaries of the unit, but within those

of the total organization. The internal environment comprises factors within the boundaries of the unit such as

work delivery patterns and characteristics of the work

group.

In considering contextual effects on patient outcomes, the research emphasis is usually on aggregates

of patients who are heterogenous with respect to illness.

Research in this area, usually, but not always, focuses

on global group level outcomes such as length of hospital stay, mortality, morbidity, satisfaction and cost. There

are a number of limitations to the use of these outcome

measures primarily due to their lack of sensitivity. In

addition, analysis in this type of research is hindered by

the quality of data sources and the need for group level

analysis.

Selected research on three external environmental variables and four internal environmental variables

was reviewed to examine the findings in terms of impact on patient outcomes. The external variables were

Hospital Ownership, Hospital Teaching Status, and

Volume of Procedures. The internal environmental variables were Hospital to Home Nursing Management,

Multidisciplinary Coordination/Collaboration, Job Satisfaction and, Education.

Results of studies on both Hospital Ownership

and Teaching Status are inconsistent. There does seem

to be some indication that teaching hospital status or

affiliation with medical schools could have a positive

impact on mortality rates, but these findings tend to be

diagnosis dependent. In terms of Volume of Procedures,

mortality seems to be reduced when surgical patients

are considered, but for medical patients, the effect of

high volume is questionable. A major difficulty with

studies of these three variables are the considerable interaction effects on outcomes.

The research on internal environmental effects

on patient outcomes is limited by two factors: Inadequate replication and the study of organizational outcomes, rather than patient outcomes. The variables selected for examination have received a great deal of

discriptive attention in the literature as ways to improve

patient outcomes.

A number of investigators are examining models of nursing management that extends from the hospital to the home. Such specialized nursing care seems to

have a significant impact on patient cost outcomes.

There are also some indications that this care delivery

method may have a positive influence on some indices

of morbidity such as hospitalization or rehospitalization.

For acutely ill patients, research has also provided beginning evidence that mortality is reduced in units evidencing greater collaboration between nurses and physicians. Although job satisfaction is frequently cited as

Contextual Factors Influencing Patient Outcomes

Individual/Group/Environment: Interactions and Clinical Practice Interface

Joyce A. Verran PhD, RN, FAAN

Barbara Mark, PhD, RN
a desirable organizational outcome, little research has

been done on its influence on patient outcomes. Based

upon a limited data base, there exists a significant relationship of staff job satisfaction with client satisfaction.

Finally, educational level of staff is often considered to

be associated with improved patient care. Unfortunately,

little research connecting education with patient outcomes has been conducted. Two studies that examine

the effect of continuing education programs on outcomes

present inconclusive results.

Introduction

Our purpose in this paper is to review the literature examining the effects of contextual factors on

patient outcomes. First, we suggest a taxonomy of outcomes research approaches to assist in the delineation

of our specific focus. Next, we define the independent

variable, context, as it will be used in the paper. Third,

the literature on selected contextual variables and their

relationship to patient outcomes is reviewed. Finally,

methodological issues involved in research examining

the effect of contextual factors on outcomes are briefly

addressed. A disclaimer is, however, warranted before

beginning. Most of the research in the area of context

deals with hospitals, clinics or group practice entities as

organizations. Therefore, while we recognize the importance of nursing beyond bureaucracy, of necessity,

most of our examples will refer to hospitals or other organizations providing health care services. The second

part of the disclaimer has to do with age and boundaries

of the research cited. In order to limit the review to

some extent only research published within the last decade is included. Only those contextual variables are

examined that have been either researched in some depth

or which are popularly included as being significant to a

change in outcomes.

A Taxonomy of Outcomes Research Approaches

Two axes form the basis of the proposed taxonomy shown in Figure 1. The horizontal axis refers to

the level of analysis, i.e. whether one is interested in

studying individual or group level relationships. The

vertical axis relates to the level of variability in the client population in terms of the degree to which the population is homogenous or heterogeneous with respect to

illness or diagnosis.

Quadrant 1 represents research with individuals who are homogeneous with respect to illness. Intervention would be directed toward individual treatment

and individual response. Outcomes are then analyzed

at an individual level, even though they are reported in

grouped form, and are referred back to the individual.

Quadrant 2 also deals with homogeneous groups

of clients but the intervention in is directed toward the

group of clients as a group. Appropriate group level

outcomes, related to the specific illness of the client

group, should be reported and analyzed. Results from

this type of research are referable only to the group not

to the individuals who are members of that group.

Quadrant 3 is characterized by the study of individuals who are heterogeneous with respect to their

diseases, but who exhibit similar symptoms, for example,

individuals who suffer sleeplessness, pain or stress.

Research in this quadrant would again have the individual as the focus and examine individual response to

intervention.

In the fourth quadrant, the research emphasis is

on aggregates of patients who are heterogenous with

respect to illness. Research in this area usually focuses

on global group level outcomes such as length of hospital stay, mortality, morbidity, satisfaction and cost. For

example, health services research may investigate the

relationship between certain organizational characteristics and length of stay, while nursing research may examine the comparative costs of differing nursing prac-
tice models. In research on global outcome indicators,

however, the close correspondence between research

problem or clinical condition and outcomes disappears,

opening a virtual Pandora’s box of conceptual and methodological controversies about the “appropriate” selection and measurement an analysis of outcomes. Much

of the research that investigates the effect of context on

patient outcomes would logically fall in this last quadrant of the taxonomy. Some studies however, analyze

the dependent variable at the individual level even though

it is a global indicator of outcome. In general, the research that we will be reviewing next is most logically

referable to the fourth quadrant of the taxonomy.

Context Defined

The most important aspect of an organization’s

context is the environment in which it operates. According to Duncan (1972), the environment of an organization consists of the social and physical factors that

are considered by individuals when making decisions.

Much of the work on the effect of contextual factors on

patient outcomes has been done with the nursing unit as

the focal unit. When the focal unit is defined in this

manner, the external environment encompasses factors

outside the boundaries of that unit, but within the boundaries of the total organization. The external environment for the unit, then, includes the “macro” characteristics of the organization in which it operates, such as

size, teaching status, ownership and volume of procedures. The internal environment comprises factors

within the boundaries of the unit such as work delivery

patterns, attributes of individuals as members of the work

group and characteristics of the work group itself. This

internal environment is made up of the “micro” characteristics of the organization. Taken together, the external and internal environments comprise the nursing unit’s

context. We will first review selected research that relates to the effects of the external environment on patient outcomes.

External Environmental Effects on Patient Outcomes

Nursing research has generally not taken into

account organizational characteristics that may confound

the relationships between selected independent variables

and outcome measures. In health services research, three

organizational characteristics and their impact on patient

outcomes have been examined in some depth. They are:

1) the type of hospital ownership, 2) hospital teaching

status, and, 3) volume of surgical procedures. Our discussion focuses on selected studies that exemplify both

representative findings and typical methodological issues. For each of the comparison, all studies employ

mortality rate as the outcome of interest, despite the rather

obvious problems in using such a gross indicator of outcome (Chassin et al., 1989; Demlo, 1990; Fink, Yano &

Brook, 1989). Tables 1, 2 and 3 present summaries of

these studies.

Hospital Ownership

Hospital ownership has been studied from two,

often combined, perspectives: whether the hospital is

public or private, and whether it is investor-owned (IO)

[proprietary] or not-for-profit (NFP). Federally owned

and operated hospitals, such as Veterans Administration and Public Health Service hospitals are typically

excluded from consideration. Gaumer (1986), for example, examined a large sample of short-term U.S. hospitals with regard to four different outcomes: 1) in-hospital mortality for Medicare patients undergoing any of

eight elective surgical procedures1

; 2) mortality for Medicare patients 180 days following hospital admission for

the same procedures; 3) 90 day post-discharge readmission rates, again for the same procedures; and 4) JCAHO

accreditation status. Using the ratio of actual to expected

mortality rates, in order to standardize differences in
severity, Gaumer found that for all procedures, there

were significantly lower in-hospital mortality rates in

IOs compared with NFPs, but no consistent pattern

emerged when procedures were examined separately.

There were no significant differences between IOs and

NFPs for either 180 day mortality rates or 90 day readmissions, but IOs were 11% less likely than NFPs to

have full JCAH accreditation status. At a time when

there was growing concern about the potential of investor-owned hospitals to provide poor quality care, Gaumer

concluded that there was no evidence for “concluding

that the profit motive, in the aggregate, has compromised

patient care to the point of causing large and systematic

differences in post-operative mortality or readmission”

(p. 367).

Shortell and Hughes (1988) examined the relationships between regulation, competition and ownership and in-hospital mortality rates for over 214,000

patients in 981 U.S. hospitals. They concentrated on

deaths of Medicare patients for 16 clinical conditions

(10 operative, 5 non-operative, and an additional category called “complications and misadventures” that

referred to preventable complications). Using the

HCFA’s Medical Provider Analysis and Review

(MEDPAR) data base, the researchers found no significant differences in in-hospital mortality for any ownership category: independent investor-owned, multi-hospital investor-owned, independent not for profit, or not

for profit multi-hospital system.

While Gaumer (1986) and Shortell and Hughes

(1988) used HCFA data to study mortality rates among

Medicare patients, Kelly and Hellinger (1986) used data

from the Hospital Cost and Utilization project (HCUP)

of the National Center for Health Services Research

(NCHSR) to examine in-hospital post-surgical mortality for all patients between the ages of 18 and 99 with

four surgically treated conditions: 1) stomach cancer

with abdominal surgery, 2) peptic ulcer with surgery, 3)

colon cancer with surgery and, 4) abdominal aneurysm

with surgery. Using a sample of 373 short-term general

hospitals, the authors found that for patients undergoing

surgery for peptic ulcer or colon cancer, being in a public hospital significantly increased the probability of

mortality. Patients experiencing surgery for cancer had

slightly, but not significantly better outcomes in public

hospitals, while patients with abdominal aneurysms had

slightly, but again, not significantly, worse outcomes in

public hospitals.

Hartz et al. (1989) however, discovered poorer

outcomes in for profit hospitals. They used the HCFA

Medicare Hospital Mortality Information to examine all

in-hospital deaths of Medicare patients in a sample of

3100 hospitals. Using the HCFA’s predicted mortality

rate to adjust for severity, the researchers found investor-owned hospitals had higher mortality rates than notfor-profit hospitals, after adjustment for severity of illness. Private not for profit hospitals had lower adjusted

mortality rates than did private for-profit hospitals. In

addition, osteopathic and public hospitals had high mortality rates than other types of hospitals.

Results of these studies are inconsistent, and

frequently are diagnosis or procedure dependent. Differences in findings can be explained partly by different

researchers focusing on different types of conditions

(medical vs. surgical), different patient populations

(Medicare vs. non-Medicare), different hospital samples,

and different methodologies for severity adjustments.

Clearly, however, nursing research that examines differences in patient outcomes across hospitals must include hospital ownership as part of model specification.

Teaching Status

In many studies, a hospitals’s teaching status is

often simply coded as a control variable. Few studies

investigate the impact of teaching status, or level of involvement in teaching on patient outcomes. Yet, more

complex case mix, a higher proportion of board certi-
fied medical specialists and better qualified nurses may

all be characteristics of teaching hospitals that will relate to outcomes.

Kelly and Hellinger (1986), using the HCUP

data set described earlier, measured three degrees of

hospital involvement in teaching. Members of the Council of Teaching Hospitals (COTH) were assumed to have

the highest level of involvement in teaching, medical

school affiliation without COTH membership (MSA,

non-COTH) suggested a somewhat lower level of involvement, while non-medical school affiliated, nonCOTH hospitals (non-MSA, non-COTH) would clearly

have the lowest, if any, involvement in teaching. For

seven of eight comparisons (i.e. four surgical treatments

by two levels of teaching involvement, with the nonMSA, non-COTH group omitted), involvement in teaching decreased the likelihood of in-hospital mortality. For

surgery for colon cancer, the difference was significant

for both levels of teaching involvement, while for abdominal aneurysm, the difference was significant for

MSA hospitals, but not for COTH hospitals. However,

ulcer patients undergoing abdominal surgery in COTH

hospitals had somewhat, but not significantly worse

outcomes.

Kelly (1990) reporting on NCHSR HCUP data

to study seven groups of patients (diabetes, hypertension, CABG, cardiac catheterization, cholecystectomy,

atherosclerosis and cranial injury) using a five category

classification of teaching status to study in-hospital

mortality, found that teaching hospital status significantly

improved the outcomes for atherosclerosis patients, and

that the more involved the hospital was in teaching, the

less likely the patient was to die. The results for cranial

injury, however, were exactly the opposite: patients in

teaching hospitals had significantly worse outcomes than

those in non-teaching hospitals, and the more involved

in teaching the hospital was, the more likely the patient

was to die. For the five other conditions investigated,

there were no differences between types of hospitals.

Hartz et al. (1989) also examined the relationship of teaching status and outcome. Hospitals were

designated simply as teaching (members of COTH) or

non-teaching. Mean mortality rate, adjusted for severity, for patients in teaching hospitals was significantly

lower than for patients in non-teaching hospitals. Hospitals with lower mortality rates were also characterized

by having a significantly higher proportion of board certified physicians, a significantly higher proportion of

nurses who were RNS, higher occupancy rate, and a

higher technology index. In a multivariate regression

equation explaining 54.3% of the variance in patient

mortality, the same characteristics described hospitals

with lower adjusted mortality rates. The most important predictors of lower mortality rates were board certification of physicians and the proportion of nurses who

were RNs.

Similar to studies on ownership, findings on the

relationship between teaching status and patient outcome

are inconclusive. Yet, the results do suggest fruitful areas for further research in nursing, particularly with regard to the impact on mortality of increasing the overall

proportion of registered nurses in hospitals2

.

Volume of Procedures

A variety of studies have concluded that outcomes for surgical patients are likely to be significantly

better if they undergo surgery in a hospital that performs

a “greater than average” number of those procedures

(Flood, Scott & Ewy, 1984a, 1984b; Luft, 1980; Luft,

Bunker & Enthoven, 1979; Sloan, Perrin & Valvona,

1986).

In an early study, Shortell and LoGerfo (1981)

examined the relationship of hospital structural characteristics including volume, medical staff characteristics

and outcomes for patients with acute myocardial infarc-
tion (AMI) and appendicitis. Data on 50,000 AMI patients and 8200 appendectomy patients were included

in the Commission on Professional Hospital Activities

(CPHA) data base with the American Hospital Association Annual Survey being used for hospital and physician data. For AMI, the authors developed a standardized mortality ratio, and found that physician participation in decision-making, volume of AMI patients per

physician and the presence of a coronary care unit were

all significantly associated with lower mortality. For

appendicitis, the outcome was the percent of normal

appendices removed. Frequency of medical staff committee meetings was the most important predictor of

better outcomes for appendicitis patients. Volume made

no significant impact on outcomes.

In a landmark study, Flood, Scott and Ewy

(1984a, 1984b), using 1972 CHPA and Professional

Activities Survey (PAS) data files, investigated in-hospital mortality for 15 surgical and two medical conditions for 550,000 patients in 1200 U.S. acute care hospitals. Hospitals were considered high volume if they

treated more than the average number of patients in the

same diagnostic category. A standardized mortality ratio (SMR) was developed for each hospital, based on

the ratio of actual deaths to deaths expected on the basis

of differences in both individual patient characteristics

and hospital patient mix.

The findings are complicated, but, in general,

there was strong evidence across the aggregate (i.e. combined) data for six surgical categories exhibiting more

than 1000 deaths per category (surgery for abdominal

aortic aneurysm, gallbladder disease, ulcer disease, colon cancer, hip fracture and amputation of lower limb)

that patients in high volume hospitals had significantly

lower mortality rates (SMRs) than those in low volume

hospitals. For medical categories, gallbladder patients

did significantly better in low volume hospitals, while

for ulcer patients, there were no differences depending

on volume. When probability of dying, or risk level

(low, medium, high) was taken into account, in general,

in high volume hospitals, outcomes did not change substantially depending on patient risk level, while in low

volume hospitals, there appeared to be interactions between volume and risk. In low volume hospitals, low

risk surgical patients had poor outcomes which were significantly worse than low risk patients in high volume

hospitals, while medium risk patients had better outcomes (but still poorer than medium risk patients in high

volume hospitals). In comparison to low or medium

risk surgical patients in low volume hospitals, high risk

patients had the best outcomes, and these outcomes were

not significantly different than for those high risk patients treated in high volume hospitals.

For medical patients, greater experience did not

make a significant difference in explaining outcomes for

ulcer patients, but was weakly related increased mortality for gallbladder patients. For gallbladder patients in

high volume hospitals, there was no relationship between

risk and outcome; for low volume hospitals, high risk

patients did better than either low or medium risk patients. For ulcer patients there was no interaction between risk and volume.

The effects of hospital size, teaching status and

expenditures were then introduced into the analysis. For

surgical patients, high volume continued to reduce mortality even after size was considered, while size, after

controlling for the effects of volume, increased the likelihood of death. When teaching status and expenditures

were entered into regression equations, the results did

not change: larger hospitals were associated with higher

mortality rates, while high volume hospitals were associated with lower mortality rates.

For medical patients, it was only after controlling for the effects of size, teaching status, and expenditures that a highly significant relationship was revealed
between volume and outcome for both gallbladder and

ulcer disease. Again, high volume was associated with

better outcomes.

Understanding the volume-outcome relationship, however, is complicated by different interpretations. One, the “practice-makes-perfect” explanation,

hypothesizes that because physicians and hospital personnel develop greater skills, better outcomes will result. The other, the “selective-referral pattern”, suggests

that physicians and hospitals with better outcomes attract more patients (Luft, Hunt & Maerki, 1987).

Kelly and Hellinger, in their 1986 study investigating ownership and teaching status, also examined

volume of surgical procedures, with the purpose of investigating whether the inverse relationship between

volume and outcome is due to the volume of services

provided by individual physicians or to particular characteristics of high-volume hospitals. They found that

across all diagnoses examined, in-hospital mortality was

lower in high volume hospitals, and for patients undergoing surgery for peptic ulcer and abdominal aneurysm,

the difference was significant. In no case, however, was

the volume of procedures by an individual physician

related to outcomes. These results did not change, even

after re-specification of the regression equations to take

into account potential collinearity between patient specific variables and volume variables. The authors concluded, therefore, that the volume-outcome relationship

was explained by hospital characteristics rather than

physician characteristics.

From the studies just reviewed, it is clear that

for most surgical conditions, in-hospital mortality rates

are lower in high volume hospitals. The results for medical conditions, however, are mixed.

Internal Environmental Effects on Patient Outcomes

While there has been a great deal written on

internal environmental influences on outcomes, there are

two limitations to this body of literature. First, research

is seldom replicated and, second, the outcomes studied

are usually related to the organization rather than to the

patient. For the purpose of this paper, four contextual

variables related to the internal environment have been

selected for review for differing reasons. The first two

variables to be addressed refer to characteristics of the

work pattern in which nurses function. These variables

involve the effect of hospital to home nursing management (Nursing Case Management, Nurse Specialist Care)

and the effect of multidisciplinary collaboration/coordination of the patient’s care. Both of these variables have

received considerable recent attention in the literature.

The second set of two variables were selected due to the

fact that they are often cited either as ways to improve

care or as desireable organizational outcomes. These

variables are staff work satisfaction and education of

staff. Research related to the four variables is summarized in Tables 4, 5, 6 and 7.

Hospital-Home Nursing Management

In 1986, Brooten and colleagues (Brooten, et

al., 1986) published a landmark study on the effect of

nurse specialist care for discharge and at home for the

families of low birthweight infants. The experimental

intervention included early discharge of low birthweight

infants meeting specific criteria, to be followed by

master’s prepared nurse specialists for 18 months after

hospitalization. Infants were randomly assigned to a

control or experimental group resulting in 39 infants in

the experimental group (36 mothers) and 40 infants in

the control group (36 mothers). Groups were found to

be equivalent on a number of demographic family variables and infant treatment variables. Findings indicated

that the experimental group was discharged a mean of

11.2 days earlier than the controls. There were no dif-
ferences in rehospitalizations, acute care visits, failure

to thrive, child abuse, foster placement or developmental quotient of infants. However, the mean hospital

charges were $17,420 less for the experimental group

and physician charges were a mean of $1,716 less. The

nurse specialist care cost an average of $576.00 for patients receiving the intervention. Thus, the hospital-home

nurse specialist care was credited with resulting in health

outcomes equal to traditional care but with cost outcomes

of approximately $18,560 less per family.3

A series of research projects at Carondolet St.

Mary’s hospital in Tucson is currently underway, with

some data published, to evaluate the impact of the nursing case management system centered at this facility.

This nursing delivery pattern involves a network of nursing care delivery including home care, hospice, community wellness centers and in-hospital nursing with the

nurse case manager, prepared at least at the Bachelor’s

level, at the hub of these services. Ethridge and Lamb

(1989) report on the effects of the nursing case management intervention with two groups of patients: those

who received total hip replacements and who represent

the effect on patients with acute illness and those with

respiratory disease who represent the effect on patients

with a chronic illness. The results of the analysis are

limited in their generalizability due to a lack of random

assignment to the intervention, however, the authors report that for patients with total hip replacement, length

of stay, the outcome measure for this investigation, was

reduced by 2.1 days due to case management. There

was a 3.5 day reduction in length of stay for the case

managed chronically ill patients. It is hypothesized that

the reduction for the acute illness occurs at the end of

hospitalization. In other words, case management allowed earlier discharge for these patients. For the chronically ill, a different mechanism is in operation. Length

of stay appeared to be reduced at the beginning of the

hospitalization. Patients who were case managed prior

to hospitalization entered the hospital at lower acuity

levels and shortened their length of stay by seeking care

before illness severity reached a level than would require longer hospitalization.

An additional report by Ethridge (1991) provides data on more than 700 case managed patients enrolled in a Health Maintenance Organization Senior Plan.

Outcomes examined include annualized hospital admissions and bed days per 1000 enrollees as well as average length of hospital stay. The data for the case managed patients is descriptively compared to national and

state statistics for Medicare patients and health maintenance organization service use statistics. The annualized admissions for the case managed patients (after

eleven months of operation) numbered 242 as compared

to a range of 239 to 318 admissions as cited in comparison data bases. Annualized bed days were 1,311 as compared with a range of 1,677 to 2,798. Average length of

hospital stay was 5.77 days compared with a low of 5.85

days and a high of 9.50 days from published data. A

more specific comparison indicated that the case managed patients had 53 less annualized hospital admissions,

895 less bed days and an average length of stay 1.73

days lower than other Medicare patients in the State of

Arizona. Again, these results are limited in

generalizability due to methodological difficulties in

applying the treatment and due to the retrospective nature of data analysis.

A recent study by Naylor (1990) reports on the

effects of gerontological nurse specialist care primarily

in planning discharge for hospitalized elders. While this

intervention concentrates on the discharge component

of the Brooten et al. (1988) model of nurse specialist

care, it also includes some home care elements such as

telephone follow-up at specified times. This pilot study

included 40 hospitalized patients, age 70 and older, who

were randomly assigned to the discharge planning or

control group. Each group had twenty subjects who were
evaluated for average length of initial hospitalization,

post-discharge morbidity (infections and

rehospitalizations) and cost of initial hospitalization.

Groups were found to be equivalent on age, sex, race,

marital status, education, financial status, admission

mental and functional status. No statistical differences

were found in initial hospital length of stay, or costs for

the hospitalization. There was also no difference in the

post-hospital infection rate. However, there were significant differences in the number of rehospitalizations

during the twelve weeks after discharge. For the control group, 64.7% of the subjects were rehospitalized

while only 16.7% of the experimental group required

additional hospital stays. Since data on costs was unavailable for a number of the rehospitalizations, health

care cost information post discharge was not compared.

The results of these investigations indicate that

specialized nursing care that bridges the hospital and

home environment has a significant impact on patient

cost outcomes. In addition it appears that there is some

indication that this health care delivery method may have

a positive effect on morbidity as indexed by rehospitalization.

Multidisciplinary Coordination/Collaboration

Koerner, Cohen & Armstrong (1985) designed

a study to evaluate the effects of organizational implementation of a system of professional nursing practice

through collaboration with physicians. The collaborative practice system included the five interrelated parts

as specified by the National Joint Practice Commission

in 1977.4

 In their study, Koerner et al. (1985) compared

outcomes between adult patients discharged from a nursing unit utilizing team nursing (control) and one in which

collaborative practice had been established. Patients

were selected for survey during a six week period at

four, eight and twelve months after the start of the project.

Sample size was 280 patients which included 100 from

the team nursing unit and 180 from the collaborative

practice unit. Data on the outcome of patient satisfaction was analyzed at the individual level. Patient satisfaction and perception of quality of care was indexed

by an instrument designed by the researchers to measure patient-provider interaction, quality of care, health

education, knowledge of practitioners and environment

of the unit. Findings indicated that there was no difference between units on patient age, gender, ethnicity, illness severity and hospital admissions. Patients who were

hospitalized on the collaborative practice unit reported

significantly greater patient-provider interaction, provider knowledge, health teaching and respectful treatment. There was no difference in patient satisfaction

with the physical environment or in expectations of care.

The authors indicate that the satisfaction questionnaire

was designed with the emphasis on items thought to be

pertinent to an evaluation of collaborative practice, thus

the results may be biased towards the positive evaluation of the experimental treatment. In addition there

appears to be some confusion as to exactly what is being measured as an outcome: patient satisfaction or patient perception of care.

As a further test of the delivery method, the investigators performed a retrospective record audit on a

random selection of 234 patient records (116 from the

team unit and 118 from collaborative practice unit) to

investigate the outcomes of length of stay, number of

laboratory days, IV therapy days, cardiac arrests, deaths,

and transfers to ICU. In addition, the care process activities of referrals to nurse specialists, referrals to allied health workers, teaching plans and discharge plans

were also examined. There were no differences in any

of these measures except for the process variable of

teaching plans which was higher on the team unit. The

authors conclude that it is possible that several intervening variables influenced the outcomes so that no differences in the units were found. These variables include the system of medical education at the study hos-
pital which would influence the number of laboratory

tests ordered; the availability of nursing home beds,

which would influence the length of hospital stay, and

inservice education on charting which would influence

the number of teaching plans recorded.

The study discussed above examined the effect

of collaborative practice on selected outcomes for patients hospitalized on intermediate care units. Other research has investigated outcomes for patients admitted

to intensive care units in which there was a high degree

of collaboration among disciplines.

Knaus, Draper, Wagner and Zimmerman (1986)

conducted an extensive study with adult patients who

had been hospitalized in intensive care units at 13 hospitals. Patients who had burns or coronary artery bypass grafts were eliminated from the study. The total

individual patient sample was 5,030 patients with a range

of 159 to 1,657 patients per hospital. The goal of the

investigators was to determine if the differences in organization, staffing, commitment to teaching, research

and education across hospitals influenced the outcomes

of care as measured by the ratio in actual to expected

mortality rates as determined by the APACHE 2 system

of classifying severity of illness. Findings indicate that

there were substantial differences in predicted and observed mortality rates across the hospitals and that “these

differences appeared to relate to the interaction and communication between physicians and nurses” (pg. 416).

The hospital with the lowest ratio of actual to expected

deaths was organized with clinical protocols implemented by in-unit physicians, a comprehensive nursing

educational support system, clinical specialists with

Masters degrees and extensive experience in intensive

care units, independent nursing responsibilities as designated within clinical protocols, and excellent communication between physicians and nursing staff. Use of

advanced technology in care was important but was not

a sufficient factor to differentiate hospitals with lower

mortality. Reduced mortality was not limited to specific diagnostic categories or severity levels.

The American Association of Critical-Care

Nurses (AACN) developed a Demonstration Project to

further examine patient outcomes in a unit that has valued organizational attributes some of which were delineated in the Knaus et al. (1986) research just described.

Mitchell, Armstrong, Simpson and Lentz (1989) provide a report of the AACN demonstration. Since the

sample for the demonstration was one intensive care unit,

the authors examined their data in comparison to data of

previously published research and health care statistics.

Specific clinical outcomes examined were in-hospital

mortality ratio of observed to expected deaths; complications related to infections, immobility, and fluid balance; patient satisfaction with nursing care, length of

stay; and, hospital accounting costs. Patients (N=192)

included in the analysis represented 42% of the admissions to the unit during the data collection period. Findings indicated that the standardized mortality ratio of

51.2% was comparable to the findings of the Knaus et

al. (1986) study for a hospital with low mortality rates;

complications represented non-resolution of problems

on admission rather than new problems; patient satisfaction ratings were higher that those reflected in two

previously published sets of data; patient charges and

length of stay were within the range of data selected for

comparison. The authors conclude that the desirable

clinical outcomes of low mortality, no new complications and high patient satisfaction existed in the ICU

with valued organizational attributes. A strong dimension of this project is the validation of the existence of

the organizational attributes of high perceived level of

nurse-physician collaboration, highly rated objective

nursing performance and significantly more positive

organizational climate and indices of job satisfaction and

morale than found in historical samples. While the pa-
tient subjects in this research were not selected randomly,

they do reflect the same characteristics of other ICU

patients at the same hospital and the specific unit is further representative of other units in the United States.

Therefore, a statement could be made that the sample

appears to be representative of ICU patients on those

comparison variables that were examined.

The results of these studies indicate that, at least

in settings with acutely ill patients, a high degree of

nurse-physician collaboration and positive interaction

is associated with lower mortality rates, high patient satisfaction with care and low nosocomial complications.

In intermediate care units, findings are less clear. Patient seem to perceive better quality of care which may

be reflective of increased satisfaction, but other positive

outcomes were not supported in the one study examined.

Job Satisfaction

Job satisfaction is a variable frequently cited as

an important organizational outcome related to a number of contextual factors such as degree of control over

nursing practice, autonomy in practice, group cohesion,

and commitment to the organization (Verran, Murdaugh,

Gerber, and Milton, 1988). It is often theorized that

increased job satisfaction will result in positive patient

outcomes, however, this link has been seldom researched

and supported with empirical data. Three studies are

described that have examined the relationship of staff

job satisfaction to patient outcomes.

Holland, et al. (1981) studied resident mental

health patients and staff on 22 wards from three psychiatric institutions. They examined aggregated data for

98% of the eligible staff (N=297) and 68% (N=249) of

the total potential patients who were selected with stratified random sampling. Staff subjects included all staff

on each treatment unit although exact preparation and

titles were not specified in the published report. The

unit of analysis for this research was the unit which resulted in a sample of 22. The outcome examined in this

study was potential posthospital adjustment of patients

as measured at discharge by a standardized scale. Results indicated that improvement in resident functioning was moderately associated with staff satisfaction,

that greater staff participation in resident treatment only

affected the outcome through staff satisfaction and not

directly. The total effects of job satisfaction on resident

functioning as analyzed through path modeling were

higher than any other variable at .55 which includes .38

direct effect and .17 indirect effect.

Linn, Brook, Clark, Davies, Fink and Kosecoff

(1985) examined the relationship of patient satisfaction

and physician satisfaction in 16 group practice sites.

Although it is unclear which variable is meant to be the

outcome in this research since it appears that temporally, physician satisfaction was measured after patient

satisfaction, the findings were that there were statistically significant correlations among aggregated satisfactions scores for faculty, housestaff and patients. The

samples for this research represented 94% of the physician faculty, 88% of the housestaff and 77% of the randomly selected patients from the 16 practice sites.

A study more directly related to nursing staff

was conducted by Weissman and Nathanson (1985).

These researchers examined a causal model to explain

two client outcomes for teenage clients who attended

one of 77 family planning clinics. The sample of 77

represented data from 344 nurses or 86% of the total

possible and 2,900 (80%) clients. Outcomes examined

were client satisfaction and rate of client compliance with

contraceptive prescriptions. Results of causal modeling

using path analysis were the existence of significant direct effects (.32) of job satisfaction on client satisfaction, but no direct effect of job satisfaction on compliance rates. However, there was a significant indirect

effect (.08) of job satisfaction on compliance through

client satisfaction.
Hays and White (1987) reanalyzed the

Weissman and Nathanson (1985) data using the LISREL

program for structural equation modeling. They supported the model proposed in the original study and also

proposed an alternative model that also supported the

hypothesis that job satisfaction of staff has a direct and

indirect effect on selected patient outcomes.

The research studies cited indicate that, with a

variety of work groups, increased job satisfaction will

improve patient outcomes in terms of patient satisfaction and functional abilities. At least two of these studies provide some evidence of the simultaneous effect

and interactions of many variables on outcome measures.

This supports the need for multivariate models in describing patient outcomes and the need for the appropriate analysis of these models.

Education

Education of care providers has often been cited

as a workgroup variable that will improve patient outcomes. In fields such as rehabilitation the link between

level of education and outcome has been investigated

(Szymanski & Parker, 1989). However, most research

in the topic that relates to nursing, examines primarily

the effect of education on the process of care rather than

on patient outcomes5

. A few studies have examined the

effects of special educational programs on patient outcomes.

Alexander (1990) investigated the effects of

providing a staff educational program on caring for patients with breast cancer on patient outcomes of satisfaction with care, patient knowledge and affective responses of anxiety, depression and hostility. The patient sample for the research included 18 patients. Nine

patients were hospitalized prior to the educational intervention while 9 were hospitalized after staff received

the continuing education offering. Findings were that

the experimental group had significantly higher mean

satisfaction and knowledge scores. There were no differences in depression or hostility, however the experimental patients evidenced significantly lower anxiety

than did controls. As with previous research cited, the

satisfaction instrument used in this research was designed

specifically by the investigator for this project. Other

measures however, were well developed and tested instruments. Although the sample size for this project is

small and was not selected randomly, the research does

provide an excellent example of how patient outcomes

can be incorporated in evaluation studies of educational

programs.

A second publication which examines the effect of education on outcomes reports on the impact of a

diabetes educational and organizational development

program on health centers in Sweden (Carlson &

Rosenqvist, 1991). Thirty-four health centers were included in the study with 17 having received the treatment. A sample of a total of 566 patients (317 from

intervention sites) were randomly selected for measurement of the outcomes of dietary knowledge, self-care

practices, and metabolic control. The results indicated

no significant differences in dietary knowledge or metabolic control. The only self-care practice that was affected by the educational program was self-testing for

glucose levels.

Results of only two studies provide limited evidence for the effect of educational programs on patient

outcomes. In addition, the results are inconclusive due

to differing findings across the studies. However, this

is an area of needed nursing research to support the impact of education on patient outcomes. Tangentially,

the studies on delivery patterns tend to support the need

for higher educational levels for practitioners. However, this relationship is not directly supported in the

studies cited earlier.
Measurement and Methodological Issues

In examining the impact of contextual variables,

either at the external or internal environmental level, on

patient outcomes, several measurement and methodological issues are of concern. A few of these will be

summarized in this section.

Mortality as an Outcome Measure

There are obvious limitations to the use of mortality data as an outcome measure. Kelly (1990) suggests three reasons why mortality rates are inadequate

and perhaps inaccurate measures of hospital or

workgroup performance. First, because the vast majority of patients, some 95-98% do not die in hospitals,

mortality rates furnish no information on outcomes for

patients who do NOT die in hospitals. Second, patients

die in hospitals because they are severely ill and/or aged,

perhaps unrelated to hospital performance. And third,

patients die in hospitals because they may not have other

places to die. In addition to the reasons provided by

Kelly, in-hospital mortality rates ignore the fact that for

some patients, complications that occur in hospitals (preventable or not) result in death after discharge. In addition, mortality rates provide no knowledge about other

important outcomes, for example, morbidity, quality of

life or other health status indicators of interest. There is

perhaps no other outcome indicator that so clearly illustrates the dilemma of research in Quadrant 4 of the taxonomy shown in Figure 1. One is forced to accept use

of an outcome that becomes, in essence, the “lowest

common denominator” because of the heterogeneity of

patient aggregates with which one is dealing.

Patient Satisfaction as an Outcome Measure

Satisfaction of patients with their care is another

outcome frequently examined in the research related to

Quadrant 4. The popularity of this measure is reflected

by the number of patient satisfaction instruments that

have been developed for evaluation and research purposes (McDaniel & Nash, 1990). There are a number

of ways to measure patient satisfaction. Not all of those

ways are accurate or reliable. In addition, the construct

validity of many instruments designed for specific studies is questionable. Often it appears that patients are

being asked to evaluate quality of care rather than their

satisfaction with that care. A further limitation of patient satisfaction with nursing care as an outcome measure is that patients traditionally report high levels of

satisfaction with the care nurses provide, thus decreasing the variability of responses that are needed for unbiased analysis (LaMonica, Oberst, Madea & Wolf, 1986).

Measures of satisfaction, that are clinically feasible for

use because of their parsimony, seem to lack the sensitivity required to tap fine differences in patient perceptions.

Adequacy of Data Sources

For every study reported in the section on external environmental contextual factors, and, for some

of those reported in the internal environmental section,

analysis was based on large data sets, gathered for different purposes than for the particular study. Frequent

data sources are the CHPA, PAS, AHA, NCHST and

HCFA data files (Fink, Yano & Brook, 1989). Yet,

Demlo (1990) cites studies in which coding of diagnosis and even mortality was incorrect a substantial proportion of the time. For example, of 1003 cases reviewed

for correctness of coding for acute myocardial infarction (AMI), 25.9% failed to meet clinical criteria

(Iezzoni, Burnside & Sickles, 1988); while of 387 patients discharged with the diagnosis of AMI, 57%, in

fact did not have the diagnosis (Schiff & Yaacoub, 1989).

One would think that coding for in-hospital mortality

would be less ambiguous. However, a study of Medicare discharges in California found a large percentage

of patients reported as discharged alive when they had

in fact died in the hospital (Blumberg, 1987; California

Medical Review, Inc., 1986). Clearly, when policy de-
cisions are made based on the types of studies reported,

it is incumbent on researchers to ensure the quality of

their data, or at the very least, to attempt to ascertain

(and report on) potential sources of error.

Group Level Analysis

Research utilizing contextual factors almost

demands statistical analysis at the group level. However, appropriate use of the techniques for group analysis are limited. None of the studies cited that utilized

aggregated data for the analysis examined this data for

its reliability, validity and adequacy at the aggregated

level (Mark, Lamb & Verran, 1991; Verran, Lamb &

Mark, 1991). There also appears to be limited use of

appropriate statistical techniques with contextual variables (Firebaugh, G., 1979; Holzemer, et al., 1989;

Rousseau, 1985). Inappropriate use of analytic techniques, may result in fallacies of interpretation and generalization of results.

Conclusion

This paper has reviewed research on selected

contextual variables from the external and internal environment of the nursing unit. Conclusions regarding

the effect of context on patient outcomes are limited in a

number of ways. First, the variables reviewed in this

paper represent only a small number of those that may

relate to patient outcomes. Unfortunately, research has

not consistently addressed the same variables or has

examined their relationship to organizational outcomes

rather than patient responses. Second, the interrelation

of contextual variables supports the need for multivariate procedures to examine their impact, and yet, few studies have used multivariate techniques to investigate these

interrelationships. Finally, nurse researchers have not

traditionally valued the examination of the effect of context on anything, much less patient outcomes. However, in the current world of health care, with the need

to support the validity of new delivery patterns, treatment programs and environmental changes, the investigation of how and why context effects outcomes of practice is becoming vitally important. Perhaps it is time

that nurse researchers consistently examine research for

the need to include contextual variables. Perhaps it is

also time that other health services researchers consistently consider the characteristics of nursing services as

part of the hospital context and its subsequent effect on

outcomes.

References

Alexander, M.A. (1990). Evaluation of a training program in breast cancer nursing. Journal of Continuing

Education in Nursing, 21(6), 260-266.

Blumberg, M. (1987). Comments on HCFA hospital

death rate statistical outliers. Health Services Research, 21, 715-739.

Brooten, D., Kuman, S., Brown, L.P., Butts, P., Finkler,

S.A., Bakewell-Sachs, S., Gibbons, A. & DelivoriaPapadopoulos, M. (1986). A randomized clinical trial

of early hospital discharge and home follow-up of verylow-birth-weight infants. New England Journal of Medicine, 315, 934-939.

Brooten, D., Brown, L., Hazard-Munro, B., York, R.,

Cohen, S., Roncoli, M. & Hollingsworth, A.

(1988). Early discharge and specialist transitional care.

Image, Journal of Nursing Scholarship, 20(2), 64-68.

California Medical Review, Inc., (1986). Final report:

Premature discharge study. December 10.

Chassin, M., Park, R., Logr, K., Kersey, J. & Brook, R.

(1989). Differences among hospitals in Medicare p a -

tient mortality. Health Services Research, 24(1), 1-31.
Carlson, A. & Rosenqvist, U. (1991). Diabetes care organization, process, and patient outcomes: Effects of a

diabetes control program. The Diabetes

Educator, 17(1), 42-48.

Demlo, L. (1990). Measuring health care effectiveness:

Research and policy implications. International

Journal of Technology Assessment in Health Care, 6,

288-294.

Duncan, R. (1972). Characteristics of organizational

environments and perceived environmental uncertainty. Administrative Science Quarterly, 17, 313-

327.

Ethridge, P. (1991). A nursing HMO: Carondelet St.

Mary’s experience. Nursing Management, 22(7), 22-

27.

Ethridge, P. & Lamb, G.S. (1989). Professional nursing

case management improves quality, access and

costs. Nursing Management, 20(3), 30-35.

Fink, A., Yano, E. & Brook, R. (1989). The condition

of the literature on differences in hospital mortality.

Medical Care, 27(4), 315-336.

Firebaugh, G. (1979). Assessing group effects: A comparison of two methods. Sociological Methods andResearch, 7, 384-395.

Flood, A., Scott, W.R., & Ewy, W. (1984a). Does practice make perfect? Part I: The relation between

hospital volume and outcomes for selected diagnostic

categories. Medical Care, 22(2), 98-114.

Flood, A., Scott, W.R., & Ewy, W. (1984b). Does practice make perfect: Part II:

The relation between hospital volume and outcomes and other hospital characteristics. Medical Care,

22(2), 115-124.

Gaumer, G. (1986). Medicare patient outcomes and hospital organizational mission. In Gray, B. (Ed.)

The For-Profit Enterprise in Health Care (pp. 354-374).

Washington, D.C.: National Academy Press.

Hartz, A.J., Drakauer, H., Kuhn, E.M., Young, M.,

Jacobsen, S.J., Gay, G., Muenz, L., Katzoff, M.,

Bailey, R.C., Rimm, A.A. (1989). Hospital characteristics and mortality rates, New England Journal of Medicine, 321,(25), 1720-1725.

Hays, R.D. & White, K. (1987). Professional satisfaction and client outcomes. Medical Care, 25(3), 259-

262.

Holland, T.P., Konick, A., Buffum, W., Smith, M.K.,

Petchers, M. (1981). Institutional structure and

resident outcomes. Journal of Health and Social Behavior, 22, 433-444.

Holzemer, W.L., Jennings, B.M., Chambers, D.B., &

Paul, S.M. (1989). Contextual regression analysis.

Nursing Research, 38(2), 124-125.

Iezzoni, L., Burnside, S., Sickles, et al. (1988). Coding

of acute myocardial infarction: Clinical and policy implications. Annals of Internal Medicine, 109, 745-751.

Kelly, J. (1990). What do mortality studies reveal about

hospital volume, teaching status and ownership? International Journal of Technology Assessment in Health

Care, 6, 239-252.
Kelly, J. & Hellingwer, F. (1986). Physician and hospital factors associated with mortality of surgical p a -

tients. Medical Care, 24(9), 785-800.

Knaus, W.A., Draper, E.A., Wagner, D.P., &

Zimmerman, J.E. (1986). An evaluation of outcome from

intensive care in major medical centers. Annuals of Internal Medicine, 104, 410-418.

Koerner, B.L, Cohen, J.R. & Armstrong, D.M. (1985).

Collaborative practice and patient satisfaction.

Evaluation & the Health Professions, 8(3), 299-321.

LaMonica, E.L, Oberst, M.T., Madea, A.R. & Wolf,

R.M. (1986). Development of a patient satisfaction

scale, Research in Nursing & Health, 9, 43-50.

Linn, L.S., Brook, R.H., Clard, V.A., Davies, A.R., Fink,

A., Dosecoff, J. (1985). Physician and patient satisfaction as factors related to the organization of internal medicine group practices. Medical Care, 23(10),

1171-1178.

Luft, H. (1980). The relation between surgical volume

and mortality: Exploration of causal factors and a l -

ternative models. Medical Care, 18, 940-959.

Luft, H., Bunker, J. & Enthoveen, A. (1979). Should

operations be regionalized? The empirical relation b e -

tween surgical volume and mortality. New England Journal of Medicine, 301, 1364-1369.

Luft, H.S., Hunt, S.S., & Maerki, S.C. (1987). The volume-outcome relationship: Practice-makes-perfect o r

selective-referral patterns? Health Services Research,

22(2), 157-182.

Mark, B., Lamb, G. & Verran, J.A. (1991). Conceptual

issues in multi-level organizational research in

nursing, Unpublished manuscript.

McDaniel, C. & Nash, J.G. (May, 1990). Compendium

of instruments measuring patient satisfaction with

nursing care. Quality Review Bulletin, 182-188.

Mitchell, P.H., Armstrong, S., Simpson, T.F., Lentz, M.

(1989). American association of critical-care

nurses demonstration project: Profile of excellence in

critical care nursing. Heart & Lung, 18(3), 219-237.

Naylor, M.D. (1990). Comprehensive discharge planning for hospitalized elderly: A pilot study. Nursing

Research, 39(3), 156-161.

Rousseau, D.M. (1985). Issues of level in organizational

research: Multi-level and cross-level perspectives. Research in Organizational Behavior, 7, 1-37.

Schiff, G. & Yaacoub, A. (1989). The diagnostic coding of myocardial infarction. Annuals of Internal

Medicine, 110, 243.

Shortell, S. & Hughes, E. (1988). The effects of regulation, competition and ownership on mortality

rates among hospital inpatients. New England Journal

of Medicine, 318(17), 1100-1107.

Shortell, S., & LoGerfo, J. (1981). Hospital medical

staff organization and quality of care: Results for

myocardial infarction and appendectomy. Medical Care,

19,(10), 1041-1053.

Sloan, F., Perrin, J. & Valvona, J. (1986). Is there an

empiric basis for standard setting? Surgery, 99,

446-453.
Szymanski, E.M. & Parker, R.M. (1989). Relationship

of rehabilitation client outcome to level of rehabilitation counselor education. Journal of Rehabilitation,

55(4), 32-36.

Verran, J.A., Lamb, G., & Mark, B. (1991). Methodological issues in multi-level organizational research

in nursing. Unpublished manuscript.

Verran, J.A., Murdaugh, C.L., Gerber, R.M., & Milton,

D.A. (1988). Differentiated Group Professional

Practice in Nursing, Grant Number 1 U01 NR02153,

Funded by the National Center for Nursing Research

and the Division of Nursing.

Weiss, C.S. & Nathanson, C.A. (1983). Professional

satisfaction and client outcomes. A comparative o r -

ganizational analysis. Medical Care, 23(10), 1179-1192.