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Hospital Care by Hospital-Based and Clinic-Based Faculty
A Prospective, Controlled Trial
Patrick J. Kearns, MD;
Clifford C. Wang, MD;
William J. Morris, MD;
Dennis G. Low, MD;
Allison S. Deacon, BS;
Stephanie Y. Chan, MD;
William A. Jensen, MD
Arch Intern Med. 2001;161:235-241.
ABSTRACT
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Background The hospital length of stay decreases and clinical outcomes are maintained
when teaching hospitals involve hospital-based attending physicians in comparison
with traditional attending physicians. The attending physician's time commitment,
including the number of hours per day and months per year, required to achieve
this result is unknown. This study compared the clinical outcomes and cost
of care for patients treated by hospital-based and clinic-based attending
physicians devoting dramatically different amounts of time to supervising
residents on the medical wards of a suburban county hospital.
Methods Patients were alternately admitted to 2 groups of ward teams. Faculty
who attended 10 months of the year supervised one group. The comparison group's
attending physicians were on service for 2 months or less and maintained clinic
responsibilities while on service. The cost of patient care was compared by
means of the length of stay, total hospital costs, and costs for ancillary
services. Hospital mortality and readmission rates compared clinical outcomes.
Results There were 4456 patients hospitalized on the medical wards of a teaching
service. No differences were detected in the length of stay (4.37 ±
0.1 days for hospital-based and 4.39 ± 0.1 days for clinic-based attending
physicians). Hospital cost was observed to be similar (average cost, $5989
and $5977 per patient, respectively). The clinical outcomes were equivalent,
with adjusted mortality rates for hospital-based attending physicians of 3.2%
vs 3.9% for clinic-based attending physicians (P
= .28).
Conclusion An increase of faculty time and involvement for supervision of resident-managed
hospital care did not improve clinical outcomes or decrease costs during the
1-year study period.
INTRODUCTION
RECENTLY, considerable national attention has focused on physicians
who devote a substantial amount of their time to the care of hospitalized
patients.1 Given growing pressures to manage
costs and maximize efficiency in all health care sectors, increased emphasis
on cost of inpatient care is essential.2 There
is growing evidence that hospitalists can shorten the length of hospital stay
(LOS) and decrease inpatient costs while maintaining the quality of care.3, 4, 5, 6 Because
the hospitalist model may offer a partial solution to the inflationary rise
in hospital costs, it is being routinely considered as a model for teaching
hospitals.
Many factors may influence the impact of a hospitalist program. An essential
issue in trying to develop the hospitalist's role is defining the optimal
amount of inpatient activity. Academic physicians in municipal hospitals attend
on a ward service from 1 to 6 months per year. Wachter and Goldman1 suggested that a hospitalist
should be defined as a physician occupied in hospital care 25% of his or her
professional time. Although researchers at the University of California at
San Francisco (UCSF) have demonstrated a decrease in costs and LOS with a
reorganization of the attending service, there were "no significant differences
in cost or LOS based directly on the number of months worked as attending
physicians."6 This may have been due to inadequate
power. The intervention increased the annual faculty commitment only from
0.9 month for the traditional attending physicians to 1.7 months for the managed
care service (MCS). Only 3 (21%) of the 14 MCS internists actually attended
for 3 or more months. Seventy-nine percent did not attend for the minimum
of 3 months, and 43% attended for only 1 month.1, 2
The authors commented on the need to clarify whether "the key factor in improving
efficiency is in increased faculty experience (e.g. multiple months of work
as an attending physician per year), earlier and more intensive faculty involvement
and commitment to inpatient care, greater use of guidelines, or the mandate
to improve quality and decrease costs."6
A reorganization of our medical teaching service allowed us to conduct
a prospective controlled trial in which one group of internists provided continuous,
full-time supervision for half the medical ward teams of a county teaching
hospital. The other teams were supervised by internists who maintained an
afternoon ambulatory clinic while attending for 1 to 2 months during the study.
The study evaluated the effect of extended faculty availability during the
day and an increased number of months of attending physician experience on
mortality, readmission rates,7 and resource
utilization for hospital care.
PATIENTS AND METHODS
BACKGROUND
Santa Clara Valley Medical Center is a 390-bed county hospital in San
Jose, Calif, affiliated with Stanford University School of Medicine. The internal
medicine residency program was based at Santa Clara Valley Medical Center
and consists of approximately 60 house staff and 70 faculty. Eight ward teams,
composed of an attending physician, a resident, an intern, and a periodic
medical student, managed medical care. Two ward teams were linked in the call
schedule, sharing admissions on every fourth day. In addition, the linked
teams admitted up to 4 patients each on the midcycle day. All medical ward
admissions were managed by these ward teams. A separate intensive care unit
team treated patients who required intensive care. A patient's primary care
physician relinquished responsibility for treatment of the patient to the
attending physician and residents. On discharge, the patient was sent back
to the primary care physician's clinic for ongoing treatment. There were no
subspecialty wards. All members of the department traditionally shared attending
responsibilities. While attending, the faculty maintained their clinic duties
as well as their administrative responsibilities. During the year before the
study, 38 faculty members attended for an average of 2.5 months (range, 1-4
months). A hospital reorganization plan was implemented to increase resident
supervision and attending physician involvement to optimize care and utilization
of hospital resources. The effect of this reorganization was studied prospectively.
ATTENDING PHYSICIANS
We studied clinical outcomes of patients treated by resident physicians
supervised by a hospital-based attending physician (HBA). These outcomes were
compared with those resulting from supervision by a clinic-based attending
physician (CBA). The HBAs were recruited from the board-certified internists
comprising the salaried faculty in the Department of Medicine. The HBAs were
relieved of most of their outpatient responsibilities to provide full-time
supervision for 4 of the 8 resident ward teams for 10 months during the study
year. The traditional team structure was maintained. No productivity incentives
were offered. A 7% salary supplement was given in anticipation of the increase
in work hours required by the HBA schedule.
The CBAs were selected from the same pool of full-time faculty. The
contrasting expectations of the 2 groups' duties are presented in
Table 1. The essential difference between
the 2 groups was the job expectation and their involvement in ambulatory care
clinics. The HBAs attended for 10 months and were to be in the hospital and
actively involved in the patient's treatment on the day of admission. The
CBAs were to supervise a resident ward team, identical to the HBA teams, for
1 to 2 months of the year. While an inpatient attending physician, the CBAs
made rounds in the morning with their team and then returned to their ambulatory
care clinical duties for the afternoon. The majority of admissions for this
group were presented to the attending physician on the morning after admission.
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Table 1. Expectations Communicated to Attending Physicians in Each
Group*
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Each HBA team was linked to a CBA team and alternated admissions during
call. The teams admitted patients to geographically separate medical wards.
An exception to this separation involved patients admitted to the shared transitional
care unit. Medical ward units were similar in layout, staffing, and organizational
structure. The CBA group did not admit their clinic patients to their teams
unless this assignment was made by the alternating admission scheme. The HBA
staff had minimal interaction with the CBAs. For both groups, outpatient follow-up
was provided by primary care attending physicians assigned by ambulatory care
staff. A discharge clinic was staffed by the HBAs to facilitate the transition
of care of HBA patients to their primary care physician. The HBAs emphasized
the need for a team member to communicate details of the discharge plan to
the outpatient caregiver. No other differences existed between groups in the
transitioning of care from the inpatient to outpatient venue. Only 4 HBAs
were used. During the 2 vacation months taken by each HBA, a CBA substituted
for the HBA. Patients admitted to the linked teams during these 8 vacation
periods were excluded from analysis (Figure
1). This was done to avoid dilution of the HBA effect during their
absence.
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Description of patients hospitalized and cared for by the medical
ward teams throughout the study period. HBA indicates hospital-based attending
physician; CBA, clinic-based attending physician.
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Control for the assignment of residents was not included in the study
design. The chief resident and program director based assignments on the resident's
academic needs, as had been the custom in previous years. The study coordinators
gave explicit instructions to the chief residents not to allow the attending
physician's assignment to influence those of the residents. Resident satisfaction
was measured by an anonymous 15-question survey. The areas evaluated included
the learning experience, emphasis on evidence-based medicine, quality of health
care delivered, the level of autonomy, and availability of attending physicians.
Each area was ranked on a 5-point scale; 5 was excellent and 1, poor. The
instrument was developed internally and validated during the 3-month prestudy
period.
The study's primary intervention was the creation of differing expectations
and time commitments for the attending physicians. An increase in the hospital
presence of the HBAs augmented the attending physician's early involvement
in the assessment and treatment of patients.
PATIENTS
All patients admitted to the hospital on the medical service were eligible
for admission to the study. These included patients admitted from the emergency
department and specialty clinics and those transferred from other specialty
services or community hospitals. Patients excluded from the study were those
admitted to the critical care units. Patients who were admitted to a medicine
team that was not part of a paired HBA-CBA team were also excluded from analysis.
This occurred only during the vacation periods for the HBAs when a CBA substituted
as the attending physician for the month. Data from these periods were compared
separately and did not differ from those generated during the CBA-HBA months.
The first patient enrolled in the study was randomly assigned to the
care of 1 of the 2 groups at the time of admission. Subsequently, patients
were admitted alternately to the CBA and HBA teams admitting on the same day.
Two teams from each group admitted every day. A blinded admitting clerk assigned
patients to alternating teams according to a prescribed protocol. Any attempted
deviation from the assignment scheme was reported. The institutional review
board approved the protocol and determined that the study did not require
informed consent.
DATA COLLECTION
Data collection and data entry were performed daily. Demographic data,
attending physician assignment, LOS, hospital charges, and readmissions were
derived from the Shared Medical Systems (Melvern, Pa) hospital database. The
treating physicians corroborated this information once during every 4-day
call cycle. After they reviewed and corrected their census sheets, the Shared
Medical Systems computer was updated. All mortality data were confirmed by
the treating physician, the hospital morgue, and vital statistics. Thirty-day
mortality was obtained by review of the California Department of Public Health's
list of deaths within the state. The random assignment of patients and the
data collection procedures were implemented and refined for a 3-month period
preceding the initiation of the study.
OUTCOME MEASURES
Clinical Outcomes
The clinical outcome measures prospectively evaluated were the hospital
mortality rates and the readmission rates.7
The readmission rate was determined at 7 and 30 days after discharge.
All deaths occurring in the hospital were reviewed. The review determined
the prognosis of each patient at the time of admission. The assessment included
review of the admission history, physical examination, initial laboratory
studies, nursing notes, and admission orders. Patients were categorized as
having an excellent, good, fair, poor, or grim prognosis. Ten percent of all
charts were reviewed and categorized according to this same scheme. This distribution
by prognostic category was extrapolated to determine the frequency of prognostic
category for the entire study population. This estimation was used to calculate
the mortality rate by prognostic category. Charts of all patients who died
and were in the 3 best prognostic categories were abstracted and summarized.
This summary was reviewed by an independent, blinded clinician (W.A.J.) who
classified the death as preventable, possibly preventable, or unpreventable.8, 9 The numbers of combined preventable
and possibly preventable deaths were compared with the number of unpreventable
deaths for each group.
Resource Utilization
The outcome measures for comparing resource utilization included the
LOS and hospital costs. Costs were determined by multiplying the ancillary
ratio of cost to charges by the charges. The ancillary ratio of cost to charges
was based on the Medicare cost report. Cost-charge ratios were generated for
each specific cost center. A cost ratio analysis compared costs generated
by teams sharing the same call schedule. The overall cost ratio was calculated
by multiplying the cost-charge ratio by the total charges generated for patients
admitted to each group. The individual resource centers analyzed included
diagnostic imaging, the clinical laboratory, and radiology. Physicians' costs
to the institution were included.
A final outcome comparison was the number of patients transferred to
the critical care units after initial admission to a study team. This was
used as a measure not only of quality but also of utilization of the most
costly hospital resource.10, 11, 12
An independent analysis of the LOS was conducted for the year immediately
preceding this study. Data were retrospectively retrieved from Shared Medical
Systems and included all patients admitted to attending physicians in the
Department of Medicine. These data were censored at 100 days of hospitalization
and compared with the data for all patients admitted during the study year.
For purposes of this comparison only, the LOS for the study year was censored
at 100 days as well. Most organizational features of the medical service were
maintained during the study year. The exception to this involved the addition
of 4 HBAs assigned to the medicine service as the study's main intervention.
The four HBAs had been traditional attending physicians during the prestudy
period. During the study, the HBAs met weekly with social service, nursing,
and case managers to discuss care delivery issues and to promote coordination
of the staffs' efforts.
ANALYSIS
Analysis included each patient in the group of initial assignment. If
the patient's condition required a change of attending physician to an intensivist
or surgeon, the entirety of the hospital stay was attributed to the initial
group.
During the study organization, a power analysis predicted that 4000
patients would be required to show a clinically significant difference in
the LOS. The anticipated change was a reduction of 0.5 day over an average
LOS of 5 days. These figures were derived from published studies and the recent
historical LOS at Santa Clara Valley Medical Center.3, 4, 5, 6
This predicted an 80% chance of showing a 10% reduction in the LOS with 2000
patients enrolled in each group (ß = .80,  = .05).13
The admission rate to the medical services was anticipated to be 5000 patients
annually. The study was designed to enroll patients for 1 year.
Statistical analysis performed on StatView (Brain Power, Inc, Calabasas,
Calif) used an analysis of variance for multiple comparisons of hospital costs
and LOS across International Classification of Diseases,
Ninth Revision (ICD-9)14
codes. Comparisons of baseline characteristics, LOS, and factors contributing
to significant differences in the analysis of variance were performed by means
of an unpaired t test for continuous variables or
a  2 test for dichotomous variables. The coefficient of variation
was calculated to evaluate the variability in physician practice within each
group.15 We used multiple stepwise regression
analysis to examine the influence of confounding variables and adjust the
LOS for significant factors.16 The explanatory
variables identified included sex, age, ward or transitional care unit, principal
discharge ICD-9 code, and insurance status. To account
for outliers in the LOS, analysis was completed with the data censored at
a value equal to the 99th percentile (45 days) and at 100 days for comparison
with the baseline year. Further analysis of LOS data transformed values to
log 10 to limit the effect of skew. Death rate was adjusted by means of the
Mantel-Haenszel 2 calculation.16
Values are given as the mean ± SEM or mean with the 95% confidence
interval (CI).
RESULTS
ATTENDING PHYSICIANS
Four HBAs supervised 4 medical teams for 40 months. Twenty-seven internal
medicine faculty attended for an average of 1.5 months (range, 1-2 months)
and comprised the linked CBA group.
Attending physicians in both groups were board certified in internal
medicine. Both HBA and CBA internists had a median of 1.5 additional certifications
or special qualifications. The HBAs had an average of 10 years (range, 2-17
years) and the CBAs had 8.5 years (range, 2-21 years) of experience as ward
attending physicians.
The resident assignments were comparable for the 2 groups. The distribution
of junior and senior residents as well as the primary program affiliation
of residents were not statistically different during the course of the study.
There were 35 and 29 second-year residents and 17 and 23 third-year residents
assigned to the HBA and CBA teams, respectively (P
= .31). On the resident satisfaction questions, the HBAs scored significantly
higher than the CBAs over the entire survey (4.5 ± 0.3 vs 3.7 ±
0.4; P<.05). The differences were greatest in
the categories of attending physician availability and emphasis on evidence-based
medicine.
PATIENTS
Data were collected for all patients admitted to a medical service from
April 1, 1997, through March 31, 1998. A total of 5940 patients were hospitalized
on the medical service during this period. The teams that did not consist
of a linked HBA-CBA group admitted 1415 patients (24%). These patients were
excluded from the primary analysis. The LOS, readmissions, costs, and deaths
for this group did not differ from those of patients in the 2 study groups.
The HBAs discharged 2238 patients and the CBAs discharged 2217 patients during
the same period. The demographic data for patients admitted to the study and
control groups were comparable
(Table 2). There were no differences in the distribution of patients admitted
to the medical wards or transitional care unit (68% ± 2% and 32% ±
2%, respectively, for both groups).
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Table 2. Sex, Age, Financial Class, and Frequency of Most Common Admission ICD-9 Codes Assigned by Emergency Department Physician*
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OUTCOME MEASURES
Clinical Outcomes
The mortality rate during the hospitalization phase was 3.2% ±
0.9% for the HBA and 3.9% ± 0.9% for the CBA group (P = .28).
Table 3 shows
that, during the 30 days after discharge, the additional deaths resulted in
an overall mortality rate of 6.0% ± 0.8% for patients of HBAs compared
with 6.7% ± 0.8% for patients of CBAs (P =
.41). The adjusted odds ratio for deaths in the 2 groups was 1.15 (95% CI,
0.86-1.54). The readmission rate was comparable for the 2 groups at 7 and
30 days. The rates were 4.1% and 12.9% for HBAs vs 4.8% and 13.5% for CBAs
(P = .22 and .64, respectively).
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Table 3. Mortality, Readmission Rates, and Rates of Transfer to Intensive
Care Units*
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A total of 158 patients died during the study. The number of deaths
sorted by ICD-9 category did not differ significantly
(P = .46). These patients' charts were reviewed,
and there was a similar distribution of patients among the 5 prognostic categories
(Table 3). Twenty-two (31% ±
8%) of the patients of HBAs who died had a prognosis of fair or better on
admission. This compares with 36 of the patients of CBAs (42% ± 10%; P = .15). The charts of these 58 patients were abstracted
and reviewed to determine whether the death could have been prevented. No
significant difference was noted between the groups for preventable and unpreventable
deaths (P = .97). The HBAs had 11% of total deaths
characterized as preventable or possibly preventable; CBAs had 8% of the total
deaths in these categories (Table 3).
The estimate of the mortality rate by prognostic category showed no significant
differences between the 2 groups (Table
3).
Resource Outcomes
The overall LOS was comparable for the 2 groups
(Table 4). When the LOS was compared according to the principal discharge
diagnosis, no statistical differences were noted for the 10 most common ICD-9 code groups
(Table
4). Comparisons of the LOS censored at 3 SDs, 100 days, and uncensored
were statistically insignificant. The 2 groups did differ, however in the
variability of several measurements. The coefficient of variation differed
for LOS, average charge per patient, and average charge by each diagnostic
group. The HBAs had less practice variation, with an aggregated coefficient
of variation of 32% (95% CI, 23%-40%) vs 75% (95% CI, 65%-85%) for the CBAs.
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Table 4. Comparative Utilization Outcomes by Leading ICD-9 Diagnostic Categories*
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The total costs generated by the hospital care for the groups were comparable.
The HBAs generated $12 510 357 in overall costs compared with $12 360 837
by CBAs. These costs generated a HBA-CBA cost ratio of 1.00 (95% CI, 0.98-1.03).
The average hospital cost per patient was $5989 (95% CI, $5519-$6460) and
$5977 (95% CI, $5442-$6511), respectively. No differences were seen in the
costs by resource category
(Table 5).
The HBA costs averaged $430 (95% CI, $392-$463), $569 (95% CI, $528-$602),
and $809 (95% CI, $732-$881) for radiology, clinical laboratories, and pharmacy,
respectively. The CBA average patient care costs were $407 (95% CI, $377-$435),
$560 (95% CI, $521-$599), and $813 (95% CI, $734-$892) in the corresponding
categories. All cost ratio comparisons equaled 1.
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Table 5. Cost Ratios (HBA-CBA) for Total Hospital Cost and Costs for
Diagnostic Imaging, Clinical Laboratory, Pharmacy, and All Ancillary Costs*
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During the prestudy year, 38 faculty internists were assigned attending
duties, with an average of 2.5 months of attending each. The average LOS during
this prestudy year, censored at 100 days, was significantly longer than for
all patients admitted during the study period when similarly censored at 100
days for this comparison (5.1 ± 0.1 days vs 4.7 ± 0.1 days; P<.05). Since the prestudy data were available only
censored at 100 days, the LOS for the study year differs from the adjusted
LOS for all study patients censored at 45 days (4.4 ± 0.1 days).
COMMENT
This study demonstrates equivalence in mortality, resource utilization,
and costs for hospital care delivered by residents supervised by an HBA compared
with a CBA. This comparison of outcomes is based on differences in the time
commitment that full-time clinical faculty devoted to supervision of hospital
care. The HBAs did not decrease LOS or costs or improve clinical outcomes
despite the significant increase in the number of hours and months per year
devoted to the inpatient supervision of residents. The power analysis, sample
size, and adjustment for confounding variables lend credibility to the interpretation
that the attending physician time commitment does not have a direct impact
on resource utilization or clinical outcomes.
The UCSF group saw a significant reduction in LOS and costs, but they
too were unable to demonstrate a significant correlation between these differences
and the number of months that faculty were assigned to ward attending.6 Thus, 2 prospective studies, the UCSF and our experience,
failed to demonstrate a relationship between the attending physician time
factor and improved efficiencies. Several studies show a similar temporal
relationship between "hospitalist" programs and a shortened LOS.3, 4, 5, 6
Three of these studies showed a reduction in LOS after the initiation of a
hospitalist program.3, 4, 5
Their methodologic designs did not allow identification of a responsible factor.
One study showed no benefit when initiating a hospitalist program.17 Our study showed a reduction in LOS only with a retrospective
comparison with the prestudy year. In discussing the UCSF failure to demonstrate
a correlation between the number of attending physician months and the decreased
LOS, Wachter et al6, 18 enumerated
several alternate factors that may account for lower LOS and costs. They believed
that a search for the possible key factors should include "increased faculty
experience (e.g., multiple months of work as an attending physician per year)
earlier and more intensive faculty involvement and commitment to inpatient
care, greater use of clinical guidelines, or a mandate for change." We would
add that this mandate occurs in hospitals with and without hospitalist programs
and may be independent of the hospitalist movement. A final addition to this
list is the Hawthorne effect.19, 20
This effect would anticipate improved performance when physician-participants
become aware that LOS and costs are the observed outcomes. Even though there
was no difference between groups, both groups reduced the LOS compared with
the prestudy year. Although our findings do not identify a causative factor,
they do support the conclusion that the attending physician time factor is
not pivotal in determination of LOS or hospital costs.
The differences in design of the 2 prospective studies suggest a causal
factor. Many of the attending physicians involved in the UCSF trial had "spent
the bulk of their time engaged in research activities."6
The volunteer character of the MCS, along with the advertised MCS mandate
to decrease hospital costs while maintaining quality, selected faculty with
a focus on quality, cost-effective care. The traditional-service attending
physicians were likely to be less focused on their ward attending obligations.
With this difference in the comparative groups, the UCSF MCS reduced the LOS
and hospital costs. Our study assigned full-time clinical faculty from the
same pool, equally committed to cost-effective care, to both groups. Given
their similarity, the greater than 5-fold increase (8 months vs 1.5 months
of attending) in faculty time devoted to hospital care failed to improve quality
or efficiency. Both groups achieved a LOS (4.37 ± 0.1 and 4.39 ±
0.1 days for HBAs and CBAs, respectively) similar to that of the UCSF MCS
(4.3 ± 0.1 days; SEM calculated from published data). The difference
in attending physician attitude to ward supervision between groups may be
the critical element distinguishing the design of the UCSF hospitalist system
and accounting for the improved efficiency in hospital care. If this factor
is important, it follows that our study should produce no difference in LOS
or cost.
In our study, a system existed in which case managers and social workers
were unavailable during nights, holidays, and weekends. No attempts were made
to increase the availability of diagnostic or therapeutic procedures performed
by cardiology, gastroenterology, radiology, or surgery during weekends and
holidays. The administration's policy of providing only emergency coverage
in these areas during off hours meant that routine procedures were not available
up to 30% of the time. Since these resources were common to both groups during
the study, the lack of an effect may result from these limitations.21 However, given the adjusted LOS of 4.38 days, comparable
with the UCSF MCS experience, we believe it is unlikely that this effect was
responsible for eliminating an observable effect. An analogous rationale applies
to concern that an overworked hospital staff may have nullified an HBA impact.
If hospital staff are working at peak efficiency, the expedited HBA workups
and order writing would fail to achieve a shortened hospital stay. The physician's
commitment to hospital care may be essential but not sufficient to improve
efficiency. However, as with the previous point, since quality and LOS in
this study are comparable with or superior to those of previous studies, one
cannot attribute the lack of an HBA effect to an overstressed system. In addition,
since both groups improved in comparison with the previous year's LOS, the
hospital culture was responsive to the increased emphasis on cost and resource
utilization.
Although increasing attending ward commitment was not sufficient to
effect a change in LOS or the quality of care, this study design did not allow
comparison of many important factors that may be influenced by the hospitalist
model. This study evaluated the effectiveness of a hospitalist compared with
traditional academic attending physicians. No conclusions can be drawn about
the advantage of hospitalists over private attending physicians caring for
their own patients without house staff. This is a crucial void in the hospitalist
literature, since no prospective study examined this venue. The significantly
lower coefficient of variation for LOS and costs for HBAs suggests a decreased
variability in practice style. This predictability in hospital management
is viewed as valuable to health care planners and third-party payers. This
is a variable that should be an area for future analysis, especially in the
private practice and nonacademic settings. Other factors such as improvement
in resident curriculum and educational programs,22, 23
communication among hospital staff and physicians, an overall decrease in
resource utilization,24, 25 and
increased physician accountability for hospital systems are additional areas
of focus for future studies. It should be stressed that studies must include
the evaluation of the potential negative effects of these programs as well.
Relevant areas that should be included are the impact on malpractice suits,
physician burnout, and the financial consequences of the system on physicians.17, 25, 26 Finally, the groups
who have presented their experience should publish their follow-up data to
provide chairs of medicine with information regarding long-term effects of
these programs.22, 26 For the present,
chairs of medicine should retain maximum flexibility in the design and implementation
of a hospitalist program, realizing that its benefits may be indirect and
subjective.
AUTHOR INFORMATION
Accepted for publication July 20, 2000.
We acknowledge Jen Eng, MD, for his contributions in preparing the manuscript
for submission and Marcia Vierra for her organizational and clerical efforts.
From the Department of Medicine, Santa Clara Valley Medical Center,
San Jose, Calif.
Corresponding author and reprints: P. J. Kearns, MD, 751 Bascom Ave,
SCVMC, San Jose, CA 95128 (e-mail: pj.kearns{at}med.stanford.edu).
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