Douglas A. Conrad, Charles Maynard, Allen Cheadle, Scott Ramsey, Miriam Marcus-Smith, Howard Kirz, Carolyn A. Madden, Diane Martin, Edward B. Perrin, Thomas Wickizer, Brenda Zierler, Austin Ross, Jay Noren, Su-Ying Liang. Primary Care Physician Compensation Method in Medical GroupsDoes It Influence the Use and Cost of Health Services for Enrollees in Managed Care Organizations?. JAMA. 1998;279(11):853–858. doi:10.1001/jama.279.11.853
From the Department of Health Services, University of Washington, Seattle.
Context.— Growth of at-risk managed care contracts between health plans and medical
groups has been well documented, but less is known about the nature of financial
incentives within those medical groups or their effects on health care utilization.
Objective.— To test whether utilization and cost of health services per enrollee
were influenced independently by the compensation method of the enrollee's
primary care physician.
Design.— Survey of medical groups contracting with selected managed care health
plans, linked to 1994 plan enrollment and utilization data for adult enrollees.
Setting.— Medical groups, major managed care health plans, and their patients/enrollees
in the state of Washington.
Study Participants.— Sixty medical groups in Washington, 865 primary care physicians (internal
medicine, pediatrics, family practice, or general practice) from those groups
and affiliated with 1 or more of 4 managed care health plans, and 200931 adult
Intervention.— The effect of method of primary care physician's compensation on the
utilization and cost of health services was analyzed by weighted least squares
and random effects regression.
Main Outcome Measures.— Total visits, hospital days, and per member per year estimated costs.
Results.— Compensation method was not significantly (P>.30)
related to utilization and cost in any multivariate analyses. Patient age
(P<.001), female gender (P<.001),
and plan benefit level (P<.001) were significantly
positively related to visits, hospital days, and per member per year costs.
The primary care physician's age was significantly negatively related (P<.001) to all 3 dependent measures.
Conclusions.— Compensation method was not significantly related to use and cost of
health services per person. Enrollee, physician, and health plan benefit factors
were the prime determinants of utilization and cost of health services.
IN TODAY'S health care environment, physicians, their patients, health
care leaders, and public policymakers are confronting the challenges of managed
care. Financial incentives and externally imposed utilization management constraints
are being applied to medical practice with unprecedented intensity in a climate
of increased competition and cost consciousness. Despite professional and
public concern regarding the impact of these economic pressures on the quality
and efficiency of health care, there have been few quantitative studies of
the impact of managed care on the cost and utilization of health services.1- 3 There have been only
2 prior studies2,3 on the impact
of financial incentives for physicians on the general utilization and cost
of health services, and both of those focused on plan payment method rather
than compensation by the medical group to the individual physician. Moreover,
a recent descriptive study of large medical groups in California4
suggested that placing medical groups at risk through health plan capitation
might result in reduced utilization, but did not address individual physician
compensation methods within those groups.
The latter mechanism, the method of physician compensation within medical
groups, is arguably the most important financial incentive influencing the
individual physician's behavior. In this article, we estimate a model that
examines the relationship between the method of primary care physician (PCP)
compensation and the utilization and estimated cost of health services for
adult enrollees of managed care organizations (MCOs).
The study hypothesis posited that utilization and cost of health services
per capita (per enrollee) would be greater, other things equal, among enrollees
in the panel of PCPs who are compensated predominantly on the basis of their
individual production, generally measured as fee-for-service equivalent services
provided to patients (production based), as compared with those cared for
by PCPs predominantly compensated by salary (salary based). In our study sample,
no medical groups compensated PCPs on a capitation basis.
This study focused on PCPs in medical groups, which were defined as
3 or more physicians practicing in a common setting and sharing revenues and
expenses. A survey of clinic practices with respect to physician compensation,
health plan payment, as well as patient care management and information dissemination
was mailed to 76 medical groups and completed by 62, for a final response
rate of 82%. Two single-specialty pediatric groups were excluded from the
analysis of adult enrollees reported in this article. This resulted in a study
sample of 200931 adult enrollees in the panels of 865 PCPs within 60 medical
groups. Individuals covered by public programs (eg, Medicare, Medicaid, Civilian
Health and Medical Program of the Uniformed Services, and Veterans Affairs)
were not included in the study. The medical groups were identified by the
4 participating MCOs. These MCOs included a large staff model-health maintenance
organization (HMO); a major network-model HMO; a preferred provider organization,
which selected PCPs based on their estimated efficiency in caring for a broad
range of clinical conditions; and a group-model HMO. In all but the group-model
HMO, each individual enrollee was assigned a PCP. The individual-level analysis
included 200931 privately insured members 18 years of age or older, continuously
enrolled for the calendar year 1994, and who were in 1 of the 3 MCOs that
assigned individual enrollees to PCPs.
Measures of cost and utilization included per member per year (PMPY)
estimated costs of health services, total physician and outpatient visits
PMPY, and total hospital days per enrollee per year. The PMPY measure was
constructed by assigning resource-based relative value scale weights to each
ambulatory service or procedure and then multiplying the resource-based relative
value scale units by $46.23 (the average dollar conversion factor for commercial
health insurance plans in the state of Washington in 1994). Total ambulatory
care visits included primary care and specialty referral visits to hospital
outpatient clinics, physicians, and other health care providers. Hospital
days were converted to dollar equivalents by first applying all-payer diagnosis
related group weights to each hospital discharge, second dividing by the average
length of stay for the particular discharge, and third multiplying by the
dollar payment per hospital day among private, commercially insured patients
in Washington in 1994. Dental and pharmacy claims were not included in the
measures of cost and utilization.
The independent variables used in evaluating the study hypothesis are
listed in Table 1. Individual
enrollee data were obtained from the MCO enrollment files. The benefit level
measure was constructed by scoring each of 3 types of covered services, inpatient
hospitalization, physician office or hospital outpatient care, and emergency
department visits, as 0 (low), 1 (medium), or 2 (high), depending on whether
the level of patient cost sharing was above average, average, or below average,
respectively. Adding the 3 subscales produced a score ranging from 0 to 6,
in order of increasing overall health plan share of payment. An ambulatory
care group (ACG) relative resource consumption measure, which was based in
1994 on age, gender, and International Classification of
Diseases, Ninth Revision (ICD-9)5
diagnosis codes, was assigned to each enrollee.6
The algorithm proceeds by first assigning groups according to diagnoses (ambulatory
diagnostic groups) and then hierarchically subclassifying those groups into
ACGs (aggregations of diagnostic groups with common levels of annual resource
consumption). Earlier validation work by Weiner et al6
has established that ACGs are a powerful predictor of annual health care expenditures.
The 1994 PCP characteristics were obtained from the 4 health plans,
the Washington State Medical Association, the American Medical Association's
Physician Masterfile, and the AMA Directory of Medical Specialists. Age and
gender were obtained, and self-reported specialty was defined as family practice,
internal medicine, pediatrics, or general practice. Medical group characteristic
variables were derived from the medical group practice survey that was sent
to medical group administrators. The survey requested 1994 information about
compensation method for the typical PCP, the number of all physicians by specialty,
utilization management protocols, and the distribution of revenues from all
health plans, not just the 4 MCOs.
For each group, a utilization management score was calculated for fee-for-service
contracts, as well as for at-risk managed care contracts. The score ranged
from 0 to 9 with 1 point assigned for doing the following: (1) preauthorization
for referrals to specialists, (2) preauthorization for hospital admissions,
(3) preauthorization for outpatient procedures, (4) preauthorization for hospital
admissions, (5) concurrent review of hospital stays, (6) information feedback
to PCPs, (7) clinical guidelines, (8) case management for high-cost, catastrophic
episodes of care, and (9) internal utilization review by physician peers.
Group revenues from health plans were distributed among the different
payment methods described in Table 1.
An alternative definition of plan payment was implemented, and each of the
MCOs provided 1994 information concerning how they paid the medical groups
with which they contracted. Other variables of interest were characteristics
of the geographic areas where medical groups were located. Since groups were
concentrated in 2 large metropolitan areas with a smaller number located in
6 other counties throughout the state, market area characteristics were defined
by a series of 8 dichotomous geographic variables.
The key variable of interest, PCP compensation method, was determined
by the medical group survey that contained several questions adapted from
the Medical Group Management Association. We asked what percentage of the
typical PCP's compensation was derived from the following: (1) straight salary
with no incentives, (2) individual capitation, (3) group capitation based
on average per member per month "at risk" within the group, (4) individual
production, (5) equal share of net income, (6) structured bonus or incentive,
and (7) other. These responses were used to derive the 5 mutually exclusive
categories of compensation (Table 1).
To assess the effect of PCP compensation method on the cost and utilization
of health services, several different strategies were used. First, at the
group level, measures of cost and utilization were examined by the 5 different
compensation methods. Second, using ordinary least squares regression with
the group as the unit of observation (N=60), the association between the 3
dependent variables and compensation method was examined, while controlling
for average enrollee and medical group characteristics. Given the relatively
small number of observations, it was possible to control for only a limited
number of independent variables.
A third approach used a mixed-model analysis of variance in which the
medical group and the individual PCP were modeled as random effects.7- 10 In this
model, SEs of the regression coefficients were adjusted to reflect the nesting
of PCPs within medical groups and of individual enrollees within PCPs' panels.
Ordinary least squares and weighted least squares regression were used to
validate the results of the mixed-model analysis of variance.
In these analyses, the dependent variables were transformed to normalize
the distributions of the residuals in the estimated regression equations;
the natural logarithm of PMPY costs, hospital days, and total visits per year
was used as the transformation. Since the 1994 ACG case-mix classification
was derived principally from the diagnoses recorded for utilization in the
same year, there could be a direct correspondence between this variable and
measures of cost and utilization. Accordingly, the mixed-model analysis of
variance was run with and without the ACG weight. All variables were allowed
to enter the model and the resulting regression coefficients and P values were reported.
Measures of cost and utilization, as well as characteristics of enrollees
and physicians, are shown in Table 2.
The average number of total visits was approximately 6.5. The average PMPY
cost was equivalent to a per month cost of $105, a representative level of
cost for that period. The average hospital days per 1000 were 280. The average
probability of hospitalization for the year, 5.2%, was within the range of
averages reported in the Medical Outcomes Study.11
The average age of enrollees was 40 years, 55% were women, and the average
plan benefit level was slightly above 3 (on a 0-6 scale). Most enrollees in
this sample (65%) were panel members of family practice physicians; the average
age of these physicians was 45 years and 30% were women.
The majority of the medical groups included family practice, pediatrics,
and general internal medicine practices; 30% of groups were multispecialty.
Almost half the groups had 3 to 5 physicians (48%), and the remainder was
equally distributed between groups of 6 to 19 (26%) or 20 or more physicians
(26%). Utilization management for both fee-for-service enrollees (5.5 of 9)
and managed care enrollees (6.9 of 9) was extensive.
Compensation methods were as follows: 18.3% of the groups (46% of PCPs,
90% of PCP enrollees) were on salary-only compensation, 16.7% (17% of PCPs,
2% of enrollees) of the groups were compensated on the basis of greater than
50% base salary plus other methods, 16.7% of groups (16% of PCPs, 4% of enrollees)
were on greater than 50% production-based plus other methods, and 45% (20%
of PCPs, 3% of enrollees) were production-based only. The 2 remaining groups
(1% of PCPs, 1% of enrollees) compensated PCPs based on equal shares of net
income and a mixed scheme, respectively. The differing compensation method
percentages (by groups, PCPs, and enrollees) reflect primarily the large size
of 1 of the salary-only groups (in terms of the number of PCPs and enrollees).
For purposes of the analysis, the nature of health plan payments to
the medical group was summarized in the dummy variable, at-risk, which is
coded as 1, if the plan's contract with the specific medical group was based
on any 1 of 4 types of payment (as defined in Table 1): full-risk capitation, professional services capitation,
primary care capitation, or fee-for-service plus withhold. Under these payment
types, the medical group was effectively at risk for unanticipated variation
in utilization. Fee-for-service contracts (whether discounted or not) without
withhold were coded as 0 for the at-risk variable. Ninety-six percent of the
individual enrollees were in health plans whose payment arrangements placed
their PCP's medical group at risk (ie, their at-risk variable equaled 1).
All types of capitation (including full-risk, which accounted for less than
5% of average total revenues; professional services capitation for primary
care and specialty referrals; and capitation for primary care only) comprised
21% of total health plan payments to medical groups in Washington in 1994.
Table 3 displays the unadjusted
level of per enrollee cost and utilization by compensation method. The PMPY
cost was lower for enrollees whose physicians received salary only. However,
there was no apparent trend in the number of visits or hospital days.
Multivariate regression analysis at the level of the medical group revealed
no statistically significant association between measures of compensation
method and cost and utilization. Mixed-model analysis of variance at the level
of the individual enrollee was then used to further test the study hypothesis.
The unit of analysis for all multivariate results presented in this article
was the individual enrollee. For significant variables, and the at-risk health
plan payment and compensation variables, the impact of a 10% increase in continuous
variables or a unit change in categorical variables is displayed in Table 4.
The ACG resource consumption weight was not included in these models
because of its codeterminacy with utilization, but including the ACG weight
did not alter the significance or sign of the estimated effects of compensation
method. The coefficient of determination (R2) for the final model
(without inclusion of ACG weight) is presented for each dependent variable
in Table 4.
The impact of PCP compensation method on use and cost was statistically
insignificant for all 3 dependent measures. Our most conservative estimates
of power (for hospital days per enrollee) revealed β=.90 to detect (with α=.05)
a difference of .018 hospital days per enrollee, which is a relatively small
difference. The measure for health plan payments placing the medical group
at risk was also statistically insignificant in the analyses of visits, hospital
days, and PMPY estimated cost. Tests for interactions between compensation
method and health plan payment and between compensation method and group size
revealed no statistically significant interactions. The identical mixed analysis
of variance model was estimated for 4 specific clinical conditions of relatively
high frequency in our sample (asthma, congestive heart failure, hypertension,
and pneumonia). The results were the same: compensation method was not significantly
related to utilization or PMPY cost.
In contrast, enrollee age, gender, plan benefit level, and physician
age were significantly associated with all 3 dependent variables. For example,
adjusted for all other variables in the model, a 10% increase in enrollee
age was associated with a 7.8% increase in PMPY cost and with smaller increases
in visits and in hospital days per enrollee. Adjusting for other factors,
women enrollees used more services than men; adjusted PMPY cost and visits
per year were 77% and 4.7% greater, respectively, for women. Patient benefit
level and physician age also had statistically significant, though smaller,
impacts on use and cost.
In analysis at both the group and individual enrollee levels for all
adult enrollees and medical groups in the study sample, the effect of PCP
compensation method on the use and cost of services per enrollee was statistically
insignificant. The principal drivers of use and cost were characteristics
of individual enrollees and their PCPs and the level of health plan benefit
Use and cost increased with age, female gender, and richness-of-plan
benefit coverage. These findings are not surprising and are consistent with
earlier studies of health services utilization.12,13
The finding that the enrollees of older PCPs had lower levels of use and cost
might reflect the clinical maturity and efficiency of more experienced practitioners,
a preference for less service-intensive practice styles, or underprovision
of services. The significantly higher number of visits and hospital days per
year of female enrollees is consistent with 1994 National Health Interview
Survey age-adjusted estimates.14 The significant
age and gender effects on utilization and cost highlight the necessity of
age and sex adjustments in health plan payments.
The multivariate results regarding the effect of PCP compensation method
are not consistent with our original hypothesis, but are in accord with the
statements of PCPs and administrators in key informant interviews.15 The PCPs generally reported that their treatment
decisions were based on clinical indications rather than financial incentives.
Physicians do respond to incentives and how they are compensated is perceived
to affect their productivity, but not their treatment decisions for individual
patients. Indeed, previous studies indicate a major effect of individual production-based
compensation on physician productivity.16,17
It is also possible that the statistically insignificant effect of PCP
compensation method observed in this study was the result of offsetting effects.
For example, PCPs compensated on a production basis compared with those on
straight salary might do more primary- and specialty-type care themselves,
but make fewer referrals to specialists. In contrast, our original hypothesis
was that the financial incentive to the PCP to do more under production-based
compensation would override any potential savings from reduced referrals.
Our findings should be viewed as complementary, rather than contradictory,
to the earlier studies.2,3 Those
studies did find significant effects of plan payment incentives on health
services use, whereas we find no significant effects of individual PCP compensation
or health plan payment method (the at-risk variable). The insignificance of
the health plan payment variable might reflect the limited variation in the
at-risk variable in our sample. The fact that 96% of the enrollees were in
panels of PCPs who were at risk implies that our choice of health plans, in
effect, has eliminated the influence of health plan payment in this sample.
This actually increases one's confidence that we have isolated the effect
(or noneffect, in this case) of individual physician compensation, which is
the variable of interest in this study. This is an important consideration
because the incentive effects of health plan payment and physician compensation
are potentially significant independent influences on use and cost, and they
might interact with one another.18
The absence of capitation compensation to individual PCPs within medical
groups is not surprising. Medical groups exist, in part, to spread economic
risk among physicians17; thus groups are unlikely
to adopt compensation arrangements that place substantial risk for unanticipated
variance in utilization on individual physicians. This is consistent with
the physician and administrator responses in our key informant interviews.15 Of course, at the group level, where the risk of
unanticipated variance in volume of services per person is diversified across
physicians, capitation payments by health plans are being accepted in groups
as our data suggest.
It is important to acknowledge the potential limitations of this study.
First, the compensation of PCPs, not specialists, was the focus of this study,
although we recognize the large role of specialists. The PCPs are experiencing
declining choice in the specialists to whom they can refer their enrollees.
Within those constraints, which are imposed at the level of the MCO (benefit
design) or the group (intergroup agreements), the PCP will respond to his
or her own incentives to manage care by purposeful referral to specialists.
On a related point, because the health plan administrative data for
this study did not allow one to distinguish reliably between primary care
and referral care, we were unable directly to test hypotheses regarding the
differential effects of compensation on primary care visits vs specialty referral
care. However, the trade-off between these types of care is ultimately captured
in the PMPY cost measure.
Second, since this study examined Washington groups and 1994 quantitative
data only, our results do not necessarily generalize to other environments
or market conditions. While 1994 was a relatively stable year in terms of
physician compensation arrangements in Washington, the somewhat more turbulent
market conditions of 1996 to 1997 might produce different incentive effects
of compensation on utilization and cost. We find no suggestion of this in
the 1996 interview responses,15 but it is possible.
It is also conceivable that the presence of relatively efficient PCPs in the
preferred provider organization plan reduced the variation in use and cost
within our sample, thus making it somewhat more difficult to detect compensation-related
differences. Moreover, the relatively high penetration of at-risk managed
care in our sample may have affected the behavior of all physicians, thus
narrowing the scope of potential compensation effects.
Third, we view compensation method not as an externally imposed condition,
but as a component of work that is chosen, in part, by the practitioner. This
self-selection was suggested by the findings of the key informant interviews
of physicians and group-practice administrators.15
Self-selection might impart a positive (nonconservative) bias to our estimate
of the effect of production-based compensation on use and cost since physicians
with higher production potential might gravitate to groups compensating on
a production basis. Thus, the finding of negligible effect of compensation
method is reinforced. Reestimating the model with instrumental variables,
taking into account self-selection of compensation method, did not change
the finding of no significant compensation effects.
Finally, this study focused on PCP compensation within medical groups.
It is possible that the nature of interactions among physicians within medical
groups might attenuate the individual physician's response to financial incentives.
In contrast, individual physicians in solo or 2-person practices might react
much more strongly to compensation incentives. Future analyses should examine
the impact of financial incentives on physicians in solo or 2-person practices.
This is especially important in light of the finding in a 1995 national survey
that a large percentage of solo and small practice physicians seemed unfamiliar
with the provisions of their managed care contracts,19
and therefore might be taking on excessive financial risk.
Compensation method is 1 of many factors potentially influencing PCP
behavior. When other factors are controlled for, PCP compensation method does
not appear to have a significant effect on cost and use of health care services
per person for managed care enrollees whose PCP practices within a medical
group. Future research should examine the robustness of this finding in other
settings and as the managed care marketplace evolves over time.