[Congressional Record Volume 140, Number 30 (Thursday, March 17, 1994)]
[Senate]
[Page S]
From the Congressional Record Online through the Government Printing Office [www.gpo.gov]
[Congressional Record: March 17, 1994]
From the Congressional Record Online via GPO Access [wais.access.gpo.gov]
MOVING TO THE ACCOUNTABLE HEALTH PLAN
Mr. DURENBERGER. Mr. President, I rise today to commend and bring to
your attention a study done by the University of Minnesota and Hennepin
County Medical Center. The report indicates that the elderly poor in
Twin Cities Medicaid-HMO plans are as happy with their care and as
healthy as those who are in fee-for-service plans. Yet the cost of
their care is considerably less than that of fee-for-service plans.
It is critical for us to heed the implications of this study as we
consider how to move forward with health care reform. It points us
toward answers to two important questions: How do we contain costs and
how do we expand access to the poor and uninsured?
how do we contain costs?
Much of the health reform debate has focused on the buyer side of the
market. It is equally important to focus on the sellers or providers of
care. Cost containment will only occur if there are changes in the way
medicine is practiced and care is delivered. The key to making this
change is the accountable health plan [AHP].
HMO's, like the ones in this study, are an integrated delivery system
that bring efficiencies, economies of scale, managed utilization and
capitated prepayment. The prepaid, capitated premium shifts the risk
from a third party payer to the provider of care, who must manage the
risk. HMO's have moved from the traditional indemnity insurance bill-
paying model to a true merger of risk management and provision of care.
What, then, is an AHP? The AHP adds a public accountability feature
to the integrated system and is oriented to health outcomes.
Information on the impact of health care on patient health, functioning
and well-being, and patient satisfaction are available for comparative
purposes.
The HMO's in the Twin Cities are beginning the evolutionary process
of becoming an AHP. The study in Minnesota found that the average per-
person cost for Medicaid for those in HMO's was 27 percent less than
those in the fee-for-service plans. There was no significant difference
in health outcomes in spite of the fact that those in HMO's had fewer
doctor visits, fewer visits to emergency rooms, and shorter hospital
stays.
Furthermore, patients in the HMO's were as satisfied with their care
as fee-for-service patients, with 92 percent of HMO patients self-
reporting as very satisfied or satisfied, compared with a 94 percent
rate for fee-for-service patients. By adding data on patient
satisfaction, an accountability measure, HMO's will begin the process
of changing to an outcome orientation, or an AHP.
how do we expand access to the poor and uninsured?
I have been grappling with questions of how to expand access to care
for the poor and uninsured, how to structure their integration into the
health care system without creating a two-tiered system, and how to
finance it. This study points us in a definite direction and the
organizations like those in the study are the way we will get there.
The Hennepin County Medicaid experiment, which began in 1985,
mainstreamed Medicaid individuals into HMO's whose doctors were
expected to use the same standards in caring for the poor as they did
for others. Including the elderly poor in HMO's with the non-poor and
providing adequate reimbursement for the plan insured that this group
of elderly poor patients received the same quality of care that the
nonpoor received.
By adding an emphasis on quality of care and outcomes, these HMO's
are continuing the process of becoming an AHP. Because of its public
accountability and orientation toward outcomes, the AHP is the best
advocate for the poor and low income.
Our objective in health care reform is to get the system to change so
that people buy health services based on value. The AHP is what will
make the difference, not only for the poor, but for everyone. What is
happening in the Twin Cities for the elderly poor is an exciting
example of how our system is beginning the process of moving toward
AHP's and how it can work to benefit the poor.
We will not have either cost containment or universal access unless
we have accountable health plans that compete and are accountable to
the public on the basis of cost and quality. I would like to request
that the report and the newspaper article about the report accompany
this statement in the Record.
There being no objection, the material was ordered to be printed in
the Record, as follows:
[From the Annals of Internal Medicine, Mar. 15, 1994]
Moving to the Accountable Health Plan
(From the University of Minnesota Schools of Medicine and
Public Health and the Hennepin County Medical Center,
Minneapolis, Minnesota. For current author addresses, see end
of text)
(By Nicole Lurie, MD, MSPH; Jon Christianson, PhD; Michael Finch, PhD;
and Ira Moscovice, PhD)
Purpose: To determine the effect on health and functional
status outcomes of enrollment of noninstitutionalized elderly
Medicaid recipients in prepaid plans compared with
traditional fee-for-service Medicaid.
Design: A randomized controlled trial. Beneficiaries were
randomly assigned to prepaid care in one of seven capitated
health plans compared with fee-for-service care. Only the
Medicaid portion of their care was capitated. Patients were
followed for 1 year.
Setting: The Medicaid Demonstration Project in Hennepin
County, Minnesota, which includes Minneapolis.
Patients: 800 Medicaid beneficiaries who were 65 years or
older at the beginning of the evaluation. Beneficiaries were
interviewed at baseline (time 1) and 1 year later (time 2).
Ninety-six percent of beneficiaries were available for
follow-up interviews at time 2.
Main Outcome Measures: General health status, physical
functioning, mental health status, activities of daily
living, instrumental activities of daily living, corrected
visual acuity, and blood pressure and glycosylated hemoglobin
measurements for hypertensive and diabetic persons,
respectively.
Results: There were no differences between prepaid and fee-
for-service groups in the number of deaths (20 compared with
24, P>0.2), the proportion in fair or poor health (56.5%
compared with 59.7%, P>0.2), physical functioning, activities
of daily living, visual acuity, or blood pressure or diabetic
control. Patients in the prepaid group reported a trend
toward better general health rating scores (10.2 compared
with 9.8, P=0.06) and well-being scores (10.0 compared with
9.7, P=0.07) than patients in the fee-for-service group. The
difference in the likelihood of a patient in the prepaid
group having a physician visit relative to the fee-for-
service group was -16.5% (adjusted odds ratio, 0.46; 95% Cl,
0.29 to 0.74) and for an inpatient visit was -11.2% (adjusted
odds ratio, 0.55; Cl, 0.32 to 0.94).
Conclusions: There was no evidence of harmful effects of
enrolling elderly Medicaid patients in prepaid plans, at
least in the short run. Whether these findings also apply to
settings in which health maintenance organizations are formed
exclusively for Medicaid patients should be studied further.
The desirability of capitated health care has been
intensely debated by purchasers of health care and
policymakers alike, especially with respect to its
suitability for public sector programs. Currently, 36 states
offer capitated health plans to the poor, and enrolling
Medicaid beneficiaries in capitated plans is gaining in
popularity as a way to reduce state Medicaid expenditures
(1). Quality of care and health outcomes under capitation in
public programs have been little studied, but because early
attempts to enroll Medicaid beneficiaries in prepaid care
were plagued by inadequate access to care and fraud, critics
have focused debate on these aspects of capitation (2).
Enrolling the elderly in prepaid plans raises a number of
additional issues. In theory, health maintenance
organizations may provide better continuity and coordination
for care of chronic disease than the fee-for-service system
(3). Yet, some authors have expressed concern that health
maintenance organizations may be insensitive to special needs
of the elderly because their highly structured care systems
may be difficult for elderly patients to use, creating
nonfinancial barriers to care (4). Under prepayment,
physicians may respond to economic incentives to restrict
services by seeing chronically ill patients less often (5).
Incentives to limit treatment may be particularly powerful
among high-cost enrollees such as the elderly.
Previous studies of the effects of capitation have focused
on either nonelderly poor or elderly nonpoor persons. None
has studied populations that are both elderly and poor, which
may be at particular risk for underservice in prepaid plans.
Further, they suffer either from incomplete follow-up of
study patients or from the fact that patients were not
randomly assigned to prepaid and fee-for-service groups,
introducing the substantial threat of selection bias. We
describe the experience of noninstitutionalized elderly
Medicaid beneficiaries who were randomly assigned to prepaid
compared with fee-for-service Medicaid care.
methods
The study was conducted as part of the Hennepin County
Medicaid Demonstration Project, one of the Health Care
Financing Administration-sponsored Medicaid Competition
Demonstration sites. This site enrolled a broad range of
Medicaid beneficiaries, including the elderly, and randomly
assigned 35% of them to prepaid care. The remaining 65%
continued to use fee-for-service providers participating in
Medicaid. Once randomly assigned to the capitation group,
beneficiaries were given an opportunity to choose among seven
health plans. These included a closed-panel health
maintenance organization, a county-sponsored network health
maintenance organization that formed in response to the
demonstration, and five independent practice association
plans. The 8% of persons who did not voluntarily choose a
plan were randomly assigned to one. Beneficiaries were
required to remain in the plan for at least a year, unless
they successfully appealed.
Because over 40% of the Twin Cities' population is enrolled
in health maintenance organizations, it is likely that nearly
all physicians caring for study patients had some patients in
their practices for whom they were reimbursed on a capitation
or reduced-fee basis, with risk-sharing through ``withhold''
arrangements in which part of their compensation was
determined by their success in containing costs.
Almost the entire study sample was enrolled in both
Medicare and Medicaid, and the Medicaid portion of care for
the prepaid group was capitated as part of the demonstration.
Under this capitation payment, Medicaid paid for the
copayment and deductible portion of the Medicare, such as
drugs, dental care, and physical, speech, and occupational
therapy. These Medicaid costs were fixed at 95% of estimated
fee-for-service costs, which constituted about half of total
health care expenditures for this population. Plan
participation was voluntary, but all plans participating in
the demonstration chose to enroll elderly patients.
We identified from Medicaid tapes all 1496
noninstitutionalized, aged (65 years) Medicaid
beneficiaries in Hennepin County, Minnesota, and randomly
selected 400 beneficiaries for an experimental (prepaid)
group and 400 beneficiaries for comparison group for
evaluation. Sample members who identified themselves as
hypertensive or diabetic at baseline were included in a
predesigned substudy to assess physiologic outcomes. Sample
sizes were chosen on an alpha of 0.05, a beta of 0.8, and
estimates of the prevalence of hypertensive and diabetic
persons in the population. The sample was designed to include
enough hypertensive persons to detect a 10 mm Hg change in
systolic and a 5 mm Hg change in diastolic blood pressure,
enough diabetic persons to detect a 15% change in
glycosylated hemoglobin, and a 4 percentage point
difference for dichotomous outcome variables for the entire
study sample.
Overall, health status was assessed along the dimensions
specified by the World Health Organization (6). Patients
rated their health as excellent, good, fair, or poor.
Physical functioning was assessed with the nine-item battery
used in the RAND Health Insurance Experiment (7). Social
functioning was measured using a modified five-item scale
developed by Kane and colleagues (8). Role function was
measured with a two-item scale, and general health
perceptions were measured with a four-item general health
scale, both from the RAND Health Insurance Experiment (7);
Activities of Daily Living and Instrumental Activities of
Daily Living were assessed with standard measures (9, 10).
Other than the physical functioning, Activities of Daily
Living and Instrumental Activities of Daily Living measures,
which are scored in terms of numbers of limitations, measures
were scored such that a high score indicated better health.
Three domains of mental health status were measured: well-
being, anxiety, and depression. Well-being was measured using
items from the RAND Health Insurance Experiment (7). Anxiety
was measured with items from the Hopkins Symptom Checklist
(11), and depression was measured with items from the Zung
Depression Scale (12). In all cases, a higher score indicated
better health. Because pilot testing indicated that
beneficiaries found the long mental health scales to be too
intrusive, we used the three items from each scale with the
highest published factor loadings.
We selected three physiologic indicators of health status:
blood pressure control for hypertensive persons, glycosylated
hemoglobin in diabetic persons, and visual acuity for the
entire elderly population. These were chosen because they
have been shown to be sensitive to changes in access to care
(13, 14). In the RAND Health Insurance Experiment, far visual
acuity was better among low-income enrollees receiving free
care (15), and we hypothesized that access to eye glasses or
cataract surgery might differ among the fee-for-service and
prepaid enrollees. Finally, we collected information
regarding
sociodemographic characteristics,
access to care (usual source of care, delay and refusals
of care, travel and waiting time), satisfaction with care
(global satisfaction and satisfaction with provider and
staff), and use of health services. Utilization data were
available from client self-report at baseline and 1 year
later and from the state Medicaid program and Part A
Medicare claims for the demonstration year.
We used Medicare and Medicaid claims to measure inpatient
use during the demonstration year. However, when we conducted
an audit of medical records to validate a sample of the
outpatient claims submitted to the state by the health plans,
we found that they were incomplete, that there was
substantial under- and over-reporting, and that he degree of
accuracy varied by plan. Thus, in our analyses we use only
self-reported outpatient use.
We interviewed sample members at baseline, which was the
period between assignment to prepaid plans and 2 weeks after
coverage started for experimental group patients. Control
group interviews were conducted during a similar period. All
patients were reinterviewed 1 year later, at which time we
also interviewed proxy respondents when patients had died or
were too ill to be interviewed. Methods for achieving high
response rates are described, in part, by Bindman and
colleagues (16).
Near and far visual acuity were measured for all patients
sing standard Snellen charts. Patients were instructed to use
glasses if they routinely wore them.
After patients were interviewed for the evaluation, those
who reported having hypertension or diabetes or both were
visited by a physician or medical student. Standardized blood
pressure measurements were obtained for all hypertensive
persons; glycosylated hemoglobin levels were measured for all
diabetic persons. These were repeated at the 1-year follow-up
interview.
data analysis
We compared the distributions of variables between
experimental and control populations for the baseline and
follow-up periods using t-tests and chi-square techniques. In
analyzing follow-up data, ordinary least-squares techniques
were used to analyze continuous variables, whereas logistic
regression was used for dicbotomous variables. In all these
analyses, the dependent variable was a health status measure
at the follow-up interview. In addition, for health status
measures that were continuous variables, we computed the
difference between the value of the variable at baseline and
follow-up and used the difference as the dependent variable.
These results were similar to those in which the dependent
variable was a health status measure at follow-up. For
hospitalization and nursing home utilization data, we used
tobit regression (17), a method for handling censored data
(because of the large number of people with no admissions) as
well as logistic regression. To minimize the loss of data,
mean sample values were substituted for missing values of
independent variables if the number of observations for which
data on a specific variable were missing was less than 10%.
Otherwise, the variable with missing data was not included in
any analyses. In the regression models, we controlled for
baseline values of sociodemographic characteristics,
inpatient and outpatient use, general health status, physical
function, activities of daily living, instrumental activities
of daily living, social function insurance, and length of
time in the plan. For the health status variables, the
regression-adjusted results were similar in magnitude and
direction to the unadjusted findings, and the results of
analyses using the dependent value at follow-up did not
differ from those using change scores as the dependent
variable. Thus, we report only unadjusted data. Regression
adjustment did alter the magnitude of the utilization
differences, however. Thus, unadjusted and regression-
adjusted scores are presented for these data. For the
logistic regression analyses, we report both the odds of
having a visit in the prepaid group compared with fee-for-
service group as well as the difference in the likelihood of
a patient in the prepaid group having a visit compared with a
patient in the fee-for-service group.
Finally, we calculated the average annual expenditures per
person. For the fee-for-service group, this was the total of
actual Medicare and Medicaid payments for the sample divided
by the total number of beneficiaries. For the prepaid group,
this was the total of capitation payments and estimated
reinsurance payments divided by the total number of
beneficiaries plus the Medicare payments.
TABLE 1.--SAMPLE SIZES AT BASELINE AND FOLLOW-UP
------------------------------------------------------------------------
Fee-for-
Sample Size Prepaid Service
------------------------------------------------------------------------
Total sample at baseline, n......................... 400.0 400.0
Completed follow-up,*n.............................. 387.0 384.0
Refused........................................... 10.0 13.0
Moved out of state................................ 3.0 3.0
Response rate at follow-up, %....................... 96.9 96.0
------------------------------------------------------------------------
*For sample members who had died, 24 elderly control and 20 elderly
experimental interviews were completed by proxies. Proxy respondents
also completed interviews for six elderly control group members and
two elderly experimental group members who were too ill to complete
the interview.
results
We obtained second interviews for 387 control and 384
experimental group patients 1 year after the baseline
interview, yielding 96% and 97% completion rates,
respectively. Reasons for loss to follow-up appear in Table
1. Prepaid and fee-for-service groups did not differ
significantly in any sociodemographic characteristics,
baseline utilization (Table 2), or baseline health status
measures (Table 3). Patients were mostly female and white,
and had, on average, three chronic conditions. Consistent
with our expectations, the study sample reported
significantly poorer health than did the overall Medicare
population in the Twin Cities, based on survey data collected
in 1989 (Wisner C. Personal communication). Sixty percent
reported being in fair or poor health, in contrast to only
13% of the general Medicare population.
Use of services was lower in the prepaid group (Table 4).
Based on logistic regression analyses, the difference in the
likelihood of a patient in the prepaid group reporting an
outpatient visit compared with a patient in the fee-for-
service group was -16.6% (adjusted odds ratio, 0.44; CI, 0.29
to 0.74) and -21.2% for an emergency department visit (odds
ratio, 0.40; CI, 0.25 to 0.63). Claims data indicated that,
relative to the fee-for-service group, the difference in
likelihood of hospitalization for the prepaid group was
-11.2% (odds ratio, 0.55; CI, 0.32 to 0.94) and that
considering all patients, length of stay for the prepaid
group was 1.3 days shorter than for the fee-for-service group
(CI, -0.06 to -7.78 days). The likelihood of being admitted
to a nursing home did not change.
TABLE 2.--BASELINE CHARACTERISTICS OF PREPAID AND FEE-FOR-SERVICE
SAMPLES
------------------------------------------------------------------------
Fee-for-
Baseline Characteristics Prepaid Service
(n=384) (n=387)
------------------------------------------------------------------------
Age (mean) y.................................... 76 76
Female, %....................................... 81 78
Married, %...................................... 9.8 11.9
Education (mean), y............................. 9.6 9.7
White, %........................................ 80 81
Monthly income, $............................... 381 400
Chronic health conditions (mean), n............. 2.9 3.2
Any physician visit in the past 3 months, %..... 80.6 78.5
Physician visits in the past 3 months (mean), n. 3.3 3.4
Any hospital admissions in the past 12 months, % 23.6 26.1
Hospital admissions (mean) in the past 12
months, n...................................... 0.4 0.4
Any nursing home admissions in the past 12
months, %...................................... 3.6 6.2
Nursing home admissions in the past 12 months, n 0.04 0.06
------------------------------------------------------------------------
Despite these differences in use, beneficiaries' reports of
access to or satisfaction with care did not differ. For
example, 92% of prepaid and 94% of fee-for-service patients
were ``very satisfied'' or ``satisfied'' with their care
(P>0.2). Eighty-six percent of each group reported having a
usual source of care, and 16.5% of prepaid and 18.6% of fee-
for-service patients reported ``at least some'' difficulty
getting emergency care (P>0.2). The difference in average
annual per-person expenditures made by Medicaid was $715 (CI,
$103 to $1326), which was 27% lower for patients in the
prepaid group. Medicare expenditures did not differ
statistically between the two groups ($462; CI, -$1118 to
$194).
Forty-four patients died during the 1-year follow-up
period; 24 were in the fee-for-service group and 20 received
capitated care (P>0.2). Table 3 compares health outcomes of
the prepaid and fee-for-service groups at baseline and
follow-up. Blood pressure and glycosylated hemoglobin for
hypertensive and diabetic persons, respectively, were similar
in both groups, as were self-rated health, physical
functioning, mental health and Activities of Daily Living and
Instrumental Activities of Daily Living dependencies for the
entire study population. Patients in the fee-for-service
group reported slightly worse general health than patients in
the prepaid group at follow-up, and these differences
remained statistically significant after regression
adjustment (0.4 points; CI, 0.06 to 0.72 points).
discussion
The current health reform debate focuses on expanding
access to care while maintaining quality and controlling
costs. Capitation, managed care, and competition are seen by
some as desired features of health care reform. This study is
the first to report on use of service and quality of care
from a randomized trial of capitated compared with fee-for-
service Medicaid payment for elderly poor, a group at
particular risk for adverse health outcomes as well as
underservice. It reports on beneficiary outcomes aggregated
across seven health plans of different types. States
contemplating the use of capitation for elderly Medicaid
beneficiaries, nearly all of whom are also Medicare
beneficiaries, will only be able to capitate the Medicaid
contribution for eligible patients. Thus, this demonstration
represents a ``real world'' test of capitation for high-risk
elderly Medicaid beneficiaries. Partially on the basis of
this demonstration experience, health care for Medicaid
recipients in Hennepin County is now being delivered via a
capitation arrangement.
TABLE 3.--HEALTH STATUS AT BASELINE AND FOLLOW-UP FOR PREPAID AND FEE-FOR-SERVICE GROUP*
----------------------------------------------------------------------------------------------------------------
Unadjusted values
----------------------------------------------------
Time 1 Time 2 Adjusted prepaid-fee-for-
Variables ---------------------------------------------------- service difference at time
Fee-for- Fee-for- 2 (95% CI)
Prepaid service Prepaid service
----------------------------------------------------------------------------------------------------------------
Physiologic measures (mean
values):
Systolic blood pressure
(hypertensive patients),
mm Hg..................... 147.5 147.9 145.1 145.0 0.1 (-6.03 to 5.12)
Diastolic blood pressure
(hypertensive patients),
mm HG..................... 79.1 76.9 75.5 76.9 -1.4 (-2.37 to 3.63)
Glycosylated hemoglobin
(diabetic patients), %.... 9.2 9.7 9.4 9.5 -0.1 (-6.68 to 10.65)
Visual aculty:
Near vision >20/200, %..... 45.4 41.6 46.2 51.7 -5.5 (-6.4 to 4.6)
Far vision >20/50, %....... 74.4 75.1 87.0 85.6 -1.4 (-1.47 to 1.33)
Perceived general health:
Fair to poor health, %..... 61.6 62.5 56.5 59.7 -3.2 (-3.27 to -3.13)
General health index (mean)
[range = 4 to 12]......... 9.9 9.8 10.2 9.8 0.4 (0.06 to 0.72)
Mental health status (mean)
[range = 3 to 12]:
Well-being................. 10.2 10.3 10.0 9.7 0.3 (-0.62 to 0.03)
Depression................. 8.4 8.5 8.2 8.2 0(-0.38 to 0.35)
Anxiety.................... 9.8 9.8 9.3 9.3 0(-0.34 to 0.31)
Physical functioning index
(mean) [range = 0 to 9]....... 5.7 5.4 5.7 5.7 0(-0.50 to 0.51)
LADL dependencies:
Number of LADL dependencies
(mean) [range = 0 to 8], n 1.8 2.0 2.3 2.6 -0.3(-0.23 to 0.47)
Dependent in, %
Using telephone........ 2.9 2.3 5.4 5.4 ...........................
Taking medications..... 5.0 5.7 8.4 12.2 ...........................
Doing laundry.......... 31.0 33.9 38.3 42.0 ...........................
Doing routine housework 36.8 39.4 41.0 44.8 ...........................
Cooking own meals...... 13.8 14.9 19.8 20.0 ...........................
Managing finances...... 14.4 12.7 17.4 20.5 ...........................
Shopping for groceries. 40.2 46.6 56.0 51.9 ...........................
Traveling in community. 37.2 39.8 44.6 45.8 ...........................
ADL dependencies:
Number of ADL dependencies
(mean) [range = 0 to 8], n 0.6 0.7 0.5 0.6 -0.12(-0.23 to 47)
Dependent in, %
Eating................. 0.8 1.3 1.0 3.1 ...........................
Dressing............... 2.3 4.7 6.0 7.8 ...........................
Grooming............... 4.2 3.4 5.5 8.3 ...........................
Mobility............... 8.6 8.0 11.7 17.1 ...........................
Transferring........... 3.4 5.2 5.7 9.6 ...........................
Bathing................ 9.4 11.6 14.9 18.4 ...........................
Toileting.............. 2.3 2.6 4.7 7.0 ...........................
Bowel and bladder
control............... 25.8 29.2 27.8 30.6 ...........................
----------------------------------------------------------------------------------------------------------------
*All of the measures were for the entire study population, except for blood pressure and glycosylated
hemoglobin. For hypertensive patients, n = 146 prepaid and 145 for fee-for-service patients. For diabetic
patients, 41 were prepaid and 50 were for fee-for-service at baseline, ADL = activities of daily living; LADL
= instrumental activities of daily living.
Although enrollees in the prepaid group used significantly
less care, there was no evidence that they experienced poorer
health during the study period, and beneficiary reports of
access and satisfaction were comparable. Such findings are
consistent with those of the National Medicare Competition
Evaluation, in which Medicare enrollees in health maintenance
organizations received equivalent or better quality care for
selected conditions and had comparable health outcomes (18,
19-21) to those in fee-for-service Medicare. However,
capitated and fee-for-service groups in those evaluations
often differed in their characteristics, and follow-up data
in some cases were incomplete. Studies of private employed
groups that have addressed similar issues have generally not
used a randomized design and therefore may suffer from
selection bias because enrollees in prepaid plans may have
differed in important ways from those who were cared for in
the fee-for-service sector (22). The only randomized trial to
date examined the experience with capitation in the RAND
Health Insurance Experiment (23). This study found that the
rate of hospital admissions for prepaid health plan enrollees
were 40% lower than for fee-for-service patients. Two other
studies from the same experiment (24, 25) reached differing
conclusions regarding health outcomes. However, the health
maintenance organization studied in the RAND Health Insurance
Experiment was a staff model health maintenance organization
with salaried physicians, which is not typical of most
current prepaid plans.
Our results are also consistent with recent studies about
outcomes of capitated care for poor, nonelderly populations.
Carey and colleagues (26, 27) compared Medicaid enrollees
receiving Aid to Families with Dependent Children (AFDC) in
counties with capitated demonstration programs to AFDC
populations in similar counties with traditional Medicaid
fee-for-service care and found no difference in several
aspects of process of care. Finally, Lurie and colleagues
(28) found that health outcomes of chronically mentally ill
Medicaid beneficiaries enrolled in capitated health plans did
not differ statistically from those remaining under fee-for-
service care.
TABLE 4.--USE OF HEALTH SERVICES FOLLOW-UP FOR PREPAID AND FEE-FOR-SERVICE ENROLLEES
----------------------------------------------------------------------------------------------------------------
Time 2 (Unadjusted Means)
---------------------------- Adjusted Prepaid-Fee-
Variable Fee-for- for-Service Difference
Prepaid Service (Odds Ratios) [95% CT]*
(n=335) (n=336)
----------------------------------------------------------------------------------------------------------------
Self-reported:
Any physician visit in the past 3 months, %............ 67.9 72.8 16.5
(0.44) [0.29 to 0.74]
Physician visits in the past 3 months, n............... 2.3 2.3 -0.8
(-1.68 to 0.25)
Any emergency department visit in the past 3 months, %. 14.8 16.3 21.2
(0.40) [0.25 to 0.63]
Emergency room visits in the past 3 months (mean), n... 0.2 0.2 -0.19
(-0.31 to -0.04)
Claims reported:
Any hospital admissions in the past 12 months, %....... 22.8 26.2 -11.2
(0.55) [0.32 to 0.94]
Hospital admissions in the past 12 months (mean), n.... 0.4 0.5 -0.6
(-1.15 to -0.01)
Hospital days in the past 12 months (mean), n.......... 2.0 3.2 -5.5
[-10.32 to -0.19]
Any nursing home admissions in the past 12 months, %... 0.1 0.1 4.03
[-0.09 to 1.86]
Nursing home admissions in the past 12 months, n....... 0.12 0.12 ________
Nursing home days in the past 12 months (mean), n...... 6.6 8.5 ________
----------------------------------------------------------------------------------------------------------------
*For logit analyses, we present both the difference in likelihood elasticity of a visit, calculated at the mean
for a person in the prepaid group relative to fee-for-service and the odds ratio for a probability of a visit
in the prepaid group relative to fee for service and 95% CIs. Tobit adjusted means were used for number of
hospitalizations and nursing home admissions because of the proportion of patients with no visits. Tobit
adjustment was not calculated for nursing home admissions because tobit regression is not robust enough for
the limited number of nursing home admissions that occurred.
< P < 0.01.
< P < 0.05.
Although neither sample sizes nor our previous agreements
with the health plans permit plans-specific analyses, it is
important to consider the reasons that use may have been
lower for the prepaid group. Switching Medicaid beneficiaries
from fee-for-service to capitation Medicaid financing might
reduce their use because of changes in the financial
incentives faced by their physicians, the application of
managed-care techniques to control service use, or disruption
in the continuity of care for beneficiaries that reduced use
until new care patterns were established. Fortunately,
because most patients did not change doctors, we can exclude
disruption as the cause of lower use. Most of the physicians
serving beneficiaries in our sample continued to receive fee-
for-service payments from plans, often with discounts on fees
and risk-sharing through a ``withhold pool.'' Because the
county-sponsored health maintenance organization was formed
in response to the demonstration, this was the first exposure
to capitation for many physicians practicing there. All of
the plans used managed-care techniques such as prior
authorization for surgery or physical therapy, concurrent
review during hospitalization, or restricted formularies.
Thus, it seems most likely that the observed reductions in
services are caused largely by these efforts.
Several study limitations should be noted. First, because
patients were followed for only a year, we do not know if
adverse effects would have become evident over a longer
period. However, the demonstration continued after our
evaluation ended, and 101 prepaid and 111 fee-for-service
group enrollees died in the first 3 years of the
demonstration (P > 0.2). Although this is a crude measure of
outcome, it is consistent with our other findings. Second,
because only the Medicaid portion of expenditures was
capitated, we cannot be certain that the findings would be
similar if Medicare payments had also been capitated. Third,
we made many comparisons between the prepaid and fee-for-
service groups. The relatively few significant differences
observed between the groups may have occurred on the basis of
chance alone. Because of the large numbers of comparisons
made and the consistent findings, it seems unlikely that use
of additional measures would have altered the general
conclusions of the study. Also, blood pressure and
glycosylated hemoglobin levels vary from hour to hour, so
measurements made at baseline and 1 year later are liable to
substantial sampling error. Fourth, our outpatient use
measures are based on client self-report because claims data
proved inaccurate. However, we know of no reason that there
would be differential self-reporting between the two groups
that would influence our comparisons of use. Finally, most
patients were enrolled in plans that also cared for privately
insured populations, and we doubt that they treated study
patients differently than their other capitated enrollees.
Other Medicaid programs may enroll patients in prepaid plans
serving only Medicaid patients. The evidence on whether
others would fare as well in such plans is inconclusive, but
the specter of the California Medicaid scandals in the 1970s
is a reminder that the enrollment of Medicaid beneficiaries
in such settings should be carefully monitored.
________________
Acknowledgments: The authors thank Muhammad R. Akhtar, PhD,
and Charles Ng for help with data analysis; Ellen Bennvides,
MHA, for support from the Hennepin County Office of the
Medicaid Demonstration Project, Steven Foldas, PhD, for help
with the analysis of mortality data, and Willard Manning,
PhD, for review of the manuscript.
Grant Support: By Hennepin County (Minnesota), the Robert
Wood Johnson Foundation, the Bush Foundation, the Center for
Urban and Regional Affairs, University of Minnesota, the
University of Minnesota School of Public Health, and the
Hennepin Faculty Associates Young Investigator Program.
Requests for Reprints: Nicole Lurie, MD, MSPH, Department
of Medicine, Hennepin County Medical Center, 701 Part Avenue
Minneapolis, MN 55415.
Current Author Addresses: Dr. Lurie: Department of
Medicine, Hennepin County Medical Center, 701 Park Avenue,
Minneapolis, MN 55415. Drs. Christianson, Finch, and
Moscovice: Institute for Health Services Research, School of
Public Health, University of Minnesota, 420 Delaware Street
SE, Minneapolis, MN 55455.
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____
Study: Elderly Poor Happy With HMO's--Plans Cost Less Than Fee-for-
Service Doctors
(By Gordon Slovut)
A University of Minnesota study indicates that the elderly
in Twin Cities Medicaid-HMO plans are just as happy with
their care as those whose doctors are paid on a fee-for-
service basis.
The study found that the patients are just as healthy, and
that the cost of providing care for them is considerably
less.
The researchers randomly assigned 800 Medicare-covered poor
people over age 65 in Hennepin County to (HMO) or fee-for-
service doctors and followed them for a year.
``We find no significant differences in outcomes or
satisfaction,'' said Dr. Nicole Lurie, a researcher for the
University of Minnesota and Hennepin County Medical Center
who headed the study.
The results are important as national health care reform
appears to be moving the nation toward prepaid health plans
such as HMOs, Lurie said.
She said the results are based on data collected from the
enrollees, not from the HMOs.
She said that HMOs tended to underreport or overreport the
services they provided and that different HMOs don't tabulate
their data in the same ways, making HMO-to-HMO comparisons
virtually impossible.
Lurie said that HMOs weren't even reliable on reporting how
often a patient visited a doctor and that researchers
therefore relied on patients to tell them how often they saw
doctors. She said any recollection problems should have
evened out, as the researchers had to rely on patients'
memories on visits to both HMO and fee-for-service doctors.
The Star Tribune reported on Sunday that the Minnesota
Department of Human Services shelved a study designed to see
if the state saves money by sending Medicaid patients to HMOs
rather than paying episodically for their care. Lurie, who
was not involved in that study, said it will be virtually
impossible to do such research adequately until the HMOs move
into standardized reporting.
She said the elderly in the plan, who were examined for the
study initially in the late 1980s, were covered by Medicare
but also needed Medicaid because they did not have sufficient
income to cover the gap between what Medicare pays and what
doctors and hospitals charge.
Medicaid paid a flat fee (on top of what Medicare paid),
based on the individual's age and physical condition, to
HMOs--equal to about 95 percent of what that person would be
expected to pay.
Fee-for-service doctors are paid on the basis of services
they provide to their patients. So the greater the number of
visits and tests a patient needs, the higher a doctor's
income is.
Researchers also reviewed the patients' general health
status, physical function, mental health status, activities
of daily living, corrected vision, blood pressure if they had
high blood pressure and blood sugar levels if they had
diabetes.
They expected that corrected vision would indicate that
patients received adequate eye testing and had eyeglasses
prescribed for proper correction, and if cataracts, for
example, had developed and been treated if necessary.
Blood pressure levels and whether diabetes was under
control would indicate the relative effectiveness of therapy
for two very common diseases in the elderly.
``The outcomes were comparable at a year, including the
number of deaths [20 among HMO members, 24 among fee-for-
service patients],'' Lurie said. ``We have looked at deaths
three years out, and they are still comparable [101 among HMO
patients, 111 among fee-for-service patients].''
She said that any long-term differences, such as whether
preventive measures are more effective in the HMO or fee-for-
service systems, probably wouldn't show up for 10 years.
Medicaid covers preventive care in fee-for-service programs.
Lurie said it is important to note that in the Hennepin
County Medicaid experiment, which began in 1985, the poor
have been ``mainstreamed'' into HMOs such as Group Health and
Medica, whose doctors would be expected to use the same
standards in caring for the poor as they do for others. She
said the results might be different for people if they were
assigned to HMOs that serve only the poor.
Those assigned to HMOs were given a choice of seven,
including Hennepin County's Metropolitan Health Plan, which
provides prepaid care for county employees as well as poor
people.
The study, in which Lurie collaborated with Jon
Christianson, Michael Finch and Ira Moscovevic of the
university, is the first to compare people who are both
elderly and poor, Lurie said. Other research on prepaid plans
has focused on the nonelderly poor or the elderly nonpoor,
she said.
There were differences, however, in how HMO and fee-for-
service patients were treated.
Those in HMOs had fewer doctor visits and fewer visits to
hospital emergency rooms. They had shorter hospital stays--
1.3 fewer days, on average. Nursing home use was the same.
In their report, which appears in today's issue of Annals
of Internal Medicine, the journal of the American College of
Physicians, the Minnesotans wrote that ``92 percent of
prepaid [HMO] and 94 percent of fee-for-service patients were
`very satisfied'' or `satisfied' with their care.''
The average annual per-person cost for Medicaid for those
in HMOs was 27 percent less than for those in the fee-for-
service plan under which Medicaid paid doctors and others on
the basis of visits, tests and treatment. That figure does
not mean the total cost was 27 percent less; Medicare covered
roughly the first 50 percent of the cost for all of the 800
in the trial.
The researchers' conclusion:
``Although enrollees in the prepaid group used
significantly less care, there was no evidence that they
experienced poorer health during the study period, and
beneficiary reports of access and satisfaction were
comparable.''
They stopped short of saying that HMOs provided better
care. The HMOs often promote themselves as providing superior
care because they place more emphasis on prevention. Lurie
said it might take years for such a difference to show up.
____________________