Original ContributionsDifferences in 4-Year Health Outcomes for Elderly and Poor, Chronically III Patients Treated in HMO and Results From the Medical Outcomes Study John E.. Tarlov, MD
Trang 1Original Contributions
Differences in 4-Year Health Outcomes
for Elderly and Poor, Chronically III
Patients Treated in HMO and
Results From the Medical Outcomes Study
John E Ware, Jr, PhD; Martha S Bayliss, MSc; William H Rogers, PhD; Mark Kosinski, MA; Alvin R Tarlov, MD
Objective.-To compare physical and mental health outcomes of chronically ill
adults, including elderly and poor subgroups, treated in health maintenance
orga-nization (HMO) and fee-for-service (FFS) systems
Study Design.-A 4-year observational study of 2235 patients (18 to 97 years
of age) with hypertension, non-insulin-dependent diabetes mellitus (NIDDM),
re-cent acute myocardial infarction, congestive heart failure, and depressive disorder
sampled from HMO and FFS systems in 1986 and followed up through 1990 Those
aged 65 years and older covered under Medicare and low-income patients (200%
of poverty) were analyzed separately
Setting and Participants.-Offices of physicians practicing family medicine,
in-ternal medicine, endocrinology, cardiology, and psychiatry, in HMO and FFS
sys-tems of care Types of practices included both prepaid group (72% of patients) and
i ndependent practice association (28%) types of HMOs, large multispecialty
groups, and solo or small, single-specialty practices in Boston, Mass, Chicago, III,
and Los Angeles, Calif
Outcome Measures.-Differences between initial and 4-year follow-up scores
of summary physical and mental health scales from the Medical Outcomes Study
36-Item Short-Form Health Survey (SF-36) for all patients and practice settings
Results.-On average, physical health declined and mental health remained
stable during the 4-year follow-up period, with physical declines larger for the elderly
than for the nonelderly (P<.001) In comparisons between HMO and FFS systems,
physical and mental health outcomes did not differ for the average patient; however,
they did differ for subgroups of the population differing in age and poverty status
For elderly patients (those aged 65 years and older) treated under Medicare,
de-clines in physical health were more common in HMOs than in FFS plans (54% vs
28%; P<.001) In 1 site, mental health outcomes were better (P<.05) for elderly
patients in HMOs relative to FFS but not in 2 other sites For patients differing in
poverty status, opposite patterns of physical health (P<.05) and for mental health
( P<.001) outcomes were observed across systems; outcomes favored FFS over
HMOs for the poverty group and favored HMOs over FFS for the nonpoverty group
Conclusions.-During the study period, elderly and poor chronically ill patients
had worse physical health outcomes in HMOs than in FFS systems; mental health
outcomes varied by study site and patient characteristics Current health care plans
should carefully monitor the health outcomes of these vulnerable subgroups
JAMA 1996;276:1039-1047
ENROLLMENTS in health mainte-nance organizations (HMOs) have in-creased nearly 10-fold since 1976, and in some regions of the country, half of pri-vately insured Americans are enrolled
in HMOs! Policies at the state and fed-eral levels seek to affect a similar shift for those who are publicly insured, in-cluding both Medicare and Medicaid Congress has signed legislation that will give Medicare patients strong financial incentives to enroll in managed care plans Yet, as documented in a recent literature analysis,' little is known about health outcomes in HMOs for the
elder-ly and the poor, who have historicalelder-ly tended to favor fee-for-service (FFS) over HMO systems
The Medical Outcomes Study (MOS) was fielded to compare 4-year health outcomes for chronically ill patients treated in well-established HMOs and FFS plans serving the same "medical marketplaces" in 3 cities.' To increase the generalizability of results, adults with 4 physical conditions (hypertension, non-insulin-dependent diabetes mellitus [ NIDDM], recent acute myocardial in-farction, and congestive heart failure) and 1 mental condition (depressive
dis-From The Health Institute, New England Medical Center (Drs Ware, Rogers, and Tarlov, Ms Bayliss, and
Mr Kosinski), Tufts University School of Medicine (Drs Ware and Tarlov), and Harvard School of Public Health ( Drs Ware and Tarlov), Boston, Mass.
Reprints: John E Ware, Jr, PhD, The Health Institute, New England Medical Center, Box 345, 750 Washington
St, Boston, MA 02111 ( e-mail: j ohn.ware@es.nemc.org)
Trang 2order) were followed Sampling patients
with the same diagnoses across systems
of care and measuring them with the
same methods allowed more valid
com-parisons of outcomes across plans To
better address policy issues, the MOS
oversampled the elderly and the poor
Focusing on chronically ill patients and
oversampling of the elderly and poor
increased the likelihood of detecting
dif-ferences in health outcomes because
these subgroups account for a
dispro-portionate share of health care
expen-ditures and are, therefore, prime
tar-gets of cost containment
We report here the results of
com-paring changes in physical and mental
health status between FFS and HMO
systems, measured over a 4-year
pe-riod In contrast to previous MOS
re-ports of outcomes for the average
pa-tient, we focus on outcomes for
policy-relevant subgroups-including patients
aged 65 years and older covered by
Medicare and those near and below the
poverty line Further, results are
re-ported for patients across all of the
conditions sampled in the MOS and not
just for patients with hypertension and
NIDDM 4 and mental disorders s,6
METHODS
The MOS was an observational study
of variations in practice styles and of
outcomes for chronically ill adults treated
in staff-model and independent practice
HMOs vs FFS care in large
multispe-cialty groups, small, single-specialty
groups, and solo practices serving the
same areas Details of the MOS design,
including site selection, sampling,
clini-cian and patient recruitment, and data
collection methods are documented
elsewhere'- " To briefly recap the study
design, MOS sites included Boston,
Mass, Chicago, Ill, and Los Angeles,
Calif, which represent 3 of the 4 US
census regions When sampling began
in 1986 and 1987, these cities included
well-developed HMO and FFS plans,
including 2 of the country's largest
HMOs employing salaried physicians
and 2 of the largest independent
prac-tice association (IPA) networks In each
city, 5 or 6 practice sites were sampled
from each group practice HMO The
physician sample included 206 general
internists, 87 family practitioners, 42
cardiologists, 27 endocrinologists, and
65 psychiatrists In HMOs, patients
treated by 8 nurse practitioners were
also sampled In addition, patients with
a depressive disorder were sampled
from the practices of 59 clinical
psy-chologists and 9 social workers
Clini-cians averaged 39.6 years of age; 22%
were female, and 29% were
interna-tional medical graduates
Patient Sampling and Characteristics
Patients followed up longitudinally were selected from 28 257 adults who visited an MOS site in 1986; 71.6% agreed
to participate In 18 794 (92.9%) of the visits, a standardized screening form was completed both by the MOS clinician and the patient Using criteria docu-mented elsewhere,' clinicians identified patients with hypertension, NIDDM, myocardial infarction within the past 6 months, and congestive heart failure
Patients with depressive disorder were identified independently in a 2-stage screen, which included a patient-com-pleted form and a computer-assisted di-agnostic interview by telephone; 80%
of those contacted completed this screen-ing process
Patients were selected for follow-up
on the basis of diagnosis and participa-tion in baseline data collecparticipa-tion, as docu-mented in detail elsewhere 5,1 Inclusion
of patients with more than 1 of the 5 conditions, with or without other comor-bidities, allowed for a more generaliz-able study Of the 3589 eligible patients,
2708 (75.5%) completed a baseline as-sessment We randomly selected 2235
of these for follow-up, by chronic con-dition and severity of their disease A patient sample of this size was sufficient
to detect clinically and socially relevant differences in health outcomes, defined
as an average difference of 2 points or larger on a scale of 0 to 100,"I in a com-parison between HMO and FFS sys-tems Specifically, the statistical power was greater than 80%, with aat the 05 level for a 2-tailed test
Patients ranged from 18 to 97 years of age, with a mean just under 58 years At baseline, 36.8% were 65 years of age or older; all but 1 reported being covered
by Medicare (An additional 144 patients aged into this group during the 4-year follow-up.) A slight majority (54%) were female About 22% were at or below 200% of the poverty line; 16% of those reported being covered by Medicaid
Three of 10 eligible for Medicare were also in the poverty group Three of 4 had completed at least a 12th grade educa-tion; about 1 in 5 was nonwhite
Patients sampled had the following di-agnoses: hypertension (n=1318), NIDDM (n=441), congestive heart failure (n=215), recent acute myocardial infarction (n=104), and depressive disorder (n=444)
(These numbers add to more than 2235 because some patients had more than one condition.) 1,9 As in previous MOS analyses,' FFS patients followed up in this study were significantly older (41.9
vs 32.9 years on average) than HMO pa-tients, were more likely to be female (62.8% vs 57.8%), and were more likely
to be in the poverty group (25.4% vs 18.1%) The FFS patients followed were also more likely to have congestive heart failure (11.8% vs 7.3%) and to have had
a recent myocardial infarction (8.9% vs 3.4%) As documented in detail else-where (MOS unpublished data; see ac-knowledgment footnote at the end of this article for availability of all MOS un-published data), 99% of patients fol-lowed in both FFS and HMO systems had 1 or more comorbid conditions; the most prevalent conditions were back pain/ sciatica (39% and 37% in FFS and HMO systems, respectively), musculoskel-etal complaints (24% and 22%), derma-titis (17% in each), and varicosities (15% and 14%)
Longitudinal Data Collection
After screening in the physician's of-fice and enrollment by telephone inter-view, each patient was sent a baseline health survey by mail." The baseline survey was completed, on average, 4 months after the patient's screening visit with an MOS clinician Four-year
follow-up data were obtained for 1574 of the
2235 patients (70.4% of the longitudinal cohort) Patients were lost to follow-up for a variety of reasons including refus-als and failure to contact (n=661; 29.6%);
137 (6.1%) who died during follow-up were included in the analysis Analysis
of initial health status for those lost to follow-up for reasons other than death revealed no differences and loss to
follow-up was equally likely in HMO and FFS systems However, younger and pov-erty-stricken patients were more likely
to be lost from both HMO and FFS systems All analyses of outcomes ad-justed for age, poverty status, and other variables to take into account this po-tential source of bias (see "Statistical Analysis")
Health Status Measures
Summary physical and mental health scales constructed from the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) were analyzed (Table 1) These summary measures capture 82% of the reliable variance in the 8 SF-36 health scores estimated us-ing the internal-consistency reliability method The construction of sum-mary measures, score reliability and va-lidity, and normative and other inter-pretation guidelines are documented elsewhere." ,"
Changes in health were estimated in
2 ways First, baseline scores were sub-tracted from 4-year follow-up scores, with deaths assigned a follow-up physi-cal health score of 0 (Table 1) Although these average change scores have the advantage of reflecting the magnitude
Trang 3of change in the metric of the scales,
they mask the proportion of patients
with follow-up scores that differed from
those at baseline Therefore, individual
patients also were classified into 3 change
categories: (1) those whose follow-up
score did not change more than would
be expected by chance ("same" group);
(2) those who improved more than would
be expected ("better" group); and
(3) those whose score declined more than
would be expected and those who died
("worse" group) (Table 1) This latter
method has the advantage of combining
health status and mortality without
mak-ing any assumption about the "scale
value" of death Unlikely to be due to
measurement error, changes large
enough to be labeled better or worse
also have been shown to be relevant in
terms of a wide range of clinical and
social criteria."
Estimates of health outcomes for
sur-vivors only were substantially biased
be-cause deaths were more common among
those with congestive heart failure, aged
65 years and older, and under FFS care;
deaths were less likely for the clinically
depressed group Differences in survival
rates between FFS and HMO systems
were insignificant after adjustment for
baseline patient characteristics Thus,
al-ternative methods of coding deaths" in
estimating outcomes did not affect
com-parisons between FFS and HMO
sys-tems (MOS unpublished data)
Statistical Analysis
The goal of the analysis was to
com-pare HMO and FFS systems of care in
terms of average changes in health
sta-tus and in terms of the percentages of
patients who were better, the same, or
worse at follow-up These outcomes were
estimated for all patients, and separately
for subgroups differing in age, poverty
status, and initial health Multivariate
statistical methods were used to adjust
baseline scores so that the HMO and
FFS groups would begin as equal as
possible in terms of demographic and
socioeconomic characteristics, study site,
chronic conditions, disease severity,
co-morbid conditions, initial health status,
and other design variables (Table 2)
Independent regression models were
estimated for physical and mental health
summary measures, and F tests of
sig-nificance determined whether adjusted
change scores differed, on average, across
HMO and FFS systems To make sure
that the summary measures did not miss
a difference concentrated in 1 of the 8
scales, all comparisons between FFS and
HMO systems also were replicated for
each of the 8 SF-36 scales Because the
summary measures captured all
signifi-cant differences, results of their analyses
Baseline Physical health 36-Item Short-Form Health Survey (SF-36) Physical Health Summary Scale, standardized to have a mean=50, SD=10 in the general US population 13 I nternal-consistency reliability=0.91; test-retest reliability=0.89, which exceed the minimum standard suggested for group-level comparisons."
Mental health SF-36 Mental Health Summary Scale, standardized to have mean=50, SD=10 in the general US population 1 3 I nternal-consistency reliability=0.87; test-retest reliability=0.80, which exceed the minimum standard suggested for group-level comparisons."
Mean changes Physical health Calculated for all patients as [(score at 4-year follow-up) -(baseline score)], prorated to adjust for unequal
ti me intervals Patients who died during the study were assigned a score of 0 at 4-year follow-up 16 A score
of 0 falls about 1 SD below the worst possible score, a score that was observed among MOS survivors.
A score of 0 is also about 1 SD below the worst health state quantified in preliminary studies of an SF-36-based utility index, which combines health status and mortality Sensitivity analyses with deaths scored 1 SD above and 1 SD below a score of 0 did not change conclusions about differences in health outcomes between fee-for-service and prepaid health maintenance (HMO) plans (MOS unpublished data) Mental health
Calculated for surviving patients as [(score at 4-year follow-up) -(baseline score)], prorated to adjust for unequal time intervals.
Categories of change Physical health Each patient was classified into 1 of 3 categories, according to the direction and magnitude of change between baseline and 4-year follow-up Patients whose scores declined by more than 6.5 points were categorized as worse Those who scores improved by more than 6.5 points were categorized as better.
Those whose scores were within 6.5 points at baseline and follow-up were classified as same Patients who died during the follow-up period were included in the worse group As documented elsewhere, 3 a change greater than 6.5 is outside of the 95% confidence interval for an individual patient score, as estimated from the SD and score reliability 13 Differences this large have been shown to be clinically and socially relevant For example, average improvements in SF-36 Physical Health Summary scores this large
or larger were observed following heart valve replacement surgery and total hip arthroplasty; such improvements are predictive of a one third decrease in probability of job loss, within the next year, among working patients." Patients who declined enough to be classified as worse in physical health at the end of 4 years were nearly 10 times more likely (0.9I vs 8.1%, P<.001) to die during the subsequent
3 years.
Mental health Each surviving patient was classified into 1 of 3 categories according to the direction and magnitude of change between baseline and 4-year follow-up Patients whose scores declined by more than 7.9 points were categorized as worse, those whose scores improved by more than 7.9 points were categorized as better, and those whose scores were within 7.9 points were classified as same A change of this amount is outside the 95% confidence interval for an individual patient score. 13An improvement in mental health nearly this large was observed for the average elderly depressed patient who responded to drug treatment
in comparison with nonresponders 25
are reported here Results for the 8
SF-36 scales are documented elsewhere (MOS unpublished data)
Multinominal (polytomous) logistic re-gression" methods were used to com-pare categorical changes (better, same, worse) in physical and mental health across HMO and FFS systems for the total sample and for the subgroups Ad-justed percentages for change catego-ries were generated with statistical ad-justments for the same baseline characteristics used in linear models (Table 2) The X2 tests of significance were computed to determine whether the percentages across change catego-ries differed between HMO and FFS systems of care
Comparisons of outcomes across sys-tems reported here combine results for IPA "network" and staff-model HMOs
As in previous MOS analyses , 4 there were
no significant differences in outcomes for those in WAS and staff-model HMOs in any of the analyses performed and there were no consistent trends suggesting a difference between IPAs and staff-model HMOs However, because only 28% of prepaid patients were sampled from WAS, the MOS did not have enough statistical power to meaningfully compare outcomes across types of HMOs
To facilitate interpretation, regression
models were used to estimate adjusted outcomes for the total sample and for each subgroup in comparing outcomes be-tween FFS and HMO systems Formal statistical tests for interactions were per-formed to determine whether conclusions about differences between systems were the same across subgroups differing in age (Medicare), poverty status, Medicaid coverage, and initial health To test for differences in outcomes for groups in bet-ter or worse initial health status, patients were stratified using baseline physical and mental health measures, both for lin-ear and logistic regression models Thirds
of the sample were identified based on whether they were functioning (physi-cally or mentally) higher, lower, or as would be expected at baseline, given their age and medical condition (Table 2)
In keeping with the logic of an intention-to-treat analysis, patients were analyzed according to the system from which they were sampled In support of this decision, the great majority of patients had been in their system 4 years or more at the time
of sampling and most who switched did not do so for another 2 years Thus, more than two thirds of those who switched systems during the 4-year follow-up had been in the type of system they were sampled from for 6 or more years before switching However, because MOS
Trang 4pa-Main effects
System of care
Sampled from prepaid health maintenance organization (HMO) or fee-for-service care*
Age
Age -65 y or age <65 y, classified at baseline
Sex
Male or female
Race
White, black, or other minority
Poverty status
Above or below 200% of poverty, defined as per capita household income in 1986 dollars
Medical Outcomes Study (MOS) tracer conditions
Hypertension, myocardial infarction (MI), congestive heart failure, non-insulin-dependent diabetes mellitus,
depressive disorder
Comorbid medical conditionst
Asthma, chronic obstructive pulmonary disease, angina (ever), angina (recent, no MI), MI past, other lung
disease, back pain/sciatica, hip impairments, rheumatoid arthritis, osteoarthritis, musculoskeletal
complaints, other rheumatic disease, colitis, diverticulitis, fistulas, gallbladder disease, irritable bowel
disease, liver disease, type I diabetes mellitus, ulcer, kidney disease, benign prostatic hypertrophy, urinary
tract infection, varicosities, cancer, dermatitis, anemia
I nitial physical or mental health
Tertiles of baseline health status estimated from multiple linear regression models that adjusted for age,
MOS tracer conditions, and comorbid medical conditions Initial tertiles labeled as "good," "average," and
"ill" health were defined by thirds of the distribution of residuals from each regression model; these patients
were, respectively, functioning better than expected, as expected, or worse than expected, given their age
and medical condition
MOS design variables
Study site, cluster sampling of patients within physician offices, seasonality, weights for unequal probability
caused by design choices and nonresponse
Two-way interaction terms
HMO and age ?65 y
HMO and poverty status
HMO and physical or mental health tertiles
Age ?65 y and poverty
Age -65 y and physical or mental health tertiles
Poverty and physical or mental health tertiles
Three-way interaction terms
HMO and age -65 and physical or mental health tertiles
HMO and poverty and physical or mental health tertiles
*Thirty patients (1.9% of those followed) who reported no insurance coverage were included in the fee-for-service
group All were younger than 65 years Analyses excluding the uninsured group did not change the conclusions from
comparisons between systems reported here.
tInformation regarding the comorbid medical conditions was obtained from the patient during a structured medical
history interview conducted by a trained clinician If information regarding a condition (or conditions) was missing,
an independently derived probability of each diagnosis was substituted Because of very low prevalence, the
following conditions are incorporated into an index of 11 comorbid conditions: angina (ever), other rheumatic disease,
colitis, diverticulitis, intestinal fistulas, gallbladder disease, liver disease, benign prostatic hypertrophy, varicosities,
cancer, and type I diabetes mellitus.
tients were more likely to switch from an
HMO than from an FFS plan (20% vs
15%; P<.01), estimates of outcomes could
have been biased This potential source
of bias was evaluated by comparing rates
of switching within elderly and poverty
subgroups along with average outcomes
for those who did and did not switch As
documented elsewhere (MOS unpublished
data), the relative probability of
switch-ing from an HMO observed within the
elderly and poverty subgroups was
com-parable to that for the total sample
Fur-ther, baseline scores and average changes
in physical and mental health did not
dif-fer significantly for those who did and did
not switch plans within either subgroup
( MOS unpublished data) Thus,
conclu-sions about system differences in health
outcomes are not likely to have been
bi-ased by the intention-to-treat method of
analysis used in this study
To evaluate whether differences in
rates of loss to follow-up were a source of
bias in comparisons of outcomes between
systems, these rates were compared for
the total sample and separately for the
elderly and poverty subgroups As
docu-mented in detail elsewhere (MOS
unpub-lished data), follow-up rates did not
dif-fer between the 2 system cohorts for the total sample (71% vs 70% for FFS and HMO, respectively), among the elderly (both 74%), or for those in poverty (62%
vs 60%) Baseline physical health scores for those followed up and lost to
follow-up did not differ between FFS and HMO cohorts in analyses of the total sample or for elderly or poverty subgroups To de-termine whether those lost and followed for health status outcomes had equal sur-vival probabilities, sursur-vival was moni-tored for all study participants for 7 years after baseline Survival probabilities did not differ for those followed up and those lost to follow-up As documented in de-tail elsewhere (MOS unpublished data), mental health scores for those lost to follow-up were significantly (P<.001) lower at baseline for both FFS and HMO cohorts The same pattern was observed for elderly and poverty subgroups, with
a significant difference favoring FFS over HMO for the poverty group (P<.05) (MOS unpublished data) However, as documented in the tables cited in the
"Results," adjusted physical and mental health scores for the follow-up samples analyzed here did not differ at baseline in comparisons between FFS and HMO
co-horts within the total follow-up sample, the elderly subgroup, or the poverty sub-group
To test whether differences in patient outcomes between FFS and HMO sys-tems could be explained by the specialty
of their regular physicians, these dif-ferences were also estimated with sta-tistical adjustment for physician special-ties Estimates of outcomes for each system were equivalent with and with-out adjustment for specialty and are re-ported here without adjustment
To facilitate interpretation, all tables
of results include 95% confidence inter-vals around average change scores and all differences associated with a chance probability of 05 or less were consid-ered statistically significant Significance tests were not adjusted for multiple com-parisons
We hypothesized that the MOS sample would score below 50, the norm for the general population, on both measures at baseline, and they did Because there are good arguments for hypothesizing better or worse outcomes across HMO and FFS systems over the 4-year
follow-up period, we used 2-tailed tests of sig-nificance throughout
RESULTS
Adjusted physical and mental health scores were virtually identical at base-line for patients sampled from HMO and FFS systems (Table 3) In relation to pub-lished norms for the US general popula-tion," MOS patients scored at the 24th and 35th percentiles for physical and men-tal health, respectively, indicating sub-stantially more physical impairment and emotional distress than experienced by the great majority of adults During the 4-year follow-up, average changes in physical and mental health were indis-tinguishable between HMO and FFS sys-tems Physical health scores declined about 3 points in both systems, lowering the average patient to the 19th percentile
at follow-up Mental health improved slightly in both systems, raising the av-erage to about the 38th percentile The MOS had sufficient statistical power to detect differences in health outcomes as small as 1 to 2 points be-tween HMO and FFS systems of care According to published interpretation guidelines for the SF-36 Health Sur-vey," differences of this amount or smaller are rarely clinically or socially relevant Thus, there is a basis for con-fidence that an important average dif-ference in health outcomes between HMO and FFS systems was not missed Analyses of change scores categorized
as better, same, or worse confirmed these results for physical and mental health for the average patient
Trang 5How-*HMO indicates health maintenance organization Scores are adjusted for demographics, chronic disease, and design factors The 4-year change scores for physical health (but not mental health) include deaths scored at 0 at 4-year follow-up.
tThe X2 statistics for categorical change refer to the results shown below and i ndicate whether the patterns of change are equal across the following pair of rows.
$Significance tests for average scores indicate whether the mean score in 1 row differed from the mean score for the other row.
§If the 95% confidence interval (CI) does not include 0, then average change scores are larger than expected by chance (P<.05).
IIP<.001.
~P=.01.
Table 4.-Physical and Mental Health Outcomes in Prepaid and Fee-for-Service Systems for Elderly and Nonelderly Patients
ever, the categorical analyses called
at-tention to substantial variation in
out-comes Physical health scores at
follow-up differed (from those at baseline) for
45% of patients; about 30% declined and
15% improved, more than would be
ex-pected due to measurement error The
reverse pattern-improvement more
of-ten than decline-was observed for
men-tal health scores (Table 3)
Variations in Outcomes for Elderly
and Poverty Groups
The average adjusted physical decline
was greater for elderly than nonelderly
patients (0=-5.8 vs -1.9; P<.001); 36%
and 26% of elderly and nonelderly
pa-tients, respectively, scored worse at
fol-low-up than at baseline (P<.001) (Table
3) Elderly patients scored higher in
men-*Scores are adjusted for demographics, chronic disease, and design factors The 4-year change scores for physical health (but not mental health) include deaths scored
at 0 at 4-year follow-up.
tThe X 2 statistics for categorical change refer to the results shown below and indicate whether the patterns of change are equal across the following pair of rows.
$Significance tests for average scores indicate whether the mean score for the health maintenance organization (HMO) group differs from the mean score for the fee-for-service (FFS) group.
§If the 95% confidence interval (CI) does not include 0, then average change scores are larger than expected by chance (P<.05).
IIP=.001.
#P-05.
**P<.001.
tt P-01.
tal health than nonelderly at baseline (P<.001); nonelderly patients improved significantly over time while the elderly did not
Both poverty and nonpoverty groups declined in physical health (0=-3.6 and -2.9, respectively), which are not sig-nificantly different amounts Mental health improved significantly for non-poverty patients but did not improve for those in the poverty group
Differences in Outcomes by System:
Elderly and Nonelderly
Although adjusted baseline scores were equivalent for elderly and nonel-derly patients in comparisons between HMO and FFS systems (Table 4), changes in physical and mental health scores over time for the elderly in HMO
and FFS plans were significantly dif-ferent from those for the nonelderly (F=2.1, P<.05, and X2=35.6, P<.001 for physical health; F=1.3, P>.05, and Xz=25.9, P<.01 for mental health) (Table 4) Physical health outcomes were, on average, more favorable for nonelderly patients in HMOs, while physical health outcomes were more favorable for el-derly patients in FFS
Although we could say with statistical confidence that the patterns of average change scores were different across HMO and FFS systems for elderly and nonel-derly patients, only pairwise comparisons between categories of changes were sig-nificant for the elderly (Table 4) The analysis of change categories also revealed that physical health was much less stable over time for elderly patients in HMOs
No.
Average Scores
Baseline* 4-y At 95% CI§
Categorical Change, */.t
Worse Same Better
Average Scores
Baseline* 4-y At 95% CI§
Categorical Change, %t
Worse Same Better
Total sample 2235 45.0 -3.0 -3.8 to -2.2 29 56 15 48.5 1.1 0.3 to 1.9 15 63 22 Service system
Prepaid (HMO) 1073 44.9 -3.1 -4.3 to -1.9 30
X2=1 5
55 15 47.9 1.2 0.0 to 2.4 14
X2 =1 3_
64 22
Fee-for-service 1162 45.2 -3.0 -4.2 to -1.8 27 57 15 49.0 1.0 -0.4 to 2.4 16 63 21 Age
Elderly 822 43.5§ -5.8T -7.0 to -4.6 36
X2 =14.111
53 11 50.3T 0.7 -0.5 to 1.9 15
X24.3
Nonelderly 1413 45.7 -1.9 -2.9 to -0.9 26 58 17 47.7 1.3 0.3 to 2.3 15 63, 22 Poverty status
Poverty 489 44.4 -3.6 -5.2 to -2.0 33
X2=4.6
51 17 47.6 0.7 -1.1 to 2.5 17
' X2=1:6
Nonpoverty 1746 45.2 -2.9 -3.7 to -2.1 27 58 15 48.8 1.2 0.4 to 2.0 15 64 21
Average Scores Categorical Change, %t Average Scores Categorical Change, %t
No Baseline (SE) 4-y A$ 95% CI§ Worse Same Better Baseline (SE) 4-y At 95% CI§ Worse Same Better
Prepaid (HMO) 346 43.4 (0.7) -7.0 -8.8 to -5.2 54 37 9 50.1 (0.8) 1.3 -0.5 to 3.1 14 60 26
Fee-for-service 476 43.5 (0.7) -5.0 -6.6 to -3.4 28 63 9 50.6 (0.8) 0.2 -1.6 to 2.0 14 73 13
Prepaid (HMO) 727 45.8 (0.5) -1.2 -2.6 to 0.2 23 62 16 46.9 (0.6) 1.5 0.1 to 2.9 12 68 20 Fee-for-service 686 45.6 (0.5) -2.4 -3.8 to -1.0 29 57 15 48.5 (0.5) 1.1 -0.7 to 2.9 16 64 19 Test for equivalence
of differences in
outcomes between
prepaid and
fee-for-service systems
among elderly vs
Trang 6*Scores are adjusted for demographics, chronic disease, and design factors The 4-year change scores for physical health (but not mental health) include deaths scored atoat 4-year follow-up HMO indicates health maintenance organization.
tThe )(3 statistics for categorical change refer to the results shown below and indicate whether the patterns of change are equal.
*Significance tests for average scores indicate whether the mean score for the HMO group differs from the mean score for the fee-for-service group.
§lt the 95% confidence i nterval (CI) does not include 0, then average change scores are larger than expected by chance (P<05).
II P=.01.
#P<.001.
**P=.03.
Table 6.-Physical and Mental Health Outcomes in Prepaid and Fee-for-Service Systems for Initially III Patients in the Poverty Group
Average Scorest Categorical Change, %# Average Scorest Categorical Change, %3
No. Baseline (SE) 4y A 95% CI§ Worse Same Better Baseline (SE) 4y A 95% CI§ Worse Same Better
Prepaid (HMO) 90 35.21(0.8) -2.0# -5.1 to 1.1 33 45 22** 37.1 (0.9) 4.5 -1.4 to 10.4 16 55 29 Fee-for-service 126 32.1 (1.0) 5.4 2.1 to 8.7 5 38 57 37.5 (0.8) 5.9 2.2 to 9.6 16 34 49
*Scores are adjusted for demographics, chronic disease, and design factors The 4-year change scores for physical health (but not mental health) include deaths scored
at 0 at 4-year follow-up.
tSignificance tests for average scores indicate whether the mean score for the health maintenance organization (HMO) group differs from the mean score for the fee-for-service group.
$The Xz statistics for categorical change refer to the results shown below and indicate whether the patterns of change are equal across the following pair of rows.
§If the 951/6 confidence i nterval (CI) does not include 0, then average change scores are larger than expected by chance (P<.05).
IIP=.006.
1P-.014.
#P<.001.
**P=.04.
compared to those in FFS (37% vs 63%,
respectively, stayed the same; X2=19.2,
P<001) The elderly treated in HMOs
were nearly twice as likely to decline in
physical health over time (54% vs 28%,
P<001) (Table 4) The difference in
physi-cal health outcomes favoring FFS over
HMOs was statistically significant for
el-derly patients regardless of their initial
health (MOS unpublished data) Physical
health outcomes favoring FFS over
HMOs for the elderly were also apparent
in all 3 study sites (MOS unpublished
data).
Average changes in mental health for
elderly and nonelderly patients did not
favor 1 system over the other (P>.05).
However, analyses of mental health
change categories for elderly patients
favored HMOs over FFS; the elderly
were twice as likely to improve in an
HMO (26% vs 13% for FFS; X2=7.1,
P<03) This result was due entirely to
the better performance of HMOs in 1
study site A formal test for a statistical
interaction between plan and site
re-vealed that mental health outcomes in
HMOs differed significantly across the three sites (F=2.44, P<01).
Differences in Outcomes of Poverty and Nonpoverty Groups by System
As shown in Table 5, comparisons of physical and mental health outcomes across HMO and FFS systems produced different patterns of results for poverty and nonpoverty groups (F=2.7, P<.01, and X2= 24.2, P<.02 for physical health;
F=4.2, P<.001, and X2=23.0, P<.03 for mental health) Only the pairwise com-parisons between HMO and FFS sys-tems for poor patients who were in ill health at baseline were significant (Table 6) Those in HMOs experienced an av-erage decline of -2.0 in physical health;
those in FFS improved 5.4 points, on average (P<.001) Comparison of cat-egorical changes for poor patients in ini-tial ill health also favored FFS plans, with 57% scoring better at follow-up in FFS versus 22% in HMOs (X2=10.2, P<006).
To determine whether Medicaid sta-tus accounted for differences observed
in outcomes for the poor, HMO and FFS systems were compared among Medic-aid patients (n=216) MedicMedic-aid patients
in HMOs did not differ from Medicaid patients in FFS plans in health status at baseline or in health outcomes, as docu-mented elsewhere (MOS unpublished data), and there were no noteworthy trends However, because of the rela-tively small sample of Medicaid patients, the MOS did not have sufficient preci-sion to rule out an important difference among Medicaid patients favoring ei-ther system.
COMMENT Limitations
Limitations of the MOS have been discussed extensively,"" but some limi-tations and potential sources of bias war-rant special emphasis here Analyses of 4-year health outcomes have been a long time coming because of the many meth-odological challenges faced by the MOS.
Do results apply to current health care?
If cost-containment pressures have
in-Physical Health* Mental Health*s
Average Scores Categorical Change, %t Average Scores Categorical Change, %t
No Baseline (SE) 4y A4 95% CI§ Worse Same Better Baseline (SE) 4y A* 95% CI§ Worse Same Better
Prepaid (HMO) 295 43.3 (0.9) -4.0 -6.2 to -1.8 32 58 9 47.2(l.0) -0.4 -3.9 to 3.1 14 71 14 Fee-for-service 194 45.1 (0.8) -3.3 -5.7 to -0.9 36 46 18 47.9 (0.8) 1.3 -1.2 to 3.8 17 57 26
Prepaid (HMO) 879 45.3 (0.5) -2.2 -3.6 to -0.8 24 62 13 47.9 (0.5) 1.4 0.2 to 2.6 11 70 18 Fee-for-service 867 45.1 (0.4) -3.4 -4.6 to -2.2 30 57 12 49.5 (0.5) 1.0 -0.8 to 2.8 16 66 18 Test for equivalence
of differences in
out-comes between
pre-paid and
fee-for-service systems
among poverty vs
non poverty subgroups Fa,1s1e=2.711 X2=24.21 Fa,3s3-4.2# X2=23.0**
Trang 7creased since MOS data collection ended
in the early 1990s, high-risk patient
groups may be at an even greater risk
today If information systems for
moni-toring and improving the quality of care
are better now and if health promotion
and disease prevention initiatives are
more successful in HMOs, MOS results
may not apply to current health care.
The MOS was not a randomized trial;
such trials are rare in health care policy
research.'a'9 Although
quasi-experimen-tal methods2° achieved equivalent
aver-age baseline health status scores for
nearly all pairwise-comparisons between
FFS and HMO systems of care,
unmea-sured risk factors could have biased
es-timates of differences in outcomes
Fur-ther, differences in outcomes that
occurred "on the watch" of the FFS and
HMO systems are not necessarily their
responsibility Structural and process
differences in care beyond their control,
such as arrangements for home health
and long-term care, may account in part
-for MOS findings.
The MOS monitored outcomes in only
3 large urban cities; results should not
be generalized to HMO or FFS plans in
other cities or rural areas Although the
MOS represented 5 chronic conditions
and many patients had comorbid
condi-tions such as angina, back pain/sciatica,
lung disease, and osteoarthritis, these
patients do not necessarily represent
other conditions or results of care
pro-vided by other medical specialties All
patients had a regular source of care.
All patients were being actively treated
when the MOS began, and only three
fourths who agreed to participate were
followed up longitudinally.
Two potential sources of bias in
esti-mates of health outcomes-plan
switch-ing and loss to follow-up-were
system-atically studied Patient loss to
follow-up is an unlikely source of bias in
comparisons of outcomes between
sys-tems because adjusted physical health
scores at baseline did not differ between
FFS and HMO cohorts followed within
the total sample or for elderly or
pov-erty subgroups (Tables 3 through 5).
Further, all study participants were
fol-lowed up through 1993 to determine their
survival." Seven years after baseline,
those included and not included in this
4-year analysis were equally likely to
have survived (MOS unpublished data).
Two of 10 HMO patients switched to
an FFS plan by the end of the 4-year
follow-up Comparisons between
sys-tems could have been biased had these
rates differed within elderly or poverty
subgroups or had switchrs experienced
different outcomes than nonswitchers.
However, rates of switching did not
dif-fer for elderly or poverty subgroups,
and system differences in physical and mental health outcomes were indistin-guishable for those who stayed in the same system, in comparison with those who switched (MOS unpublished data).
Thus, it is unlikely that conclusions about system differences in outcomes were bi-ased by switching Because more than two thirds of patients who switched sys-tems during the follow-up period had been in their system at least 6 years before switching, we adhered to the logic
of intent to treat and analyzed patients according to the systems from which they were sampled The finding that MOS patients were significantly more likely to switch from an HMO than to an HMO (20% vs 15%; X2 =7.3, P<.01) is surprising given that most MOS patients were aged 60 years or older, all were chronically ill, and financial incentives were beginning to favor HMOs over FFS during the MOS The dynamics of switch-ing and their implications for monitor-ing current health outcomes warrant fur-ther study.
Although the MOS achieved the de-sired statistical precision for overall HMO vs FFS comparisons, confidence intervals were too large for meaningful interpretation of some comparisons that yielded insignificant differences in out-comes Examples include comparisons between IPAs, the fastest growing form
of HMO, and staff-model HMOs; Med-icaid and non-MedMed-icaid groups could not
be compared with precision, and com-parisons between plans within sites were relatively imprecise, although the dif-ference in 1 site was large enough to reach significance (This difference would not have been significant with an ad-justment for multiple comparisons.) For many comparisons, the MOS cannot rule out large differences in outcomes in ei-ther direction.
Interpretation of Results
The success of HMOs in reducing health care utilization has been docu-mented in numerous studies? ,'9 With few exceptions, the best-designed and most recent studies show that HMOs achieve lower hospital admission rates, shorter hospital stays, rely on fewer subspecial-ists, and make less use of expensive tech-nologies Results from FFS-HMO com-parisons of utilization rates in the MOS ,,"
are consistent with previous studies, and extend that evidence to the population
of adults with chronic conditions, for whom health outcomes are reported here Rarely have the same studies
Results from the MOS lead us to sev-eral conclusions about health outcomes for the chronically ill adults who were treated in HMO and FFS systems of
care during the years of the MOS First, similarities in health outcomes between systems previously reported' for the av-erage MOS patient with hypertension
or NIDDM do not appear to hold for elderly patients covered by Medicare or for those in poverty Elderly patients sampled from an HMO were more likely (than those sampled from an FFS plan)
to have a poor physical health outcome
in all 3 sites studied Second, patients in the poverty group and particularly those most physically limited appear to be at
a greater risk of a decline in health in an HMO than similar patients in an FFS plan Finally, MOS results suggest the need for caution in generalizing conclu-sions about outcomes across study sites Mental health outcomes for Medicare patients differed significantly across HMOs, suggesting that their perfor-mance relative to FFS plans may de-pend on site.
Previous studies;'-21 that found no dif-ferences in health outcomes between FFS and HMO plans followed patients for only 1 year Were these studies too brief to draw conclusions about health outcomes? Supporting this explanation, significant differences in health outcomes observed between the FFS and HMO systems after 4 years of follow-up in the MOS were not statistically significant after 1 year The importance of a longer follow-up is underscored by the obser-vation that the 4-year statistical models reported here explained twice as much
of the variance in patient outcomes as did the same models in analyses of 1- and 2-year outcomes (MOS unpub-lished data) Thus, follow-up periods longer than i year may be required to detect differences in outcomes for groups differing in chronic condition, age, in-come, and across different health care systems.
Future Outcomes Studies
Our results raise many questions that the MOS was not designed to address What are the "clinical" correlates of changes in patient-assessed functional health and well-being? What can health care plans do to improve outcomes, and what specific treatments have been linked to physical and mental health out-comes as measured by the SF-36 Health Survey? Adverse medical events were too rare for meaningful comparison be-tween plans in the MOS and were moni-tored only during the first 2 years of follow-up' However, these events were significantly related to health outcomes,
as hypothesized Declines in SF-36 physi-cal health scores were significantly more likely among patients who experienced
a new myocardial infarction, weight loss sufficient to warrant a physician visit,
Trang 8and chest pain sufficient to require
hos-pitalization (MOS unpublished data)
These preliminary MOS results are
con-sistent with published studies that have
linked SF-36 health scores to disease
severity and to treatment response,
in-cluding severity of soft-tissue injuries"
and changes in hematocrit among chronic
dialysis patients 2 5 The SF-36 studies of
outcomes have also linked treatment to
outcomes including drug treatment for
depression among the elderly,26 total
knee replacement 2',21 heart valve
re-placement surgery ,21 use of aerosol
in-halers in treating asthma, 3°
intermit-tent vs maintenance drug therapy for
duodenal ulcer," elective hip
arthro-plasty,32 elective coronary
revascular-ization," and various other elective
sur-gical procedures 34 Three dozen such
studies using the SF-36 are cited
else-where.15 Identification of the clinical
correlates of changes in physical and
mental health status warrants high
pri-ority in outcomes and effectiveness
re-search."
Future studies should address
whether variations in the quality of care
explain differences in outcomes across
systems The MOS patients in HMOs
reported fewer financial barriers and
better coordination of services in
com-parisons with equivalent FFS
pa-tients 12,3s Analyses of primary care
qual-ity criteria indicated that those in FFS
systems experienced shorter treatment
queues and better comprehensiveness
and continuity of care and rated the
qual-ity of their care more favorably.12,3' D o
such variations in process account for
differences in outcomes? Practice-level
analyses in progress have linked scores
for primary care process indicators12 to
4-year health outcomes, as defined here,
supporting this hypothesis These and
other associations warrant further study
to determine which practice styles and
specific treatments are most likely to
i mprove health outcomes Because many
of the structural and process indicators
being relied on to evaluate the quality of
current health care have not been shown
to predict outcomes, targeted
monitor-ing efforts are required to discern health
outcomes
The MOS has demonstrated the
fea-sibility and usefulness of readily
avail-able patient-based assessment tools,
such as the SF-36 Health Survey, in
monitoring outcomes across diverse
pa-tient populations and practice settings
The SF-36 summary measures of
physi-cal and mental health reduce the
num-ber of comparisons necessary to
moni-tor outcomes while retaining the option
of analyzing the 8-scale SF-36 health
profile on which they are based The
reporting of results in change
catego-ries in terms of better, same, and worse may simplify the reporting of outcomes
to diverse audiences and may make re-sults easier for them to understand More practical data collection and processing systems-under development-and ad-vances in understanding of the specific treatments that improve health scores the most and the clinical and social rel-evance of those improvements will in-crease their usefulness in improving pa-tient outcomes."
Policy Implications
The MOS results reported here and previously' for the average chronically ill patient constitute good news for those who consider HMOs as a solution to ris-ing health care costs Outcomes were equivalent for the average patient be-cause those who were younger, rela-tively healthy, and relarela-tively well-off financially did at least as well in HMOs
as in the FFS plans However, our re-sults sound a cautionary note to policy-makers who expect overall experience
to date with HMOs to generalize to spe-cific subgroups, such as Medicare ben-eficiaries or the poor Patients who were elderly and poor were more than twice
as likely to decline in health in an HMO than in an FFS plan (68% declined in physical health in an HMO vs 27% for FFS; P<.001) (MOS unpublished data)
An implication for future evaluations of changes in health care policies is that high-risk groups, including the elderly and poor who are chronically ill, should
be oversampled when outcomes are monitored to achieve the statistical pre-cision necessary to rule out harmful health effects
Medicaid coverage did not explain the differences in physical or mental health outcomes observed for the poor in MOS comparisons between FFS and HMO systems Only 1 in 5 poor were covered under Medicaid Further, when out-comes for MOS patients covered and not covered under Medicaid were com-pared, there were no significant differ-ences between FFS and HMO plans and there were no noteworthy trends (MOS unpublished data) Poverty status, as opposed to Medicaid beneficiary status, was the better marker of risk of a poor health outcome in an HMO This is not
a new finding The Health Insurance Experiment also observed that some health outcomes were less favorable over
a 5-year follow-up for low-income pa-tients in poor health in 1 HMO com-pared with equivalent patients under FFS care."
Final Comment
In this article, the MOS has docu-mented variations in health outcomes
for chronically ill patients that cannot
be explained in terms of measurement error For elderly Medicare patients and for poor patients, variations in outcomes during a 4-year period extending through 1990 were linked to FFS and HMO systems of care (the latter were predominantly staff-model HMOs) Other explanatory factors included prac-tice site, suggesting that health out-comes should be monitored on an ongo-ing basis, by particular HMO and by marketplace Outcomes did not differ across systems for those covered under Medicaid and could not be explained in terms of the specialty training of phy-sicians The contrast between results reported here for high-risk patients vs results reported previously for the average patient' underscore the hazard
in generalizing about outcomes on the basis of averages This is why quality improvement initiatives focus on var-iations rather than only on usual per-formance." Patient-based assessments
of outcomes are likely to add signifi-cantly to the evidence used in informing the public and policymakers regarding which health care plans perform best-not just in terms of price, but in overall quality and effectiveness
Indications in the text of "MOS unpublished data" refer to 16 pages of additional documents that are available at http://www.sf-36.com on the Internet These data are also available from the National Auxiliary Publications Service, document 05340 Order from NAPS, c/o Microfiche Publications, PO Box 3513, Grand Central Station, New York, NY 10163-3513 Remit in advance, in US funds only,
$7.75 for photocopies or $5 for microfiche Outside the United States and Canada, add postage of $4.50 The postage charge for any microfiche order is $1.50 Collection of 4-year health outcome data and preparation of this article were supported by grant 91-013 from the Functional Outcomes Program of the Henry J Kaiser Family Foundation, at The Health Institute, New England Medical Center, Boston, Mass (John E Ware, Jr, PhD, principal in-vestigator) Design and implementation of the MOS were sponsored by the Robert Wood Johnson Foundation, Princeton, NJ; the Henry J Kaiser Family Foundation, Menlo Park, Calif; and the Pew Charitable Trusts, Philadelphia, Pa Previously re-ported analyses were sponsored by the National Institute on Aging, Bethesda, Md; the Agency for Health Care Policy and Research; and the National Institute of Mental Health, Rockville, Md Partici-pating plans, professional organizations who as-sisted in recruitment, and our many colleagues who contributed to the success of the MOS are acknowl-edged elsewhere.` The authors acknowledge the thorough and constructive suggestions received from Allyson Ross Davies, PhD, Kathleen Lohr, PhD, Edward Perrin, PhD, Dana Safran, SeD, and anonymous JAMA peer reviewers; and gratefully acknowledge the editing and typing assistance of Orna Feldman, Sharon Ployer, Rebecca Voris, and Andrea Molina
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