[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.


                               References

       1. Medicaid managed care: it is time? Kent C, ed. In: 
     Medicine and Health Perspectives; 13 April 1992.
       2. Annual Report to the Governor and Legislature on Prepaid 
     Health Plans, May 1976, NTIS HRP 0015709.
       3. Christianson J. A comparative study of public sector 
     financing arrangements in mental health care. Proceedings of 
     the National Institute of Mental Health Symposium on Public 
     Sector Capitated Funding Mechanisms in Mental Health, 21-22 
     September 1987. Arlington, Virginia.
       4. Bates EW, Brown BS. Geriatric care needs and HMO 
     technology. A theoretical analysis and initial findings from 
     the National Medicare Competition Evaluation, Med Care. 
     1988;26:488-98.
       5. Freeborn DK, Pope CR, Mullooly JP, McFarland BH. 
     Consistently high users of medical care among the elderly. 
     Med Care: 1990;28:527-40.
       6. World Health Organization. Constitution of the World 
     Health Organization. Geneva: World Health Organization Basic 
     Documents; 1948.
       7. Stewart AL, Ware JE Jr, Brook RH. Construction and 
     Scoring of Aggregate Functional Status Measures. 2d ed. Santa 
     Monica, California: The RAND Corp; 1982.
       8. Kane RA, Kane RC, Arnold S. Measuring Social Functioning 
     in Mental Health Studies: Concepts and Instruments. 
     Rockville, Maryland: National Institute of Mental Health. 
     (ADM) 85-1384 U.S.D.
       9. Katz S. Ford AB, Moskowitz RW, Jackson BA, Jaffee MW. 
     Studies of illness in the aged. The index of ADL: a 
     standardized measure of biological and psychosocial function. 
     JAMA, 1963:185:914-9.
       10. Lawton MP, Moss M. Fulcommer M. Kleban MH. A research 
     and service oriented multilevel assessment instrument. J 
     Gerontol. 1982;37;91-9.
       11. Derogatis LR, Lipman RS, Rickels K, Uhlenbuth EH, Covi 
     L. The Hopkins Symptom Checklist (HSCL): a self-report 
     symptom inventory. Behav Sci. 1973;19:1-15.
       12. Znag WW. A self-rating depression scale. Arch Gen 
     Psychiatry. 1965;12:63-70.
       13. Lurie N, Ward NB, Shapiro MF, Brook RH. Termination 
     from Medi-Cal--does it affect health? N Engl J Med. 
     1984;310:480-4.
       14. Brook RH, Ware JE Jr, Rogers WH, Keeler EB, Davies AR, 
     Donald Ca, et al. Does free care improve adults' health? 
     Results from a randomized controlled trial. N Engl J Med. 
     1983;309:1426-34.
       15. Lurie N, Kamberg C, Brook RH. How free care improved 
     vision in the Rand Health Insurance Experiment. Am J Public 
     Health. 1989;79:640-2.
       16. Bindman AB, Grumbach K, Keane D, Lurie N. Evaluating 
     natural experiments: collecting primry data within vulnerable 
     populations. Fam Med 1993;25:114-9.
       17. Tobin J. Estimation of relationships for limited 
     dependent variables. Econometrica. 1958;26:24-36.
       18. Retchin SM, Brown R. The quality of ambulatory care in 
     Medicare health maintenance organization. Am J Public Health. 
     1990;80:411-5.
       19. Retchin SM, Brown B. Management of colorectal cancer in 
     Medicare health maintenance organizations. J Gen Intern Med. 
     1990;5:110-4.
       20. Retchin SM, Brown B. Elderly patients with congestive 
     heart failure under prepaid care. Am J Med. 1991;90:236-42.
       21. Retchin SM, Clement DC, Rossiter LF, Brown B, Brown R, 
     Nelson L. How the elderly fare in HMOs: outcomes from the 
     Medicare competition demonstrations. Health Serv Res. 
     1992;27:651-69.
       22. Udvarbelyi IS, Jeonlson L, Phillips RS, Epstein AM. 
     Comparison of the quality of ambulatory care for fee-for-
     service and prepaid patients. Am Intern Med. 1991;115:394-
     400.
       23. Manning WG, Leibowitz A, Goldberg GA, Rogers WH, 
     Newhouse JP. A controlled trial of the effect of a prepaid 
     group practice on use of services. N Engl J Med. 
     1984;310:1505-10.
       24. Ware JH Jr, Brook RH, Rogers WH, Keeler EB, Davies AR, 
     Sherboune CD, et al. Comparison of health outcomes at a 
     health maintenance organization with those of fee-for-service 
     care. Lancet. 1986;1:1017-22.
       25. Sloss EM, Keeler EB, Brook RH, Operskalski BH, Goldberg 
     GA, Newhouse JP. Effect of a health maintenance organization 
     on physiologic health. Results from a randomized trial. Am 
     Intern Med. 1987;106:130-8.
       26. Carey TS, Weis K. Diagnostic testing and return visits 
     for acute problems in prepaid, case-managed Medicaid plans 
     compared with fee-for-service. Arch Intern Med. 
     1990;150:2369-72.
       27. Carey T, Wels K, Homer C. Prepaid versus traditional 
     Medicaid plans: effects on preventive health care. J Clin 
     Epidemiol. 1990;43:1213-20.
       28. Lurie N, Moscovice IS, Finch M, Christianson JB, Popkin 
     MK. Does capitation affect the health of the chronically 
     mentally ill? Results from a randomized trial. JAMA. 
     1992;267:3300-4.
                                  ____


  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.

                          ____________________