Risk Adjustment for Health Plans Disproportionately Enrolling Frail Medicare Beneficiaries - Medicare+Choice

Health Care Financing Review, Spring, 2000 by Gerald F. Riley

INTRODUCTION

Beginning in the year 2000, Medicare is incorporating diagnostic information into its payment system for managed care plans under the Medicare Choice program. This reform of the payment system is in reaction to research showing that the adjusted average per capita cost (AAPCC), which uses demographic information to adjust payments for individual plan enrollees, is inadequate for risk adjustment (Riley et al., 1996; Physician Payment Review Commission, 1996; Brown et al., 1993). Initially, payments will be adjusted through the Principal Inpatient Diagnostic Cost Group (PIPDCG) system, which uses demographics and diagnoses associated with inpatient hospital stays occurring in the year prior to payment (Ellis et al., 1996). Other diagnosis-based risk-adjustment systems may be implemented in the future when additional types of encounter data become available from plans (Weiner et al., 1996; Pope et al., 1999; Carter et al., 1997). In general, diagnosis-based risk adjusters have been shown to be significantly better than the AAPCC in their ability to predict Medicare expenses.

There is currently concern among policymakers about the ability of diagnosis-based risk adjusters to appropriately set payments for health plans that disproportionately enroll frail, functionally impaired beneficiaries. Such plans include Program of All Inclusive Care for the Elderly (PACE); Social Health Maintenance Organization (S/HMO); Minnesota Senior Health Options (MSHO); and programs proposed by individual States to integrate Medicare and Medicaid services for frail dually eligible persons. As demonstration projects, most of these plans are paid a capitation rate based on the AAPCC, with a separate adjustment for enrollees who reside in the community and are nursing home certifiable (NHC) as defined by their State's Medicaid program. Under the Balanced Budget Act of 1997 (BBA), changes are expected to the payment methodologies for many of these projects. For example, PACE plans may be paid in the same manner as Medicare Choice plans, with an adjustment for the comparative frailty of their populations; the Department of Health and Human Services must also prepare a report on transitioning S/HMOs and similar plans to the Medicare Choice program. This raises the question of whether PIPDCGs and other currently available risk adjusters are appropriate for specialized programs serving frail enrollees.

Previous research suggests that diagnosis-based risk adjusters tend to significantly underpredict Medicare expenses for some expensive subgroups of Medicare beneficiaries, including persons with functional impairments living in the community (Pope et al., 1998, 1999; Gruenberg et al., 1999; McCall and Korb, 1998). These studies have also found that diagnosis-based adjusters tend to overpredict expenses for some low-cost subgroups, including persons without functional impairments. This suggests that functional impairment may be associated with health care expenses that are not reflected in diagnostic profiles. Diagnosed-based risk adjusters have also been found to overpredict Medicare expenses for persons institutionalized in long-term care (LTC) settings (Pope et al., 1998, 1999; Gruenberg et al., 1999; McCall and Korb, 1998).

The purpose of this study was to extend previous research that examined the ability of selected diagnosis-based risk adjusters to predict Medicare costs of frail and functionally impaired populations. This study addressed the following questions:

* How are Medicare expenses distributed across types of service, for different functional categories?

* Why do diagnosis-based risk adjusters predict expenses poorly for groups of people defined by functional status?

* Do diagnosis-based risk adjusters predict certain types of expenses better than others?

* Do diagnosis-based adjusters underpredict expenses for most functionally impaired persons, or for only a few who have high expenses?

DATA AND METHODS

Data

The data source for the study was the Medicare Current Beneficiary Survey (MCBS), a longitudinal, multipurpose survey of a nationally representative sample of the Medicare population (Adler, 1994). Both institutionalized persons and those residing in the community are included. Respondents are asked about health service utilization and costs, health status, and functional status. Survey responses are routinely linked to Medicare administrative records.

This study was conducted using a special file created by Health Economics Research for their development and validation of the PIPDCG model (Pope et al., 1999). The file contains MCBS data for 1991-1994. Persons with end stage renal disease or who were not entitled to Medicare Part A and Part B, or who were working aged, or who lived outside the United States were excluded. Each observation on the file contains PIPDCG and hierarchical coexisting condition (HCC) risk scores based on claims data in a base year (1991-1993), and actual expenses (excluding hospice expenses) incurred in the corresponding prediction year (1992-1994). Hospice expenses were excluded because they are not covered under Medicare capitation payments. Time in hospice and costs of non-hospice services incurred while enrolled in hospice were included in the study. If the sample person was in a health maintenance organization for part of either the base or prediction year, or if the person was not alive at the start of the prediction year, then that observation was deleted from the file. Individuals could contribute more than one observation to the file if they were in the survey for more than 2 years.