Academic journal article Health Care Financing Review

Analysis of Underwriting Factors for AAPCC

Academic journal article Health Care Financing Review

Analysis of Underwriting Factors for AAPCC

Article excerpt

Introduction

Currently, the adjusted average per capita cost (AAPCC) formula is used to pay health maintenance organizations (HMOs) for medical services provided to enrolled Medicare beneficiaries. This formula is based on four underwriting factors (i.e., age, sex, institutional status, and for non-institutionalized persons, their welfare status) that adjust payment for variables thought to affect the costs of providing health services to Medicare beneficiaries (Kunkel and Powell, 1981). In addition, ratio adjustments are used to scale payments from national to local area averages to control for geographic variation in cost.

In this article, we analyze the AAPCC as currently used by calculating revised AAPCC factors from a more recent survey, i.e., the 1984 National Long-Term Care Survey (NLTCS), and comparing the payments implied by the original AAPCC and those suggested by the AAPCC revised with the 1984 NLTCS data. An important feature in this analysis is that we have the individual Medicare Part A and Part B payment records and can compare the actual Medicare expenses in the fee-for-service (FFS) sector with the payment amounts from either AAPCC schedule. Having the individual data permits us to examine additional underwriting factors defined from any variable deemed to be relevant from the NLTCS.

The goals of this analysis are threefold: * To demonstrate the effect of updating the AAPCC

factors (from the period of 1974-76 to 1984) to reflect

more current underwriting experience. * To evaluate the effect of adding an additional

underwriting factor based on chronic disability. * To use simulation methods to demonstrate the dollar

impact of these two changes on payments to HMOs

and the implications for HMO solvency.

Although our revised and modified estimates of AAPCC factors are not intended to replace the current AAPCC factors, the analyses presented represent the likely effects of such replacement.

Background

Several studies (e.g., Beebe, Lubitz, and Eggers, 1985; Lubitz, Beebe, and Riley, 1985) have assessed the ability of the AAPCC underwriting factors to explain cost variation. The amount of cost variation explained by the original four factors was low-only 0.5 percent of the variance in a recent analysis for cross-sectional data (Ash et al., 1989; Anderson, 1983; Beebe, Lubitz, and Eggers, 1985; Lubitz, Beebe, and Riley, 1985). This means that the formula may not accurately estimate the payments that HMO enrollees would have received had they remained in the FFS sector (Eggers, 1980; Eggers and Prihoda, 1982). As a consequence, there has been a search for additional underwriting factors that could better describe cost variation.

Underwriting factors, in addition to explaining payments and service use, must be based on easily measured factors and not be easily manipulated by providers. Prior service use (e.g., Beebe, Lubitz, and Eggers, 1985), disability status, and, most recently, diagnostic cost groups (DCG) have been considered as additional underwriting factors (Epstein and Cumella, 1988; Ash et al., 1989). None of these have explained more than 10 percent of the variance of Medicare costs. Usually less than 5 percent is explained (Ash et al., 1989). As a result of events unforseeable by either the HMO or the individual, the maximum achievable [R.sup.2] has been argued to be less than 100 percent-possibly closer to 15 percent to 20 percent (an estimate of 14.5 percent is provided in Newhouse et al., 1989; also see Welch, 1985).

In addition, searches for improved underwriting factors have been motivated by recent changes in Medicare payment practice and policy. The original AAPCC underwriting factors (Kunkel and Powell, 1981) were used unchanged through 1984. The first modification was in 1985, and since then the factors have been periodically revised. The existing underwriting factors have been updated using current Medicare expenditure data but not new survey data. …

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