Modeling Medicare Costs of PACE Populations - Program of All-Inclusive Care for the Elderly

Health Care Financing Review, Spring, 2000 by James Robinson, Sarita L. Karon

INTRODUCTION

Concerns about high health care expenditure rates have given rise to a variety of public and private initiatives to better manage both the use and costs of health care services. Several programs have been developed that use managed care strategies to better control costs and utilization. One of the few such programs to address the needs of elders with complex and chronic care needs is the Program of All-Inclusive Care for the Elderly (PACE), a voluntary program that coordinates all acute and long-term care services and multiple sources of funding (typically, Medicare and Medicaid) for elders who are deemed to be "nursing home certifiable" (NHC) under the laws of their State. In the past, Medicare has paid PACE providers a monthly capitated rate equal to 95 percent of the site's county average adjusted per capita cost (AA CC), multiplied by a frailty adjuster of 2.39. The Balanced Budget Act of 1997 (BBA) makes PACE a permanent provider category and mandates that future Medicare payments be based upon the rate structure of the new Medicare+Choice (M+C) program. This study presents a model that can be used to calculate a frailty adjuster that is appropriate for a variety of populations, such as may be present in the different PACE sites.

The original development and subsequent analyses of the frailty adjuster by Gruenberg (Gruenberg, Tompkins, and Porell, 1990; Gruenberg, Silva, and Leutz, 1993; Gruenberg and Kaganova, 1997) used data from the Social Health Maintenance Organization (SHMO) demonstration program to develop models that predicted the likelihood that an individual would meet NHC criteria. These predictive models were applied to nationally representative data bases (the 1982 National Long-Term Care Survey [NLTCS], 1984 NLTCS, 1989 NLTCS, and the Medicare Current Beneficiary Survey [MCBS], depending on the particular study) to obtain NHC weights (predicted likelihoods) that were used in the regression of individual Medicare cost ratios against respondent characteristics, such as age, sex, and functional status. The fitted regression functions were then applied to the observed distribution of characteristics for existing PACE sites to estimate the aggregate ratio of PACE Medicare costs to national Medicare costs. The SHMO data were ideal for this purpose, as they provided a clinical assessment of NHC status, as well as self-reported data on health and functional status that closely approximated those available from the other surveys.

The use of data from the SHMO also imposes some important limitations in applying this experience to PACE. First, the data reflect the NHC definitions of only four States and do not reflect the experience of all States that are home to one or more PACE programs. Analyses by Gruenberg, Tompkins, and Porell (1990) found differences even among these four States in the definition of NHC. Although these differences appeared to have little impact on the average Medicare cost ratio, they did have a significant impact on the proportion of individuals predicted to be NHC. This has important implications for the costs that one might expect, as the PACE demonstration moves to a permanent provider status and is expanded to new sites.

Second, data are limited to those who are members of a SHMO program. Because the SHMO is a voluntary demonstration program, it is likely that there is some bias associated with the choice to enroll. It is difficult to assume that the SHMO population is representative of the general Medicare population or even of the NHC population. The use of a screening and queuing mechanism has been used to ensure that the SHMO population is, within broad categories, comparable to the average Medicare population in terms of impairment level (Leutz et al., 1988). However, this is a rather crude adjuster. Further, the SHMO population is overwhelmingly white, and few enrollees in the original four sites were eligible for Medicaid (Harrington, Newcomer, and Preston, 1993). These two factors alone distinguish the SHMO from the PACE program, which serves primarily low-income and substantially other-than-white populations. Both of these factors (income and race) are known to be associated with health care costs. Each of these reasons suggested that it would be useful to explore alternative methods of modeling NHC status.

Finally, an evaluation of this relationship in 1997 by Gruenberg et al. suggested that the PACE frailty adjuster was not excessive and might indeed be inadequate to capture the costs of the PACE membership. However, that study estimated Medicare costs based upon the characteristics of individuals currently enrolled in existing PACE sites. The expected expansion of PACE sites and likely increased variation among them raises concerns that such a method might not yield the best predictor of future costs. The study reported here was intended to address some of these challenges and to provide an assessment of the appropriateness of the frailty adjuster that is independent of the original developers of that rate.