Back to Annual Meeting Page		American Public Health Association 133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA

Abstract #97056

Steven B. Cohen, PhD¹, Trena Ezzati-Rice, MS¹, and William Yu². (1) Center for Financing, Access and Cost Trends, Agency for Healthcare Research and Quality, 540 Gaither Road, Suite 5220, Rockville, MD 20850, 301-427-1466, scohen@ahrq.gov, (2) Division of Statistical Research and Methods, CFACT, Agency for Healthcare Research and Quality, 540 Gaither Road, Rockville, MD 20850

Given the high concentration of health care expenditures in a given year among a relatively small percentage of the population, a prediction model that can accurately identify the persistence of high levels of expenditures is an important analytical tool. This type of modeling effort also enhances the ability to discern the causes of high health care expenses and the characteristics of the individuals who incur them. This feature also applies to prediction models that can accurately identify those individuals with persistently low or average levels of expenditures. The models that are presented have particular relevance as statistical tools to facilitate efficient sampling strategies that permit the selection of an over-sample of individuals likely to incur high levels of medical expenditures in the future. Furthermore, such modeling efforts are particularly attractive to assist in the targeting of disease management programs to high cost cases, which may facilitate reductions in the concentration of overall future year health care expenditures. The national Medical Expenditure Panel Survey (MEPS), sponsored by the Agency for Healthcare Research and Quality (AHRQ), is particularly well suited for supporting modeling efforts of this nature. In this paper, the performance of alternative prediction models to identify future high expenditure cases is evaluated. Particular attention is given to investigating the added value of an extended longitudinal profile in accurately predicting future health care expenditures.

Learning Objectives:

• Participants in the session will acquire information and perspectives regarding the capacity of the Medical Expenditure Panel Survey to permit analyses of the U.S. health care system including the population’’s access to, use of, and expenditures and sources of payment for health care; the availability and costs of private health insurance in the employment-related and non-group markets; the population enrolled in public health insurance coverage and those without health care coverage; and the role of health status in health care use, expenditures, and household decision making, and in health insurance and employment. Participants will learn of the statistical and methodological strategies adopted in MEPS to improve the accuracy of resultant healthcare expenditure estimates.
• In addition, the models that are presented have particular relevance as statistical tools to facilitate efficient sampling strategies that permit the selection of an over-sample of individuals likely to incur high levels of medical expenditures in the future. Furthermore, such modeling efforts are particularly attractive to assist in the targeting of disease management programs to high cost cases, which may facilitate reductions in the concentration of overall future year health care expenditures.

Keywords: Cost Issues, Methodology

Related Web page: www.meps.ahrq.gov

Presenting author's disclosure statement:

I wish to disclose that I have NO financial interests or other relationship with the manufactures of commercial products, suppliers of commercial services or commertial supporters WITH THE EXCEPTION OF Employment.

Recorded presentation