National health care utilization estimates for the overall population and specific population subgroups are critical to policymakers and others concerned with access to medical care and the cost and sources of payment for that care. The Medical Expenditure Panel Survey (MEPS) is one of the core health care surveys in the United States that serves as a primary source for these essential national health care utilization estimates. The survey is designed to provide annual national estimates of the health care use, medical expenditures, sources of payment and insurance coverage for the U.S. population. In 2007, the survey experienced two survey design modifications: a new sample design and an upgrade to the Computer Assisted Personal Interview (CAPI) platform for the survey instrument, moving from a DOS to a Windows based environment. This study examines the impact of these survey design modifications on the national health care utilization estimates of the following health care services: ambulatory visits, in-patient stays, emergency room visits, dental visits and prescribed medicine purchases.
The overlapping panel design of the MEPS survey and its longitudinal features are particularly well suited to assess the impact of survey redesign modifications on estimates. Since two independent nationally representative samples are pooled to produce calendar year estimates, one has the capacity to compare estimates for a calendar year based on the “original survey design” in contrast to those derived from the “survey redesign.” This paper examines the correlates of nonresponse incorporated in the estimation techniques and adjustment methods employed in the survey, and the measures utilized for post-stratification overall and by panel. Particular attention is given to assessing the level of convergence in utilization estimates based on the alternative designs as well as the alignment of model based analyses that discern which factors are associated with health care use. The paper concludes with a discussion of strategies under consideration that may yield additional improvements in the accuracy for these critical policy relevant survey estimates.
J.W. Cohen, S.B. Cohen and J. Banthin, The Medical Expenditure Panel Survey: A National Information Resource to Support Healthcare Cost Research and Inform Policy And Practice, Medical Care, 47(7) (2009), S1:44-50.
S.B. Cohen, T.M. Ezzati-Rice, and W. Yu, The Utility of Extended Longitudinal Profiles in Predicting Future Health Care Expenditures, Medical Care, 44(5) (2006), 45-53.
S.B. Cohen, T.M. Ezzati-Rice and W. Yu, The Impact of Survey Attrition on Health Insurance Coverage Estimates in a National Longitudinal Health Care Survey, Journal of Health Services and Outcomes Research Methodology, 6 (2006), 111-125.
D. Kashihara and T.M. Ezzati-Rice, Characteristics of survey attrition in the household component of the Medical Expenditure Panel Survey, Proceedings of the Section on Survey Research Methods. American Statistical Association; (2004), 3758-3765.
Keywords: National longitudinal healthcare survey; Official healthcare statistics; Complex survey redesign; Healthcare utilization statistics
Biography: Dr. Cohen is Director of the Center for Financing, Access, and Cost Trends at the Agency for Healthcare Research and Quality (AHRQ). He directs a staff of approximately 50 highly trained and skilled statisticians, biostatisticians, survey researchers, economists, social scientists, clinicians and support staff conducting research. Dr. Cohen also leads the Center's administration of surveys and development of large primary data sets, including the Medical Expenditure Panel Survey (MEPS), to support health care policy and behavioral research and analyses. Dr. Cohen has authored over 100 journal articles and publications in the areas of biostatistics, survey research methodology, estimation, survey design and health services research. He is co-author of the text, Methodological Issues for Health Care Surveys. He has also served as an Associate Professor at the Johns Hopkins University and at the George Washington University. He is also a Fellow of the American Statistical Association.