Trena M. Ezzati-Rice

The utility of extended longitudinal profiles in predicting future health care expenditures

Background:Health care spending is highly concentrated. Prediction models that accurately identify the characteristics of individuals most likely to incur high levels of health expenditures in a subsequent year are important analytical and statistical tools. Objectives:This study examined the capacity of alternative models to predict the likelihood of incurring high levels of medical expenditures in a subsequent year. This effort also evaluated the utility of an additional year of longitudinal information. Subjects:A nationally representative sample from the Medical Expenditure Panel Survey (MEPS). Methods:The MEPS longitudinal data are used to examine the persistence of high expenditures during a 2-year period. With the unique linkage of the MEPS to the National Health Interview Survey, the utility of an additional year of data also was examined. Resultant models were evaluated in terms of sensitivity, specificity, and predictive capacity. Results:Only modest marginal gains in discrimination capacity were realized from the use of extended longitudinal profiles from the National Health Interview Survey, relative to information on prior year characteristics. Conclusions:Our results highlight the continuing concentration of health care expenditures during the period 1996 to 2002 and reveal some attenuation in magnitude in the tail of this distribution over time. Further, our results provide evidence of the utility of probabilistic models as prediction tools to identify individuals likely to incur high levels of expenditures in future years. Predictive capacity does not suffer when restricted to a single year of prior information.

The impact of survey attrition on health insurance coverage estimates in a National Longitudinal Health Care Survey

Timely, accurate and reliable estimates of the population’s health insurance status are essential inputs to policymakers to inform assessments of the population’s access to medical care and analyses of associated health care expenditures. Alternative criteria that have been used to produce annual estimates of the uninsured include the following specifications: those uninsured for a full-year, those ever uninsured during a year, and those uninsured at a specific point in time. The Medical Expenditure Panel Survey (MEPS), one of the core health care surveys in the United States, supports all three types of estimates. In this paper, a summary is provided of the survey operations, informational materials, the interviewer training and experience of the field force, and the refusal conversion techniques employed in the MEPS to maintain respondent cooperation for five rounds of interviewing, to help minimize sample attrition. The impact of nonresponse attributable to survey attrition is also assessed with respect to the national health insurance coverage estimates derived from the MEPS. The study includes an examination of the quality of the nonresponse adjustments employed to adjust for potential nonresponse bias attributable to survey attrition. The overlapping panel design of the MEPS survey is particularly well suited to inform these studies. The presentation concludes with a discussion of strategies under consideration that may yield additional improvements in the accuracy for these critical policy relevant survey estimates.

Health insurance coverage during a 24-month period: a comparison of estimates from two national health surveys

National estimates of the uninsured are available from multiple surveys and differ across surveys. Previous efforts to better understand reasons for differences among these estimates have primarily focused on annual estimates. This study compares national estimates of health insurance coverage over generally comparable 24-month time periods using two integrated Federal health-related surveys, the Medical Expenditure Panel Survey (MEPS) and the National Health Interview Survey (NHIS) for the years 2002–2003 and replicated analyses for 2001–2002. We examine survey participants insurance status in year 1 and year 2 based on the NHIS linked with the MEPS and also for MEPS year 1 and year 2 participants. We also examine characteristics associated with 24-month coverage status. National estimates of the percents continuously insured did not differ significantly between the two data sources. In contrast, the MEPS longitudinal estimate of the percent continuously uninsured was higher than the NHIS-MEPS linked estimate whereas the MEPS longitudinal estimate of the discontinuously insured was lower than that derived from the NHIS-MEPS linked data. Factors that help explain these differences include the non-equivalence of the time periods covered by the data sources, modest differences in the length of time covered by the MEPS and NHIS survey instruments, and length of recall. Regression analyses yielded highly consistent correlates of being continuously uninsured versus continuously insured for both data sources. Regression results for discontinuous versus continuous coverage were also generally similar for both data sources. Gaining a better understanding of the alignment in findings based on alternative data sources that support comparable analyses of health insurance coverage helps policymakers to make the most appropriate use of resultant estimates.

An assessment of the impact of two distinct survey design modifications on health care utilization estimates in the medical expenditure panel survey

The Medical Expenditure Panel Survey (MEPS) is one of the core health care surveys that are a primary source for essential national healthcare utilization estimates. In 2007, the survey experienced two dominant survey design modifications: a new sample design attributable to the sample redesign of the National Health Interview Survey, 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. 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 that may yield additional improvements in the accuracy for these policy relevant survey estimates.

The impact of survey design modifications on health insurance coverage estimates in a National Longitudinal Health Care Survey

National health insurance coverage 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 insurance coverage 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. civilian non-institutionalized population. In 2007, the survey experienced two dominant survey design modifications: (1) a new sample design attributable to the sample redesign of the National Health Interview Survey, and (2) an upgrade to the 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 estimates of insurance coverage. 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 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 coverage estimates based on the alternative designs as well as the alignment of model based analyses that discern which factors are associated with health insurance classifications. 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.