Improving Identification of Medicaid Eligible Community-Dwelling Older Adults in Major Household Surveys with Limited Income or Asset Information.

Abstract

Analysis of public policy affecting dual eligibles requires accurate identification of survey respondents eligible for both Medicare and Medicaid. Doing so for Medicaid is particularly challenging given the complex eligibility rules tied to income and assets. In this paper we provide guidance on how to best identify eligible respondents in household surveys that have limited income or asset information, such as the National Health Interview Survey (NHIS), American Community Survey (ACS), Current Population Survey (CPS), and Medical Expenditure Panel Survey (MEPS). We show how two types of errors-false negative and false positive errors-are impacted by incorporating limited income or asset information, relative to the commonly-used approach of solely comparing total income to the income threshold. With the 2018 Health and Retirement Study (HRS), which has detailed income and asset information, we mimic the income and asset information available in those other household surveys and quantify how errors change when imposing income or asset tests with limited information. We show that incorporating all available income and asset data results in the lowest number of errors and the lowest overall error rates. We recommend that researchers adjust income and impose the asset test to the fullest extent possible when imputing Medicaid eligibility for Medicare enrollees.