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Using Adjusted MEPS Data to Study Incidence of Health Care Finance

Using Adjusted MEPS Data to Study Incidence of Health Care Finance. Thomas M. Selden Division of Modeling & Simulation Center for Financing, Access and Cost Trends. Advantages of HH Survey Data. Only HH survey data possess the correlations across variables necessary for: Behavioral research

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Using Adjusted MEPS Data to Study Incidence of Health Care Finance

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  1. Using Adjusted MEPS Data to Study Incidence of Health Care Finance Thomas M. Selden Division of Modeling & Simulation Center for Financing, Access and Cost Trends

  2. Advantages of HH Survey Data • Only HH survey data possess the correlations across variables necessary for: • Behavioral research • Subgroup or distributional estimates • Policy simulations

  3. Using MEPS to Study Finance Incidence • Prevalence and distribution of high out-of-pocket burdens • Overall population (Banthin and Bernard, JAMA) • Within-year burdens (Selden, HSR) • Policy impacts (Banthin and Selden, Inquiry; Selden, Kenney, et al., Health Affairs) • Distribution of benefits from public spending • Selden and Gray (Health Affairs) • Selden and Sing (Health Affairs) • Progressivity of the financing of health care • Selden (preliminary)

  4. Potential Issues with Using Unadjusted MEPS • Out-of-scope populations • Institutionalized persons not in MEPS • Out-of-scope expenditures • Personal care • Differential attrition (high-cost cases) • Under-reporting of use • Lump-sum payments to providers • MCR/MCD grants to hospitals for teaching/needy • Tax subsidies for coverage and care

  5. Presentation Overview • Present step-by-step results from efforts at AHRQ to adjust MEPS to • Include tax subsidies • Align with National Health Expenditure Accounts • Show some applications: • burdens • benefit incidence analysis • equity in financing of health care finance and use

  6. MEPS Data • Over 30,000 persons in over 10,000 households • Every year since 1996 • Civilian noninstitutionalized population • Households report use and expenditures during 5 in person interviews over 2 years • Supplemented by journal entries and follow back survey of providers • Compared to CMS NHEA every 5 years when availability of Census data on providers facilitates alignment (last done in 2002)

  7. Apples to Apples Comparison of MEPS & NHEA, 2002

  8. MEPS-Consistent NHEA Personal Health Care, 2002 • x Source: Selden and Sing (2008a)

  9. MEPS-Consistent NHEA Personal Health Care, 2002 (cont) • Producing this chart is a lot of work! • Aligning service definitions • Hospital-owned home health services • “Physician and clinical services” (allocated to Physician vs. Other professional as in MEPS) • LTC estimates • Acute care of LTC residents • Hospital-owned nursing homes • All adjustments by sources of payment and type of service...

  10. Closing the 13% Gap with MEPS-Consistent NHEA PHC • Step 1: Account for wider public coverage gap by upweighting persons with Medicaid/CHIP coverage • 10 percent increase • Brings enrolled population into alignment with administrative enrollment counts • Raking post-stratification used so that adjustment does not change full MEPS distribution of age, race, sex, Medicare enrollment, and uninsurance (so adjustment in essence entails modest reduction in private coverage)

  11. Closing the 13% Gap with MEPS-Consistent NHEA PHC • Step 2: Account for differential attrition of high-cost cases • upweighted top 3 percent of distribution by major insurance group (by average of 18%) • adjustment justified by analyses of claims data (public and private) • upweighting used raking post-stratification to preserve distribution by age, race, sex, poverty, coverage, region • closed 37% of the gap

  12. Closing the 13% Gap with MEPS-Consistent NHEA PHC • Step 3: Close remaining gap • Allocate lab test gap according to physician visits • Scale remaining expenditures • Brings MEPS up from $881B to $964B

  13. Out-of-Scope PHC Spending Note: Useful for reform simulations that would, say, cover uninsured or increase/decrease Medicaid population

  14. Non-PHC Spending Note: Useful for benefit incidence and equity analyses

  15. Application: Reform Simulations • NHEA-aligned MEPS data is at the heart of health reform simulations • Improves on situation in early 1990s, when simulations of previous health reforms differed largely due to different starting points • Projected NHEA-aligned MEPS

  16. Application: 20% Burden Frequency among Nonelderly with Private Insurance: With and without Adjusting for Tax Expenditures, 2002 Source: Selden (IJHCFE, 2008)

  17. Tax Expenditure Effect on Burdens is Small, Compared to: Within-Year Burdens and Cost-Sharing in Public Coverage for Children Source: Selden (HSR, 2009) Source: Selden et al. (HA, 2009)

  18. Application: Benefit Incidence Analysis of Public Spending * 80% of health care spending for persons in poor health paid by public sector Source: Selden and Sing (Health Affairs, 2008)

  19. Benefit Incidence (cont.) * Nearly half of all health care in highest income group paid by public sector Source: Selden and Sing (Health Affairs, 2008)

  20. Application: Equity in Health Care Finance, 2002

  21. Average Combined Burdens by Financing Source and Income Decile

  22. Conclusion • Adjusting MEPS to peg NHEA benchmarks and capture tax expenditures is a painstaking endeavor • The result, however, is a powerful tool for reform simulations and equity analyses

  23. Bibliography • Banthin and Bernard (2006) Changes in Financial Burdens for Health Care: National Estimates for the Population Younger Than 65 Years, 1996 to 2003, JAMA, v. 296, n. 22: 2712-2719. • Selden and Banthin (2003) The ABC's of children's health care: How the Medicaid expansions affected access, burdens, and coverage between 1987 and 1996, Inquiry 40:133-45. • Selden, Kenney, Pantell, Ruhter (2009) “Cost Sharing In Medicaid And CHIP: How Does It Affect Out-Of-Pocket Spending?” Health Affairs (http://content.healthaffairs.org/cgi/content/abstract/hlthaff.28.4.w607)

  24. Bibliography (cont.) • Selden (2009) The Within-Year Concentration of Medical Care: Implications for Family Out-of-Pocket Expenditure Burdens, Health Services Research, 44(3):1029-1051. • Selden and Gray (2008b) Tax Subsidies For Employment-Related Health Insurance: Estimates For 2006, Health Affairs (http://content.healthaffairs.org/cgi/content/abstract/25/6/1568) • Selden (2008) The effect of tax subsidies on high health care expenditure burdens in the United States, International Journal of Health Care Finance and Economics, v. 8: 209-223.

  25. Bibliography (cont.) • Selden and Sing (2008a) Aligning the Medical Expenditure Panel Survey to Aggregate U.S. Benchmarks, MEPS Working Paper (http://www.meps.ahrq.gov/mepsweb/data_stats/Pub_ProdResults_Details.jsp?pt=Working%20Paper&opt=2&id=862) • Selden and Sing (2008b) The Distribution Of Public Spending For Health Care In The United States, 2002, Health Affairs (http://content.healthaffairs.org/cgi/content/abstract/hlthaff.27.5.w349v1) • Selden, Equity in the Finance and Delivery of Health Care in the United States (unpublished)

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