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Estimating the Size of the Uninsured and Other Vulnerable Populations in a Local Area Lynn A. Blewett, Ph.D. Timothy Beebe, Ph.D.

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Presentation on theme: "Estimating the Size of the Uninsured and Other Vulnerable Populations in a Local Area Lynn A. Blewett, Ph.D. Timothy Beebe, Ph.D."— Presentation transcript:

1 Estimating the Size of the Uninsured and Other Vulnerable Populations in a Local Area Lynn A. Blewett, Ph.D. Timothy Beebe, Ph.D.

2 Estimating the Size of the Uninsured Populations at the Local Level 1.Do your own survey - To directly measure health insurance coverage and rates of uninsurance 2.Use existing available data to: -Develop proxy measures of uninsurance -Develop statistical model-based estimates

3 Direct Measures: National Data Three surveys provide state-level estimates of health insurance coverage. –Current Population Survey (CPS): Census –Medical Expenditure Panel (Employer) Survey – Insurance Component (MEPS-IC): Agency for Healthcare Research and Quality –State and Local Area Integrated Telephone Survey (SLAITS): National Center for Health Statistics

4 Direct Measures: State Data 37 States have developed and fielded their own state household survey to estimate levels of health insurance coverage –Many funded by the federal Health Resources Services and Administration State Planning Grant Program –Typically have larger sample size and some regional/county estimates of coverage

5 Proxy Measures Use an available measure to serve as a proxy for health insurance coverage Example: self-pay variable from hospital administrative records to estimate local levels of uninsurance

6 Model-Based Approach Predicts health insurance coverage using one or more variables correlated with health insurance coverage Example: correlation between state unemployment and uninsurance and applying this at local level

7 National Model-Based Estimates Small-Area Estimation Census and AHRQ are both working on sophisticated models to provide state and local area estimates –CPS: Uninsurance –MEPS-IC: Employment offer and take up rates

8 Approach Principal Strength Principal Weakness Direct Estimation- New Survey PrecisionCost Proxy Measure CostBias Model-Based Predictive Accuracy Complexity Overview of Approaches for Estimating Number of Uninsured At the Local Level

9 University Avenue, Suite 345 Minneapolis Minnesota (612) Principal Investigator: Lynn Blewett, Ph.D. Co-Principal Investigator: Kathleen Call, Ph.D. Center Director: Kelli Johnson, M.B.A. Senior Research Associate: Timothy Beebe, Ph.D. Research Associate: Michael Davern, Ph.D. Contact Information


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