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Public Program Sensitivity: Using ROC curves to characterize classification efficiency of State Medicaid Systems

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  • Lisa Frazier

    (John Glenn College of Public Affairs, the Ohio State University)

Abstract

Despite being the largest single source of health care coverage in the US, Medicaid fails to capture all eligible citizens. This is a well-known problem among means-tested programs like Medicaid; discussions of take-up and churning attend to this failure. Cases of fraud in programmatic enrollments represent another classification failure in these systems. Reports on rates of fraud, take-up, and churn rarely acknowledge that such outcomes are ultimately features of the same tradeoff function: the sorting of citizens into benefit groups on the basis of membership to some a priori category. This research elucidates the implicit tradeoffs being made in the Medicaid citizen sorting mechanism by using administrative data to construct ROC curves for each State Medicaid system before and after the passage of the Affordable Care Act.

Suggested Citation

  • Lisa Frazier, 2015. "Public Program Sensitivity: Using ROC curves to characterize classification efficiency of State Medicaid Systems," 2015 Stata Conference 20, Stata Users Group.
  • Handle: RePEc:boc:scon15:20
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