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CKF’s Influence on Enrollment and Retention in Public Coverage

CKF’s Influence on Enrollment and Retention in Public Coverage. Academy Health Meeting Christopher Trenholm June 10, 2008. Rigorously Measuring Effects of CKF is HARD. Many Factors Affect Enrollment/Retention Policies can be difficult to measure and isolate

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CKF’s Influence on Enrollment and Retention in Public Coverage

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  1. CKF’s Influence on Enrollment and Retention in Public Coverage Academy Health Meeting Christopher Trenholm June 10, 2008

  2. Rigorously Measuring Effects of CKF is HARD • Many Factors Affect Enrollment/Retention • Policies can be difficult to measure and isolate • Economic conditions can confound policy effects • Socio-demographics have a further influence • Measurement is Often Blunt • Counts of enrollees? • Numbers of kids leaving the programs? • Attribution to CKF is a Further Challenge • Counterfactual is lacking

  3. Analytic Approach: “Two-Step, Mixed Method” • Step 1: Case Studies in Selected States • Identify/isolate promising policies • Assess contribution of CKF • Step 2: Impact Analysis of Identified Policies • Test statistical significance • Measure magnitude of effect (if evident)

  4. Step 1: Case Studies • Focus on 10 States with Well-Implemented CKF Programs, Good Data, & Active Policy Setting • Develop Measures Sensitive to Policy Changes • Enrollment: “New Entries” • Retention: “Cyclers” • Drop insensitive eligibility groups (e.g. SSI) • Examine Trends & Identify Major Changes in Enrollment/Retention • Conduct Site Visit Interviews to Assess Link Between Changes and Policy (and Policy to CKF)

  5. Case Study Illustration: Virginia

  6. Trend By Program Show Links to Major Policy Changes

  7. Step 2: Impact Analysis of Identified Policies • Illustrate with Enrollment Findings • Most Robust Link Revealed by Case Study: Less Local Involvement = More Coverage - Drop face-to-face interview ~ Growth in new entries - Mail-in/No wrong door ~ Growth in new entries - Centralized eligibility ~ Growth in new entries • Most evident/identifiable for Medicaid children • Major variation across the 10 case study states • Important variation within these states

  8. Local Involvement Can Vary Dramatically Across States Most local/county role 1. Face-to-face interview at county office 2. Mail-in application to county office (no face-to-face) 3. “Pass-through”application to state/CPU; local eligibility 4. “Retained” application to state/CPU; centralized eligibility Least local/county role

  9. Estimation Strategy • Outcome: New Entries (Per State Per Quarter; 1999-2006) • Covariates: Time Fixed Effects, State Fixed Effects, Unemployment, Estimated Eligibles • Policy variables • Focal: “local involvement” (categorical) • Sensitivity: joint application, presumptive eligibility, stated income

  10. Findings: Centralization is the Key Policy Step Local Involvement% Change in New Entries 1. Face-to-face interview reference 2. Mail-in app (county); local eligibility -3.2% 3. Pass-through app; local eligibility 4.4% 4. Retained app; state/CPU eligibility 16.0%** ** p-value (of estimated % change) < 0.01

  11. Effect of Centralized Eligibility Persists When Tested With Other Policies ModelPolicy Variables% Change 1. Centralized eligibility 15.7%** Joint application 1.2% 2. Centralized eligibility 15.3%** Presumptive eligibility 4.5% 3. Centralized eligibility 12.8%** Stated income 6.9%* **/* p-value (of estimated % change) < 0.01/0.05

  12. Summary • Two-Step (Mixed Method) Approach Offers Efficient Means to Rigorously Measure Policy Effects on Coverage • Evidence From Enrollment Study Pinpoints Centralization of Eligibility as a Particularly Beneficial Policy • Retention Study Underway

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