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Churning: Children’s Coverage Discontinuity and Its Consequences in Kentucky Julia F. Costich and Svetla Slavova College of Public Health University of.

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Presentation on theme: "Churning: Children’s Coverage Discontinuity and Its Consequences in Kentucky Julia F. Costich and Svetla Slavova College of Public Health University of."— Presentation transcript:

1 Churning: Children’s Coverage Discontinuity and Its Consequences in Kentucky Julia F. Costich and Svetla Slavova College of Public Health University of Kentucky

2 What we know about discontinuity in children’s coverage NY: half lost coverage in a year despite most remaining technically eligible (Lipson 2003) 12 states: less than half timely renewed (Hill 2003) 4 states: half lapsed at renewal but one-fourth back in 2 months (Dick 2002) 7 states: two-thirds of disenrolled ineligible for SCHIP (but Medicaid?) (Riley 2002) Kansas: procedural and computer problems often at fault (Allison 2003)

3 Kentucky Children’s Health Insurance Program (KCHIP) Medicaid expansion to 150% FPL Look-alike to 200% FPL Administered by Dept. for Medicaid Services Eligibility determination by same agency as cash assistance, food stamps, etc. Enrollment stable at ~50,000 children Compare Medicaid at ~321,000

4 KCHIP Policy Changes 1998: Mail-in application, in-person renewal 7/1/2000: Mail-in renewal with pre-populated form and self-declaration of income 6/1/2001: Return to in-person interview for renewal 7/1/2002: Mailed renewal reinstated; return to in-person interview for initial application Confusion among caseworkers and families

5 Percentage of All Children Enrolled in KCHIP or Medicaid, SFY 2003 Data source: Kentucky Dept. for Medicaid Services Adair Allen Anderson Ballard Barren Bath Bell Boone Bourbon Boyd Boyle Bracken Breathitt Breckinridge Bullitt Butler Caldwell Calloway Campbell Carlisle Carrll Carter Casey Christian Clark Clay Clinton Crittenden Cumberland Daviess Edmonson Elliott Estill Fayette Fleming Floyd Franklin Fulton Gallatin Garrard Grant Graves Grayson Green Greenup Hancock Hardin Harlan Harrison Hart Henderson Henry Hickman Hopkins Jackson Jefferson Jessamine Johnson Kenton Knott Knox Larue Laurel Lawrence Lee LeslieLetcher Lewis Lincoln Livingston Logan Lyon Mccracken Mccreary Mclean Madison Magoffin Marion Marshall Martin Mason Meade Menifee Mercer Metcalfe Monroe Montgomery Morgan Muhlenberg Nelson Nicholas Ohio Oldham Owen Owsley Pendleton Perry Pike Powell Pulaski Robertson Rockcastle Rowan Russell Scott Shelby Simpson Spencer Taylor Todd Trigg Trimble Union Warren Washington Wayne Webster Whitley Wolfe Woodford Prepared by: Julia F. Costich, College of Public Health Under 30% 30-39% 40-49% 50-59% Over 60%

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8 Problems with added eligibility office workload Source: Family Resource & Youth Service Center Staff Survey Long waits in understaffed urban offices Refusal to provide scheduled appointments Overloaded phone system; unanswered voice mails Unexpected requests for additional documentation Inappropriate denial based on confusion Staff reporting suspect immigration status Failure or inability to accommodate working families’ schedules

9 Churning effect 46% did not renew on time New applications were 52% of total enrollment Yet total enrollment grew by only 4% Millions of wasted state dollars Risk of gaps in coverage Wide variation across the state Timely renewal highest in Medicaid expansion

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11 Data sources Open records request to Medicaid for data by county, month and program –“Requires” staff to provide data Data limitations –Not individual-level –“New” applications may be internal to system when renewal deadline is missed by staff 3 categories –Number of children up for renewal –Number timely renewed –Number of new applications approved

12 Methodology Percentage of all children (Census data) enrolled in KCHIP or Medicaid –Critically important to include both because of frequent movement between programs –Failure to account for movement overstates churning Percentage of children eligible for renewal in either program who renewed on time New applications approved as percentage of total enrollment

13 Percentage of Children Enrolled and Percentage of Timely Renewals (R 2 =.44)

14 New Approvals as Percentage of Total and Percentage of Timely Renewals (R 2 =.55)

15 Methodology and statistical findings SAS univariate regression analysis F test found p <.0001 for relationships between –renewal and enrollment –new applications and non-renewal R 2 =.44 and.55 respectively

16 Discussion Low rate of timely renewal similar to other studies’ findings Identified need for pre-termination contact, follow-up –Problem: hiring freezes, state budget deficit Next steps: –Determine whether supportive environment of high- renewal counties can be replicated with outreach workers, volunteers –Advocate for more realistic federal budget allocations

17 Limitations Inability to track individual children Considerable migration among programs Eligibility determination office practice giving rise to spurious new applications Possible delinking issues in information systems Antiquated eligibility determination system may introduce errors


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