1 / 28

What Role Does SCHIP Play in the Patchwork Insurance System for Children?

What Role Does SCHIP Play in the Patchwork Insurance System for Children?. Andrew W. Dick PhD 1 R. Andrew Allison PhD 2 Peter G. Szilagyi MD, MPH 3,1 Betsy Shenkman PhD 4. 1 Dept. of Pediatrics, University of Rochester 2 Kansas Health Institute

brielle-schmidt
Download Presentation

What Role Does SCHIP Play in the Patchwork Insurance System for Children?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. What Role Does SCHIP Play in the Patchwork Insurance System for Children? Andrew W. Dick PhD1 R. Andrew Allison PhD2 Peter G. Szilagyi MD, MPH3,1 Betsy Shenkman PhD4 1Dept. of Pediatrics, University of Rochester 2 Kansas Health Institute 3Dept. Of Community & Preventive Medicine, University of Rochester 4Institute for Child Health Policy and Dept of Pediatrics, University of Florida

  2. Background - SCHIP State Children’s Health Insurance Program • BBA of 1997 established SCHIP, providing $40 billion for block grants to states (10 years) • Provides a mechanism for insuring children who fall in the gap between Medicaid and private insurance • Provides wide latitude for states in designing and changing enrollment and eligibility policies

  3. Study Objectives Determine how SCHIP fits into the patchwork system • Describe SCHIP-enrollment patterns • Duration of enrollment, insurance prior to and following enrollment, and their relationships. • Describe differences in these patterns by subgroups • Race/ethnicity, special health care needs, poverty • Relationship between enrollment patterns and health systems access and use measures

  4. SCHIP Policies in Three States • Kansas (HealthWave, 1999) • 2001 enrollment = 34,241 • Florida (Healthy Kids, 1990) • 2001 enrollment = 298,705 • New York (Child Health Plus, 1991) • 2001 enrollment = 590,000 (18% of US)

  5. SCHIP Policies in Three States

  6. Study Design • Surveys: telephone interviews at • T1 : pre-SCHIP access/use, baseline SES • 3 to 6 months after enrollment about year before enrollment • T2 : during-SCHIP access/use, post-SCHIP insurance status • 13 to 16 months after enrollment about year after enrollment • Administrative data: monthly SCHIP-enrollment status and (KS and FL only) Medicaid enrollment status

  7. Subjects: (New Enrollees 7/00-3/01) • New York: • 2,290 completed T1 and T2 surveys • Florida: • 944 completed T1 and T2 surveys • Kansas: • 434 completed T1 and T2 surveys

  8. Measures • Access: Usual Source of Care (USC), type of USC, Unmet needs • Use of care: Any, preventive, acute, specialty • Pre-SCHIP Insurance: • Within the 12 months prior to SCHIP -- Medicaid, private • Ever insured prior to the 12 months before SCHIP enrollment • Never insured • Post-SCHIP Insurance: • Insurance status in month 13 -- Public (SCHIP, Medicaid), private, uninsured • Insurance Status immediately following SCHIP-disenrollment -- Public, private, uninsured

  9. Analyses: Enrollment Duration • Kaplan-Meier survivor functions • by prior insurance and by NY regions (9/11) • Multivariate logistic regressions • probability of surviving at least 10 months • probability of surviving at least 13 months given at least 10 months

  10. Analyses: Insurance Disposition • Multivariate multinomial logistic regression • Estimate insurance status immediately following SCHIP-disenrollment • Multivariate controls include: • SES • prior insurance • pre-SCHIP access and use • during-SCHIP access and use (when appropriate)

  11. Length of SCHIP Enrollment • By race • By income • By prior insurance • By CSHCN status • By use

  12. Insurance Status Following Disenrollment from SCHIP By duration and • By prior insurance • By CSHCN status • By access and use during SCHIP

  13. Conclusions - Recertification • Confirms and strengthens previous finding about recertification • No difference in exit rates in Florida (quantity or correlates) around recertification • Large increases in disenrollment rates around recertification in New York and Kansas • Disenrollment process differed in months 1 - 9 and 10 - 12 by income, CSHCN status and prior use • Very large differences by NY regions, consistent with 9/11 change.

  14. Conclusions – Length of Enrollment • No notable differences in length of enrollment by prior insurance status • No evidence of racial/ethnic differences except for blacks in Florida

  15. Conclusions – Insurance Status Following SCHIP Disenrollment • Children who disenrolled around active recertification were much more likely to become uninsured. • Pre-SCHIP insurance is a predictor of post-SCHIP insurance • SCHIP is not serving as a pathway to private insurance • No evidence that during SCHIP use and unmet needs affect insurance status after disenrollment.

  16. Conclusions - CSHCN • CSHCN could be at greater risk of losing insurance. • disenroll more quickly (esp. around recert.). • more likely to become uninsured after SCHIP.

  17. Limitations Limitations: • Internal Validity • Self-report • large conflicts between self-reported SCHIP-enrollment status and administrative data • Longitudinal survey response rates • KS: 35 % (T1 = 60%, T2=58%) • FL: 30 % (T1 = 60%, T2=50%) • NY: 55% (T1 = 64%, T2=87%) • External Validity: • Three states that may not be representative of many other states.

  18. CHIRITM Funders • Agency for Healthcare Research and Quality (AHRQ) • The David and Lucile Packard Foundation • Health Resources and Services Administration

More Related