Context or Composition: What Explains Variation in SCHIP Disenrollment?

Authors

  • Julie A. Phillips,

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    • Address correspondence to Julie A. Phillips, Ph.D., Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick NJ 08901. Dr. Phillips is also with the Department of Sociology, Rutgers University. Jane E. Miller, Ph.D., is with the Institute for Health, Health Care Policy and Aging Research, Rutgers University, and the Edward J. Bloustein School of Planning and Public Policy, Rutgers University. Joel C. Cantor, Sc.D., is with the Center for State Health Policy, Rutgers University, and the Edward J. Bloustein School of Planning and Public Policy, Rutgers University. Dorothy Gaboda, Ph.D., is with the Center for State Health Policy, Rutgers University.

  • Jane E. Miller,

  • Joel C. Cantor,

  • Dorothy Gaboda


  • This project was funded by the Joint Center for Poverty Research through their HHS Research Development Grants program. This study was conducted in cooperation with the New Jersey Department of Human Services, which provided study data and invaluable advice. Findings were presented at the Annual Meetings of the Population Association of America, Minneapolis, 2003, and of the Academy for Health Services Research and Policy, Washington, DC, June 2002. The authors are solely responsible for the analyses and conclusions herein.

Abstract

Objective. To investigate (1) the relative contributions of family and contextual characteristics to observed variation in disenrollment rates from the State Children's Health Insurance Program (SCHIP), and (2) whether context explains observed family-level patterns.

Data Sources. We use secondary data on 24,628 families enrolled in New Jersey's SCHIP program (NJ KidCare), and county-level data from the Area Resource File, the Census, and the NJ FamilyCare provider roster.

Study Design. Information on family characteristics, SCHIP plan, and dates of enrollment and disenrollment are taken from NJ KidCare administrative records, which provided surveillance data from January 1998 through April 2000.

Data Collection/Analysis. We estimate a multilevel discrete-time-hazards model of SCHIP disenrollment.

Findings. Families enrolled in plans involving cost-sharing, blacks, and those with only one enrolled child have higher than average rates of disenrollment. Disenrollment rates for blacks are lower in counties with a high share of black physicians. These characteristics account for part of the intercounty variation in disenrollment rates; remaining intercounty variation is largely explained by physician density or population density.

Policy Implications. It may be worthwhile to pay special attention to black families and counties with high disenrollment rates to address the reasons for their lower retention. Addressing cultural differences between physician and client and the geographic distribution of medical providers might reduce disenrollment.

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