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Barriers to SCHIP enrollment: A cross-county study of the State Children's Health Insurance Program in Pennsylvania

Published online by Cambridge University Press:  17 May 2016

Christina M. L. Kelton ,
Miriam Levitt  and
Margaret K. Pasquale
Christina M. L. Kelton
Affiliation:
College of Business Economics Center for Education & Research University of Cincinnati, 3130 Edwards One Cincinnati, OH 45221-0223, USA chris.kelton@uc.edu
Miriam Levitt
Affiliation:
Department of Epidemiology and Community Medicine University of Ottawa ML Health and Social Policy Consulting 502-207 Maclaren Street Ottawa, Ontario K2P OL4 Canada Miriam.Levitt@rogers.com
Margaret K. Pasquale
Affiliation:
Epidemiology & Pharmacoeconomics P & G Pharmaceuticals, Inc. 8700 Mason Montgomery Road Mason, OH 45040-9462, USA pasquale.mk@pg.com
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Abstract

BACKGROUND. Enrollment in the State Children's Health Insurance Program (SCHIP), created under the federal Balanced Budget Act of 1997, had a distressingly slow start and varied substantially county-to-county in many states, including Pennsylvania.

METHODS. We performed a quantitative county-level analysis of barriers to enrollment in Pennsylvania's Children's Health Insurance Program (CHIP) for the year 2000, seven years after it was implemented and three years after federal SCHIP legislation. Using multivariate regression analysis with a county as the unit of observation, we modeled enrollment in SCHIP as a function of accessibility to health care, availability of clinicians, and community economic health.

RESULTS. High clinic density and Medicaid managed-care membership predicted SCHIP enrollment success, while female head-of-household predicted SCHIP enrollment failure. A principal-components factor analysis revealed four underlying barriers to enrollment: accessibility, availability, affordability, and effort.

CONCLUSIONS. The most formidable barriers to SCHIP enrollment success in Pennsylvania were not programmatic; they were correlates of poverty itself.

Type
Research Article
Information
Politics and the Life Sciences , Volume 24 , Issue 1-2 , September 2005 , pp. 22 - 31
Copyright
Copyright © Association for Politics and the Life Sciences 

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References

1. Trafton, S., Shone, L. P., Zwanziger, J., Mukamel, D. B., Dick, A. W., Holl, J. L., Rodewald, L. E., Raubertas, R. F., and Szilagyi, P. G., “Evolution of a Children's Health Insurance Program: Lessons from New York State's Child Health Plus,” Pediatrics, 2000, 105:692–696.CrossRefGoogle Scholar
2. Children's Defense Fund, “Chip Evaluation for Hamilton County,” 1999, Working Paper.Google Scholar
3. Stuber, J. and Kronebusch, K., “Stigma and Other Determinants of Participation in TANF and Medicaid,” Journal of Policy Analysis and Management, 2004, 23:509–530.CrossRefGoogle Scholar
4. Center for Rural Pennsylvania, “Analysis of the Children's Health Insurance Program in Rural Pennsylvania,” 2003.Google Scholar
5. Pennsylvania Insurance Department at http://www.ins.state.pa.us/ins/cwp/.Google Scholar
6. Sasso, A. T. Lo and Buchmueller, T. C., “The Effect of the State Children's Health Insurance Program on Health Insurance Coverage,” Journal of Health Economics, 2004, 23:1059–1082.CrossRefGoogle Scholar
7. Kenney, G. and Haley, J., “Why Aren't More Uninsured Children Enrolled in Medicaid or SCHIP?,” 2001, The Urban Institute Working Paper.Google Scholar
8. Mathematica Policy Research, Inc., “Implementation of the State Children's Health Insurance Program: Momentum is Increasing After a Modest Start. First Annual Report,” 2001, Mathematica Contract Number 500-96-0016 (03).Google Scholar
9. General Accounting Office, “Medicaid and SCHIP: States' Enrollment and Payment Policies Can Affect Children's Access to Care,” 2001.Google Scholar
10. American Academy of Pediatrics Committee on Child Health Financing, “Implementation Principles and Strategies for the State Children's Health Insurance Program,” Pediatrics, 2001, 107:1214–1220.CrossRefGoogle Scholar
11. American Academy of Pediatrics, “SCHIP Evaluation Tool,” 2000, at www.aap.org/research/evaltool.htm.Google Scholar
12. Penchansky, R. and Thomas, J.W., “The Concept of Access: Definition and Relationship to Consumer Satisfaction,” Medical Care, 1981, 19:127–140.CrossRefGoogle Scholar
13. Pearlin, L. I., “Role Strains and Personal Stress,” in Kaplan, Howard B., ed., Psychosocial Stress: Trends in Theory and Research (New York: Academic Press, 1983).Google Scholar
14. Angel, R. J. and Angel, J. L., Painful Inheritance: Health and the New Generation of Fatherless Families (Madison, Wisconsin: The University of Wisconsin Press, 1983).Google Scholar
15. Porter, K. H. and Dupree, A., “Poverty Trends for Families Headed by Working Single Mothers: 1993–1999,” Center on Budget and Policy Priorities Working Paper, 2001.Google Scholar
16. American Academy of Pediatrics, “Medicaid and State Program Eligibility of Uninsured Children Through Age 18, Year 2000 Projections,” 2000, at http://www.aap.org/advocacy/chi2/pa.pdf.Google Scholar
17. The Pennsylvania State Data Center, at http://pasdc.hbg.psu.edu/pasdc/census_2000/Data/SF3/DP1-DP4/PA_counties.html.Google Scholar