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Wiley InterScience | |||||||||||||||||||||
  Health Services ResearchVolume 43 Issue 1p2, Pages 419 - 434 Published Online: 20 Dec 2007 © 2010 Health Research and Educational Trust Published on behalf of Health Research and Educational Trust in cooperation with AcademyHealth.
Abstract | References | Full Text: HTML, PDF (Size: 114K) | Related Articles | Citation Tracking  Crowd-Out in the State Children's Health Insurance Program (SCHIP): Incidence, Enrollee Characteristics and Experiences, and Potential Impact on New York's SCHIP Address correspondence to Laura P. Shone, Dr.P.H., M.S.W., Assistant Professor of Pediatrics and Clinical Nursing, Department of Pediatrics, School of Nursing, and the Robert J. Haggerty Health Services Research Laboratories, University of Rochester School of Medicine and Dentistry, 601 Elmwood Avenue, Box 777, Rochester, NY. Paula M. Lantz, Ph.D., M.S., Professor and Chair, is with the Department of Health Management and Policy, Faculty Associate, Institute for Social Research, University of Michigan, Ann Arbor, MI. Andrew W. Dick, Ph.D., Senior Economist, is with the RAND Corporation, Pittsburgh, PA. Michael E. Chernew, Ph.D., Professor, Harvard Medical School, is with the Department of Health Care Policy, Boston, MA. Peter G. Szilagyi, M.D., M.P.H., Chief, Division of General, Pediatrics, Professor of Pediatrics, is with the Department of Pediatrics and Strong Children's Research Center, Department of Community and Preventive Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY. Copyright © 2007 Health Research and Educational Trust KEYWORDS waiting periods • crowd-out • substitution • uninsured children • children's health insurance • state children's health insurance program • SCHIP ABSTRACTBackground. The extent to which the State Children's Health Insurance Program (SCHIP) crowds our private insurance is poorly understood. Objective. To assess the incidence of crowd-out and enrollee characteristics associated with crowd-out. Data. Parent telephone survey for 2,644 children after enrollment in NY SCHIP. Measures and Analyses. Crowd-out is measured based on enrollee reports of coverage (and loss of coverage) before SCHIP. Multivariate logistic regression is used to relate crowd-out to enrollee characteristics. Principal Findings. Only 7.1 percent of SCHIP enrollees dropped private coverage ≤6 months before SCHIP, suggesting relatively modest crowd-out. Crowd-out was associated with some enrollee traits including income, but not with health status. Implications. Most movement from private to public insurance in NY was not crowd-out. Under current program structure in NY, crowd-out concerns should not dampen enthusiasm for SCHIP. | 
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