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Wiley InterScience | |||||||||||||||||||||
  Health Services ResearchVolume 42 Issue 6p1, Pages 2109 - 2119 Published Online: 7 Jun 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: 91K) | Supporting Information | Related Articles | Citation Tracking  Using Performance Data to Identify Preferred Hospitals Address correspondence to Meredith B. Rosenthal, Ph.D., Department of Health Policy and Management, Harvard School of Public Health, 677 Huntington Avenue, Room 405, Boston, MA 02115. Mary Beth Landrum, Ph.D., Ellen Meara, Ph.D., and Haiden A. Huskamp, Ph.D., are with the Department of Health Care Policy, Harvard Medical School, Boston, MA. Rena M. Conti, Ph.D., is with the Department of Pediatrics, Institute for Molecular Pediatric Sciences, CheSS, University of Chicago, Chicago, IL. Nancy L. Keating, M.D., M.P.H., is with the Division of General Internal Medicine, Brigham and Women's Hospital and the Department of Health Care Policy, Harvard Medical School, Boston, MA. Copyright © 2007 Health Research and Educational Trust KEYWORDS Quality improvement • report cards • hospitals • referral networks ABSTRACTObjective. To explore the implications of current approaches used by health plans and purchasers to identify preferred hospitals for tiered networks using cost and quality information. Data Sources/Study Setting. 2002 secondary data from WebMD Quality Services on hospital quality and costs in five markets (Boston, Miami, Phoenix, Seattle, and Syracuse). Study Design. We compared four alternative tiering strategies that combine information on quality and cost to designate "preferred" (defined as ranking in the top quartile) hospitals. Within each market we identified the sets of hospitals designated preferred according to each strategy and examined the overlap in these sets across strategies. Principal Findings. Compared with identifying preferred hospitals based on quality scores only, we found little overlap with the sets of hospitals that would be preferred based on cost scores only, cost scores after applying minimal quality standards, and an equally weighted quality and cost measure. The last two approaches, commonly used and intuitively appealing strategies to identify high-value hospitals, led to substantially different results. Conclusions. The lack of agreement among alternative strategies to combine cost and quality data for ranking hospitals suggests the need for clear prioritization by payers and the application of more rigorous methods to identify high-value hospitals. | 
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