Service duplication within urban hospital clusters
Hanh Q Trinh1, James W Begun, Roice D Luke
1Hanh Q. Trinh, PhD, is Associate Professor, Health Care Administration and Informatics, University of Wisconsin-Milwaukee, P.O. Box 413, Milwaukee, Wisconsin. E-mail: hanht@uwm.edu. James W. Begun, PhD, is James A. Hamilton Professor of Healthcare Management, Division of Health Policy and Management, University of Minnesota, Minneapolis. E-mail: begun001@umn.edu. Roice D. Luke, PhD, is Professor Emeritus, Department of Health Administration, Virginia Commonwealth University, P.O. Box 980203, Richmond, Virginia.
Health Care Management Review
|January 30, 2013
Summary
Hospital cluster size impacts service duplication, with larger clusters offering more rationalization opportunities. For-profit hospital systems may lead in optimizing services across their networks.
Area of Science:
- Health Services Research
- Healthcare Management
- Hospital Administration
Background:
- Most U.S. urban multihospital systems cluster member hospitals within the same market area.
- Hospital clustering is often justified by the potential to reduce service duplication among member facilities.
Purpose of the Study:
- To investigate how hospital cluster characteristics influence service duplication.
- To analyze service duplication within 339 hospital clusters in U.S. metropolitan statistical areas and adjacent counties in 2002.
Main Methods:
- Employed ordinary least squares regression analysis.
- Examined the relationship between 1998 cluster characteristics and 2002 duplicated services per member.
Main Results:
- Higher case mix index and broader bed size range correlated with increased service duplication.
- Greater number of members, for-profit ownership, and increased geographic dispersion were associated with lower service duplication.
Conclusions:
- Larger hospital clusters present greater potential for service rationalization.
- For-profit hospital clusters may be early adopters of rationalization strategies and warrant further study.
- Clusters with high case mix, limited geographic spread, and hub-and-spoke designs may face challenges in service reallocation.
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