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Defining hospital clusters and associated service communities in metropolitan areas

dc.contributor.authorThomas, J. Williamen_US
dc.contributor.authorGriffith, John R.en_US
dc.contributor.authorDurance, Paulen_US
dc.date.accessioned2006-04-07T18:10:23Z
dc.date.available2006-04-07T18:10:23Z
dc.date.issued1981en_US
dc.identifier.citationThomas, J. William, Griffith, John R., Durance, Paul (1981)."Defining hospital clusters and associated service communities in metropolitan areas." Socio-Economic Planning Sciences 15(2): 45-51. <http://hdl.handle.net/2027.42/24492>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V6Y-45GSBG8-M/2/8d383f95b5262f616c35c314f88b32fcen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/24492
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=10250830&dopt=citationen_US
dc.description.abstractAccording to traditional concepts of hospital governance, each institution is considered responsible for the care of a defined community. Evaluation of hospital performance and effective service planning both require that hospitals' service communities be identified. However, in metropolitan regions it is difficult to associate a geographic population with any one hospital because of the wide choice of facilities available to area residents. The service community concept becomes more meaningful in these regions if several hospitals with overlapping geographic communities are defined as a cluster.This paper describes a two-step method for identifying hospital clusters and their associated service communities. The first step involves analysis of patient origin data to identify logical clusters of hospitals. Three algorithms for performing this analysis are presented. In the second step, analytical findings are reviewed by a panel of area planners and hospital experts who, considering additional qualitative factors, determine how the hospitals may be most appropriately grouped. Experience in using this method for hospitals in the seven-county region around Detroit, Michigan suggests that reasonable clusters can be identified, although clusters of central city hospitals are less well-defined than those in the suburban areas.en_US
dc.format.extent834430 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleDefining hospital clusters and associated service communities in metropolitan areasen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelEconomicsen_US
dc.subject.hlbtoplevelBusinessen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Medical Care Organization, School of Public Health, University of Michigan, Ann Arbor, MI 48104, U.S.A.en_US
dc.contributor.affiliationumProgram and Bureau of Hospital Administration, School of Public Health, University of Michigan, Ann Arbor, MI 48104, U.S.A.en_US
dc.contributor.affiliationumProgram and Bureau of Hospital Administration, School of Public Health, University of Michigan, Ann Arbor, MI 48104, U.S.A.en_US
dc.identifier.pmid10250830en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/24492/1/0000768.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0038-0121(81)90048-3en_US
dc.identifier.sourceSocio-Economic Planning Sciencesen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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