Using Cluster Analysis for Medical Resource Decision Making

David Dilts, Joseph Khamalah, Ann Plotkin

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


Escalating costs of health care delivery have in the recent past often made the health care industry investigate, adapt, and apply those management techniques relating to budgeting, resource control, and forecasting that have long been used in the manufacturing sector. A strategy that has contributed much in this direction is the definition and classification of a hospital's output into “products” or groups of patients that impose similar resource or cost demands on the hospital. Existing classification schemes have frequently employed cluster analysis in generating these groupings. Unfortunately, the myriad articles and books on clustering and classification contain few formalized selection methodologies for choosing a technique for solving a particular problem, hence they often leave the novice investigator at a loss. This paper reviews the literature on clustering, particularly as it has been applied in the medical resource-utilization domain, addresses the critical choices facing an investigator in the medical field using cluster analysis, and offers suggestions (using the example of clustering low-vision patients) for how such choices can be made. Key words: cluster analysis decisions; resource classification schemes; clustering methodology.

Original languageEnglish (US)
Pages (from-to)333-346
Number of pages14
JournalMedical Decision Making
Issue number4
StatePublished - Oct 1995
Externally publishedYes

ASJC Scopus subject areas

  • Health Policy


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