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Space-Time Cluster Analysis: Application of Healthcare Service Data in Epidemiological Studies

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  • Joseph M. Woodside

    (Cleveland State University, USA)

  • Iftikhar U. Sikder

    (Cleveland State University, USA)

Abstract

Spatial epidemiological approach to healthcare studies provides significant insight in evaluating health intervention and decision making. This article illustrates a space-time cluster analysis using Kulldorff’s Scan Statistics (1999), local indicators of spatial autocorrelation, and local G-statistics involving routine clinical service data as part of a limited data set collected by a Northeast Ohio healthcare organization (Kaiser Foundation Health Plan of Ohio) over a period 1994—2006. The objective is to find excess space and space - time variations of lung cancer and to identify potential monitoring and healthcare management capabilities. The results were compared with earlier research (Tyczynski, & Berkel, 2005); similarities were noted in patient demographics for the targeted study area. The findings also provide evidence that diagnosis data collected as a result of rendered health services can be used in detecting potential disease patterns and/or utilization patterns, with the overall objective of improving health outcomes.

Suggested Citation

  • Joseph M. Woodside & Iftikhar U. Sikder, 2009. "Space-Time Cluster Analysis: Application of Healthcare Service Data in Epidemiological Studies," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 4(4), pages 69-82, October.
    • Handle: RePEc:igg:jhisi0:v:4:y:2009:i:4:p:69-82
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