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

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Author(s): Joseph M. Woodside (Cleveland State University, USA)and Iftikhar U. Sikder (Cleveland State University, USA)
Copyright: 2010
Pages: 15
Source title: Health Information Systems: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Joel J.P.C. Rodrigues (Senac Faculty of Ceará, Fortaleza-CE, Brazil; Instituto de Telecomunicações, Portugal)
DOI: 10.4018/978-1-60566-988-5.ch119

Keywords: Health Information Systems / Medical Information Science Reference / Medicine & Healthcare

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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.

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

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