Paper Info
Title
Space-Time Cluster Analysis: Application Of Healthcare Service Data In Epidemiological Studies
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.
Year
DOI
Venue
2009
10.4018/jhisi.2009071005
INTERNATIONAL JOURNAL OF HEALTHCARE INFORMATION SYSTEMS AND INFORMATICS
Keywords
Field
DocType
Cluster Analysis, Healthcare Service Data, Spatial Autocorrelation, Spatial Data
Health care,Spatial analysis,Data mining,Disease,Epidemiology,Health intervention,Demographics,Health services,Health administration,Medicine
Journal
Volume
Issue
ISSN
4
4
1555-3396
Citations 
PageRank 
References 
3
0.39
2
Authors
2
Name
Order
Citations
PageRank
Joseph M. Woodside174.24
Iftikhar U. Sikder2635.75