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An OLAP-GIS System for Numerical-Spatial Problem Solving in Community Health Assessment Analysis

Scotch, Matthew (2006) An OLAP-GIS System for Numerical-Spatial Problem Solving in Community Health Assessment Analysis. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Community health assessment (CHA) professionals who use information technology need a complete system that is capable of supporting numerical-spatial problem solving. On-Line Analytical Processing (OLAP) is a multidimensional data warehouse technique that is commonly used as a decision support system in standard industry. Coupling OLAP with Geospatial Information System (GIS) offers the potential for a very powerful system. For this work, OLAP and GIS were combined to develop the Spatial OLAP Visualization and Analysis Tool (SOVAT) for numerical-spatial problem solving. In addition to the development of this system, this dissertation describes three studies in relation to this work: a usability study, a CHA survey, and a summative evaluation.The purpose of the usability study was to identify human-computer interaction issues. Fifteen participants took part in the study. Three participants per round used the system to complete typical numerical-spatial tasks. Objective and subjective results were analyzed after each round and system modifications were implemented. The result of this study was a novel OLAP-GIS system streamlined for the purposes of numerical-spatial problem solving.The online CHA survey aimed to identify the information technology currently used for numerical-spatial problem solving. The survey was sent to CHA professionals and allowed for them to record the individual technologies they used during specific steps of a numerical-spatial routine. In total, 27 participants completed the survey. Results favored SPSS for numerical-related steps and GIS for spatial-related steps.Next, a summative within-subjects crossover design compared SOVAT to the combined use of SPSS and GIS (termed SPSS-GIS) for numerical-spatial problem solving. Twelve individuals from the health sciences at the University of Pittsburgh participated. Half were randomly selected to use SOVAT first, while the other half used SPSS-GIS first. In the second session, they used the alternate application. Objective and subjective results favored SOVAT over SPSS-GIS. Inferential statistics were analyzed using linear mixed model analysis. At the .01 level, SOVAT was statistically significant from SPSS-GIS for satisfaction and time (p < .002).The results demonstrate the potential for OLAP-GIS in CHA analysis. Future work will explore the impact of an OLAP-GIS system in other areas of public health.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairParmanto, Bambangparmanto@pitt.eduPARMANTO
Committee MemberGadd, Cynthia
Committee MemberSharma, Ravi Krks1946@pitt.eduRKS1946
Committee MemberMonaco,
Committee MemberWatzlaf, Valerievalgeo@pitt.eduVALGEO
Date: 19 April 2006
Date Type: Completion
Defense Date: 5 April 2006
Approval Date: 19 April 2006
Submission Date: 11 April 2006
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: School of Medicine > Biomedical Informatics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: community health assessment; GIS; numerical-spatial problem solving; decision support systems; OLAP
Other ID:, etd-04112006-095019
Date Deposited: 10 Nov 2011 19:35
Last Modified: 15 Nov 2016 13:39


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