 | The 131st Annual Meeting (November 15-19, 2003) of APHA |
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| The 131st Annual Meeting (November 15-19, 2003) of APHA |
Matthew L. Scotch, MA, Center for Biomedical Informatics, University of Pittsburgh, 200 Lothrop St., Forbes Tower, Suite 8084, Pittsburgh, PA 15213, Bambang Parmanto, PhD, Health Information Management, University of Pittsburgh, 6051 Forbes Tower, Meyran Avenue, Pittsburgh, PA 15260, Ravi K. Sharma, PhD, Behavioral and Community Health Sciences, University of Pittsburgh, 130 DeSoto St., Room 228, Pittsburgh, PA 15261, and Michael Meit, MA, MPH, Center for Rural Health Practice, University of Pittsburgh, Hamsher House, Suite 16, 116 Interstate Parkway, Bradford, PA 16701, 814-362-8656, meit@imap.pitt.edu.
Institutions looking to perform community health assessment projects are realizing the difficulty in storing, managing, retrieving, and analyzing the various types of information needed to properly determine the well-being of specific populations. The Center for Rural Health Practice at the University of Pittsburgh has established a multidimensional health database that contains a culmination of disparate information from various sources such as the Census Bureau, the Pennsylvania Health Care Cost Containment Council (PHC4), and Pennsylvania’s Department of Health, that has served as a tool for a public health assessment of a rural area in Pennsylvania. The database’s architecture contains Online Analytical Processing (OLAP). OLAP allows for rapid queries of multidimensional data enabling powerful and unique analysis. Data from the various sources are formatted into tables in SQL Server 2000 and Oracle 9i. The OLAP engine then takes various predefined dimensions (views) of the different data sets and queries them together creating a multidimensional representation of the data. Thus, Census information can be analyzed in relation to PHC4 hospital utilization data. The database’s easy to use front-end interface allows the public health professional to clearly view graphical and eloquent interpretations of the data. The architecture in our multidimensional database enables the public health evaluator to powerfully analyze vital health and population-based statistics. The Center for Rural Health Practice at the University of Pittsburgh is also looking into expanding this project into an openly accessible on-line tool for users to gain insight into health and population statistics for specific geographic regions of interest.
Learning Objectives:
Presenting author's disclosure statement:
I have a significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.
Relationship: I am the director of the Center for Rural Health Practice, which is responsible for this project.