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GIS Based Health Information Management through LETL, Multi Criteria Query, Analysis, Visualization

GIS Based Health Information Management through LETL, Multi Criteria Query, Analysis, Visualization

Sunitha Abburu
Copyright: © 2021 |Pages: 19
ISBN13: 9781799889601|ISBN10: 1799889602|EISBN13: 9781799889618
DOI: 10.4018/978-1-7998-8960-1.ch019
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MLA

Abburu, Sunitha. "GIS Based Health Information Management through LETL, Multi Criteria Query, Analysis, Visualization." Research Anthology on Public Health Services, Policies, and Education, edited by Information Resources Management Association, IGI Global, 2021, pp. 433-451. https://doi.org/10.4018/978-1-7998-8960-1.ch019

APA

Abburu, S. (2021). GIS Based Health Information Management through LETL, Multi Criteria Query, Analysis, Visualization. In I. Management Association (Ed.), Research Anthology on Public Health Services, Policies, and Education (pp. 433-451). IGI Global. https://doi.org/10.4018/978-1-7998-8960-1.ch019

Chicago

Abburu, Sunitha. "GIS Based Health Information Management through LETL, Multi Criteria Query, Analysis, Visualization." In Research Anthology on Public Health Services, Policies, and Education, edited by Information Resources Management Association, 433-451. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-8960-1.ch019

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Abstract

For effective decision making in public health information management(HIM) system, health information availability, accessibility, prompt exchange, GIS linkage, spatiotemporal analysis of diseases is crucial. Lack of cost-effective technical support and information gaps are the main obstacles in HIM. This article defines a generic conceptual process framework for effective HIM that provides cost-effective, portable, easy to use solution. The solution incorporates GIS, Mobile technology, information management concepts, ICD-10 codes, WHO and mHealth standards. The current research is implemented as an android application that facilitates: 1) Patient disease data collection, geospatial mapping of disease data and accumulate a centralized server 2) LETL that supports bulk disease data upload 3) Addresses syntactic and semantic heterogeneity in health data 4) A strong multi-criteria query engine, visualization and spatiotemporal analysis of diseases are designed with a global perspective to be used across the globe.

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