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Spatial and multidimensional visualization of Indonesia's village health statistics

BACKGROUND: A community health assessment (CHA) is used to identify and address health issues in a given population. Effective CHA requires timely and comprehensive information from a wide variety of sources, such as: socio-economic data, disease surveillance, healthcare utilization, environmental d...

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Autores principales: Parmanto, Bambang, Paramita, Maria V, Sugiantara, Wayan, Pramana, Gede, Scotch, Matthew, Burke, Donald S
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2494543/
https://www.ncbi.nlm.nih.gov/pubmed/18544174
http://dx.doi.org/10.1186/1476-072X-7-30
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author Parmanto, Bambang
Paramita, Maria V
Sugiantara, Wayan
Pramana, Gede
Scotch, Matthew
Burke, Donald S
author_facet Parmanto, Bambang
Paramita, Maria V
Sugiantara, Wayan
Pramana, Gede
Scotch, Matthew
Burke, Donald S
author_sort Parmanto, Bambang
collection PubMed
description BACKGROUND: A community health assessment (CHA) is used to identify and address health issues in a given population. Effective CHA requires timely and comprehensive information from a wide variety of sources, such as: socio-economic data, disease surveillance, healthcare utilization, environmental data, and health resource allocation. Indonesia is a developing country with 235 million inhabitants over 13,000 islands. There are significant barriers to conducting CHA in developing countries like Indonesia, such as the high cost of computing resources and the lack of computing skills necessary to support such an assessment. At the University of Pittsburgh, we have developed the Spatial OLAP (On-Line Analytical Processing) Visualization and Analysis Tool (SOVAT) for performing CHA. SOVAT combines Geographic Information System (GIS) technology along with an advanced multidimensional data warehouse structure to facilitate analysis of large, disparate health, environmental, population, and spatial data. The objective of this paper is to demonstrate the potential of SOVAT for facilitating CHA among developing countries by using health, population, healthcare resources, and spatial data from Indonesia for use in two CHA cases studies. RESULTS: Bureau of Statistics administered data sets from the Indonesian Census, and the Indonesian village statistics, were used in the case studies. The data consisted of: healthcare resources (number of healthcare professionals and facilities), population (census), morbidity and mortality, and spatial (GIS-formatted) information. The data was formatted, combined, and populated into SOVAT for CHA use. Case study 1 involves the distribution of healthcare professionals in Indonesia, while case study 2 involves malaria mortality. Screen shots are shown for both cases. The results for the CHA were retrieved in seconds and presented through the geospatial and numerical SOVAT interface. CONCLUSION: The case studies show the potential of spatial and multidimensional analysis using SOVAT for community health assessment in developing countries. Since SOVAT is based primarily on open-source components and can be deployed using small personal computers, it is cost-effective for developing countries. Also, combining the strength in analysis and the ease of use makes tools like SOVAT ideal for healthcare professionals without extensive computer skills.
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spelling pubmed-24945432008-08-02 Spatial and multidimensional visualization of Indonesia's village health statistics Parmanto, Bambang Paramita, Maria V Sugiantara, Wayan Pramana, Gede Scotch, Matthew Burke, Donald S Int J Health Geogr Research BACKGROUND: A community health assessment (CHA) is used to identify and address health issues in a given population. Effective CHA requires timely and comprehensive information from a wide variety of sources, such as: socio-economic data, disease surveillance, healthcare utilization, environmental data, and health resource allocation. Indonesia is a developing country with 235 million inhabitants over 13,000 islands. There are significant barriers to conducting CHA in developing countries like Indonesia, such as the high cost of computing resources and the lack of computing skills necessary to support such an assessment. At the University of Pittsburgh, we have developed the Spatial OLAP (On-Line Analytical Processing) Visualization and Analysis Tool (SOVAT) for performing CHA. SOVAT combines Geographic Information System (GIS) technology along with an advanced multidimensional data warehouse structure to facilitate analysis of large, disparate health, environmental, population, and spatial data. The objective of this paper is to demonstrate the potential of SOVAT for facilitating CHA among developing countries by using health, population, healthcare resources, and spatial data from Indonesia for use in two CHA cases studies. RESULTS: Bureau of Statistics administered data sets from the Indonesian Census, and the Indonesian village statistics, were used in the case studies. The data consisted of: healthcare resources (number of healthcare professionals and facilities), population (census), morbidity and mortality, and spatial (GIS-formatted) information. The data was formatted, combined, and populated into SOVAT for CHA use. Case study 1 involves the distribution of healthcare professionals in Indonesia, while case study 2 involves malaria mortality. Screen shots are shown for both cases. The results for the CHA were retrieved in seconds and presented through the geospatial and numerical SOVAT interface. CONCLUSION: The case studies show the potential of spatial and multidimensional analysis using SOVAT for community health assessment in developing countries. Since SOVAT is based primarily on open-source components and can be deployed using small personal computers, it is cost-effective for developing countries. Also, combining the strength in analysis and the ease of use makes tools like SOVAT ideal for healthcare professionals without extensive computer skills. BioMed Central 2008-06-11 /pmc/articles/PMC2494543/ /pubmed/18544174 http://dx.doi.org/10.1186/1476-072X-7-30 Text en Copyright © 2008 Parmanto et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Parmanto, Bambang
Paramita, Maria V
Sugiantara, Wayan
Pramana, Gede
Scotch, Matthew
Burke, Donald S
Spatial and multidimensional visualization of Indonesia's village health statistics
title Spatial and multidimensional visualization of Indonesia's village health statistics
title_full Spatial and multidimensional visualization of Indonesia's village health statistics
title_fullStr Spatial and multidimensional visualization of Indonesia's village health statistics
title_full_unstemmed Spatial and multidimensional visualization of Indonesia's village health statistics
title_short Spatial and multidimensional visualization of Indonesia's village health statistics
title_sort spatial and multidimensional visualization of indonesia's village health statistics
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2494543/
https://www.ncbi.nlm.nih.gov/pubmed/18544174
http://dx.doi.org/10.1186/1476-072X-7-30
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