Parmanto Bambang, Paramita Maria V, Sugiantara Wayan, Pramana Gede, Scotch Matthew, Burke Donald S
Health Information Management, University of Pittsburgh, 6051 Forbes Tower, Pittsburgh, Pennsylvania, USA.
Int J Health Geogr. 2008 Jun 11;7:30. doi: 10.1186/1476-072X-7-30.
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.
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.
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.
社区健康评估（CHA）用于识别和解决特定人群中的健康问题。有效的社区健康评估需要来自各种来源的及时且全面的信息，例如：社会经济数据、疾病监测、医疗保健利用情况、环境数据以及卫生资源分配。印度尼西亚是一个发展中国家，由分布在13000多个岛屿上的2.35亿居民组成。在像印度尼西亚这样的发展中国家进行社区健康评估存在重大障碍，比如计算资源成本高昂以及缺乏支持此类评估所需的计算技能。在匹兹堡大学，我们开发了用于执行社区健康评估的空间联机分析处理（OLAP）可视化与分析工具（SOVAT）。SOVAT将地理信息系统（GIS）技术与先进的多维数据仓库结构相结合，以促进对大量、不同的健康、环境、人口和空间数据的分析。本文的目的是通过使用来自印度尼西亚的健康、人口、医疗保健资源和空间数据，在两个社区健康评估案例研究中展示SOVAT在促进发展中国家社区健康评估方面的潜力。
案例研究使用了印度尼西亚统计局管理的来自印度尼西亚人口普查和印度尼西亚村庄统计的数据集。数据包括：医疗保健资源（医疗专业人员和设施的数量）、人口（人口普查数据）、发病率和死亡率以及空间（GIS格式）信息。这些数据经过格式化、合并，并填充到SOVAT中以供社区健康评估使用。案例研究1涉及印度尼西亚医疗专业人员的分布，而案例研究2涉及疟疾死亡率。两个案例均展示了屏幕截图。社区健康评估的结果在数秒内即可获取，并通过地理空间和数字SOVAT界面呈现。
案例研究表明，使用SOVAT进行空间和多维分析在发展中国家的社区健康评估中具有潜力。由于SOVAT主要基于开源组件，并且可以使用小型个人计算机进行部署，因此对发展中国家来说具有成本效益。此外，分析能力与易用性相结合，使得像SOVAT这样的工具对于没有广泛计算机技能的医疗保健专业人员来说非常理想。
