Building A Health Care Decision Support System For Developing Nations

Developing countries are using technology to modernize their industries

, and the healthcare industry is no exception. Their governments, healthcare ministries, and public health officials are utilizing IT solutions to improve health outcomes. International Health and Human Services (HHS) organizations such as the World Health Organization, the International Red Cross, and U.S. agencies such as USAID are assisting them by:Providing resources that help them improve care by strengthening their healthcare-related infrastructures Providing them with expertise in the fields of medicine and disease management Utilizing technologies to drive important healthcare-related decisions for improving healthcare outcomes Some of the HHS organizations are utilizing technology to improve program effectiveness and to audit their own work in the field. One such organization is utilizing a cutting-edge semantic technology Decision Support System (DSS) to determine potential healthcare issues in a developing country and to also measure the impact of their disease control initiatives. This paper describes the challenges and opportunities in building a Decision Support System for developing nations. It also outlines how such nations are blending high technology products with their infrastructures (or lack thereof in various places) to achieve high-end technical solutions that will meet each country"s needs.Product DescriptionTerraframe, a software company based in Colorado, USA developed an ontology-based DSS for a large international HHS organization. It is a semantic technologies-based platform with an integrated Geographic Information System (GIS) that is being used for disease management-related decision making in developing nations. Its initial release was developed for a prevalent disease (malaria) in an African country. However, it is currently being expanded to address numerous diseases in multiple countries. The system is used to determine the disease footprint in a region so that remedial initiatives can be undertaken by the local public health officials, both proactively and reactively. The HHS also utilizes the product as an audit tool to determine an initiative"s effectiveness and to refine the subsequent iterations of the program based on prior results. The disease control initiatives include a wide range of measures such as the use of insecticide sprays.The DSS uses ontological principles (semantic technology) to model geographic, entomological, and insecticidal nomenclature. Standardization of insect related terminology allows data from multiple organizations to be effectively combined and queried.Additionally, since terms have hierarchical relationships, the technology allows for automatic categorization and grouping of related data. As new terms are added, dynamic queries automatically include them. This provides the DSS with a high degree of flexibility, as terms and relationships between terms can change and adapt dynamically in the field to accommodate new requirements. Furthermore, the geographic ontology standardizes terms for geographic features. This ensures data interoperability and allows for the GIS system to work, even in cases where the exact longitude and latitude of a data point is not known. The DSS uses GIS to capture, store, and analyze data associated with geographic locations in order to generate maps as a visual tool. A map consists of one or more layers, with each layer defined by a query created in the DSS. The layers can be overlaid and color-coded into meaningful representations of relationships and correlations between the data and geographic locations. These custom-generated maps greatly assist public health officials in making informed decisions regarding disease control. The developed product is capable of providing reports and query results using local data alone or data aggregated across geographic and governmental hierarchies. For example, an end user can query the system and utilize data from healthcare facilities at a village, city, district, state, or regional level""as well as a countrywide level. The international health organization referenced above expects the DSS data to be collected and utilized at all levels of the African nation.by: JP Batra

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