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Geospatial collective intelligence for health planning: A case study for screening tests in the city of Esmeraldas, Ecuador

Abstract:

Health planning via intelligent system developments is used to strengthen health care access, focusing on rural areas and underserved populations. In this paper, the authors identify, through a geospatial collective intelligence approach, suitable areas for the allocation of equipment, supplies, and services of health-screening tests for pregnant women in the city of Esmeraldas, Ecuador, with the objective of improving the territorial distribution of health services in Ecuador. The exercise was hosted with various interdisciplinary specialists in HIV from the Ministry of Public Health of Ecuador to determine by anonymous consensus the appropriate areas. The experts were provided with a software tool including features of GDSS and SDSS, from which automation provides the incorporation of the spatial version of the Delphi method in the location the location of health services. The results show that this approach had a high level of participation and feedback, which allowed obtaining the expected geoconsensus level, including high relevance and adequacy, with the proposed approach. This study provides empirical evidence on how the use of an interdisciplinary group of experts made it possible to determine a geoconsensus to allocate equipment in order to expand the coverage of screening tests of HIV in pregnant women in the city of Esmeraldas, Ecuador.