Linking Heterogeneous Health Data Sources in Brazil Centered on Drug Leaflet Processing
Resumo
Health Information Systems often include a medication Recommendation module that helps doctors find medications based on symptoms. Most such modules rely on simple AI engines, fed by rules that correlate symptoms, diseases and medications. This, however, presents research and practical problems - e.g., some of the medications may no longer be commercially available, or their components may have been updated. Moreover, studies conducted to design such modules are based on corpora and databases in the English language. This hinders an adaptation to the Brazilian context, not only because of the language, but also due to the lack of authoritative integrated bases. To help solve these issues, we have designed a framework based on automatically extracting and linking information from all drug leaflets of approved medications in Brazil to feed recommendation systems. We processed and linked heterogeneous official data sources of the Ministry of Health, symptoms and diseases. The ongoing implementation, described here, created an ontology from the extracted data to enable linkage and identified quality problems in official data.
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