Characterizing chronic disease and polymedication prescription patterns from electronic health records
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
Population aging in developed countries brings an increased prevalence of chronic disease and of polymedication-patients with several prescribed types of medication. Attention to chronic, polymedicated patients is a priority for its high cost and the associated risks, and tools for analyzing, understanding, and managing this reality are becoming necessary. We describe a prototype of a system for discovering, analyzing, and visualizing the co-occurrence of diagnostics, interventions, and medication prescriptions in a large patient database. The final tool is intended to be used both by health managers and planners and for primary care clinicians in direct contact with patients (for example for detecting unusual disease patterns and incorrect or missing medication). At the core of the analysis module there is a representation of diagnostics and medications as a hypergraph, and the most crucial functionalities rely on hypergraph transversal/variants of association rule discovery methods, with particular emphasis on discovering surprising or alarming combinations. The test database comes from the primary care system in the area of Barcelona for 2013, with over 1.6 million potential patients and almost 20 million diagnostics and prescriptions.
CitationZamora, M., Baradad, M., Amado, E., Cordomí, S., Limón, E., Ribera, J., Arias, M., Gavaldà, R. Characterizing chronic disease and polymedication prescription patterns from electronic health records. A: IEEE International Conference on Data Science and Advanced Analytics. "Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics". Paris: Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 1-9.
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