Abstract
In 2004, the US President launched an initiative to make healthcare medical records available electronically [27]. This initiative gives researchers an opportunity to study and mine healthcare data across hospitals, pharmacies, and physicians in order to improve the quality of care. Physicians can make better informed decisions regarding care of patients if physicians have proper understanding of patient journeys. In addition, physician healthcare decisions are influenced by their social networks. In this paper, we find patterns among patient journeys for pain medications from sickness to recovery or death. Next, we combine social network analysis and diffusion of innovation theory to analyze the diffusion patterns among physicians prescribing pain medications. Finally, we suggest an interactive visualization interface for visualizing demographic distribution of patients. The main implication of this research is a better understanding of patient journeys via data-mining and visualizations; and, improved decision-making by physicians in treating patients.
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Kaushik, S., Choudhury, A., Mallik, K., Moid, A., Dutt, V. (2016). Applying Data Mining to Healthcare: A Study of Social Network of Physicians and Patient Journeys. In: Perner, P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2016. Lecture Notes in Computer Science(), vol 9729. Springer, Cham. https://doi.org/10.1007/978-3-319-41920-6_47
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DOI: https://doi.org/10.1007/978-3-319-41920-6_47
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