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Supporting Physicians in the Detection of the Interactions between Treatments of Co-Morbid Patients

Supporting Physicians in the Detection of the Interactions between Treatments of Co-Morbid Patients

Luca Piovesan, Gianpaolo Molino, Paolo Terenziani
Copyright: © 2015 |Pages: 29
ISBN13: 9781466663169|ISBN10: 1466663162|EISBN13: 9781466663176
DOI: 10.4018/978-1-4666-6316-9.ch009
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MLA

Piovesan, Luca, et al. "Supporting Physicians in the Detection of the Interactions between Treatments of Co-Morbid Patients." Healthcare Informatics and Analytics: Emerging Issues and Trends, edited by Madjid Tavana, et al., IGI Global, 2015, pp. 165-193. https://doi.org/10.4018/978-1-4666-6316-9.ch009

APA

Piovesan, L., Molino, G., & Terenziani, P. (2015). Supporting Physicians in the Detection of the Interactions between Treatments of Co-Morbid Patients. In M. Tavana, A. Ghapanchi, & A. Talaei-Khoei (Eds.), Healthcare Informatics and Analytics: Emerging Issues and Trends (pp. 165-193). IGI Global. https://doi.org/10.4018/978-1-4666-6316-9.ch009

Chicago

Piovesan, Luca, Gianpaolo Molino, and Paolo Terenziani. "Supporting Physicians in the Detection of the Interactions between Treatments of Co-Morbid Patients." In Healthcare Informatics and Analytics: Emerging Issues and Trends, edited by Madjid Tavana, Amir Hossein Ghapanchi, and Amir Talaei-Khoei, 165-193. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-6316-9.ch009

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Abstract

The treatment of patients affected by multiple diseases (comorbid patients) is one of the main challenges for modern healthcare. Clinical practice guidelines are widely used to support physicians, providing them evidence-based information of interventions, but only on individual pathologies. This sets up the urgent need of developing methodologies to support physicians in the detection of interactions between guidelines, to help them in the treatment of comorbid patients. In this chapter, the authors identify different levels of abstractions in the analysis of interactions, based on both the hierarchical organization of clinical guidelines (in which composite actions are refined into their components) and the hierarchy of drug categories. They then propose a general methodology (data/knowledge structures and reasoning algorithms operating on them) supporting user-driven and flexible interaction detection over multiple levels of abstraction.

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