Decision support system for Warfarin therapy management using Bayesian networks

Date

2013-05-01

Author

Yet, Barbaros
Bastani, Kaveh
Raharjo, Hendry
Lifvergren, Svante
Marsh, William
Bergman, Bo

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Warfarin therapy is known as a complex process because of the variation in the patients' response. Failure to deal with such variation may lead to death as a result of thrombosis or bleeding. The possible sources of variation such as concomitant illnesses and drug interactions have to be investigated by the clinician in order to deal with the variation. This paper describes a decision support system (DSS) using Bayesian networks for assisting clinicians to make better decisions in Warfarin therapy management. The DSS is developed in collaboration with a Swedish hospital group that manages Warfarin therapy for more than 3000 patients. The proposed model can assist the clinician in making dose-adjustment and follow-up interval decisions, investigating variation causes, and evaluating bleeding and thrombosis risks related to therapy. The model is built upon previous findings from medical literature, the knowledge of domain experts, and large dataset of patients.

Subject Keywords

Decision support systems, Anticoagulant therapy, Warfarin therapy, Bayesian networks

URI

https://hdl.handle.net/11511/56978

Collections

Graduate School of Informatics, Article