Decision support system for Warfarin therapy management using Bayesian networks
Journal article, 2013

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.

Decision support systems

Anticoagulant therapy

Warfarin therapy

Bayesian networks

Author

Barbaros Yet

Chalmers, Technology Management and Economics

Kaveh Bastani

Chalmers, Technology Management and Economics

Hendry Raharjo

Chalmers, Technology Management and Economics, Quality Sciences

Svante Lifvergren

Chalmers, Technology Management and Economics, Quality Sciences

William Marsh

Queen Mary University of London

Bo Bergman

Chalmers, Technology Management and Economics, Quality Sciences

Decision Support Systems

0167-9236 (ISSN)

Vol. 55 2 488-498

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Health Care Service and Management, Health Policy and Services and Health Economy

Clinical Medicine

Bioinformatics (Computational Biology)

Roots

Basic sciences

Areas of Advance

Life Science Engineering

DOI

10.1016/j.dss.2012.10.007

More information

Latest update

5/17/2018