Qual Health Care 9:238-244 doi:10.1136/qhc.9.4.238
  • Viewpoint

The potential use of decision analysis to support shared decision making in the face of uncertainty: the example of atrial fibrillation and warfarin anticoagulation

  1. A Robinson, research associate in health economics,
  2. R G Thomson, professor of epidemiology and public health ,
  3. A Robinson, R G Thomson, on behalf of the Decision Analysis in Routine Treatments Study (DARTS) team*
  1. Department of Epidemiology and Public Health, School of Health Sciences, Medical School, Newcastle upon Tyne NE2 4HH, UK
  1. Dr A Robinson angela.robinson{at}
  • Accepted 1 August 2000


The quality of patient care is dependent upon the quality of the multitude of decisions that are made daily in clinical practice. Increasingly, modern health care is seeking to pursue better decisions (including an emphasis on evidence-based practice) and to engage patients more in decisions on their care. However, many treatment decisions are made in the face of clinical uncertainty and may be critically dependent upon patient preferences. This has led to attempts to develop decision support tools that enable patients and clinicians to make better decisions. One approach that may be of value is decision analysis, which seeks to create a rational framework for evaluating complex medical decisions and to provide a systematic way of integrating potential outcomes with probabilistic information such as that generated by randomised controlled trials of interventions. This paper describes decision analysis and discusses the potential of this approach with reference to the clinical decision as to whether to treat patients in atrial fibrillation with warfarin to reduce their risk of stroke.

(Quality in Health Care 2000;9:238–244)


  • * The following are also members of the Decision Analysis in Routine Treatments Study (DARTS) team: Martin Eccles, Centre for Health Services Research; Karen Jones, Jane Ling, David Parkin, Mark Sudlow, Department of Epidemiology and Public Health; Philip Lowe, Ian Purves, Sowerby Centre for Health Informatics in Newcastle; and Rosie Stacy, Department of Primary Health Care; School of Health Sciences, University of Newcastle upon Tyne.