OBJECTIVE: To investigate the effect of patients' preferences in the treatment of atrial fibrillation by using individualized decision analysis in which probability and utility assessments are combined into a decision tree. DESIGN: Observational study based on interviews with patients. SETTING: 8 general practices in Avon, England. PARTICIPANTS: 260 randomly selected patients aged 70 to 85 years with atrial fibrillation. MAIN OUTCOME MEASURES: Patients' treatment preferences regarding anticoagulation treatment (warfarin sodium) after individualized decision analysis; comparison of these preferences with treatment guidelines on the basis of comorbidity and absolute risk and compared with current prescription. RESULTS: Of 195 eligible patients, 97 participated in decision making using decision analysis. Among these 97, the decision analysis indicated that 59 (61%; 95% confidence interval, 50%-71%) would prefer anticoagulation treatment, considerably fewer than those who would be recommended treatment according to guidelines. There was marked disagreement between the decision analysis and guideline recommendations (kappa> or =0.25). Of 38 patients whose decision analysis indicated a preference for anticoagulation, 17 (45%) were being prescribed warfarin; on the other hand, 28 (47%) of 59 patients were not being prescribed warfarin, although the results of their decision analysis suggested they wanted to be. CONCLUSIONS: In the context of shared decision making, individualized decision analysis is valuable in a sizable proportion of elderly patients with atrial fibrillation. Taking account of patients' preferences would lead to fewer prescriptions for warfarin than under published recommendations. Decision analysis as a shared decision-making tool should be evaluated in a randomized controlled trial.
OBJECTIVE: To investigate the effect of patients' preferences in the treatment of atrial fibrillation by using individualized decision analysis in which probability and utility assessments are combined into a decision tree. DESIGN: Observational study based on interviews with patients. SETTING: 8 general practices in Avon, England. PARTICIPANTS: 260 randomly selected patients aged 70 to 85 years with atrial fibrillation. MAIN OUTCOME MEASURES: Patients' treatment preferences regarding anticoagulation treatment (warfarin sodium) after individualized decision analysis; comparison of these preferences with treatment guidelines on the basis of comorbidity and absolute risk and compared with current prescription. RESULTS: Of 195 eligible patients, 97 participated in decision making using decision analysis. Among these 97, the decision analysis indicated that 59 (61%; 95% confidence interval, 50%-71%) would prefer anticoagulation treatment, considerably fewer than those who would be recommended treatment according to guidelines. There was marked disagreement between the decision analysis and guideline recommendations (kappa> or =0.25). Of 38 patients whose decision analysis indicated a preference for anticoagulation, 17 (45%) were being prescribed warfarin; on the other hand, 28 (47%) of 59 patients were not being prescribed warfarin, although the results of their decision analysis suggested they wanted to be. CONCLUSIONS: In the context of shared decision making, individualized decision analysis is valuable in a sizable proportion of elderly patients with atrial fibrillation. Taking account of patients' preferences would lead to fewer prescriptions for warfarin than under published recommendations. Decision analysis as a shared decision-making tool should be evaluated in a randomized controlled trial.
Entities:
Keywords:
Empirical Approach; Professional Patient Relationship
Authors: Mark H Eckman; Ruth E Wise; Katherine Naylor; Lora Arduser; Gregory Y H Lip; Brett Kissela; Matthew Flaherty; Dawn Kleindorfer; Faisal Khan; Daniel P Schauer; John Kues; Alexandru Costea Journal: Curr Med Res Opin Date: 2015-03-13 Impact factor: 2.580
Authors: Deb Feldman-Stewart; Sarah Brennenstuhl; Kathryn McIssac; Joan Austoker; Agathe Charvet; Paul Hewitson; Karen R Sepucha; Tim Whelan Journal: Health Expect Date: 2007-03 Impact factor: 3.377