• Kevin J Bozic and Vanessa Chiu.
• Department of Orthopaedic Surgery and Philip R. Lee Institute for Health Policy Studies, University of California-San Francisco, 500 Parnassus, MU 320 W, San Francisco, CA 94143-0728, USA. kevin.bozic@ucsf.edu
• Clin. Orthop. Relat. Res. 2011 Jul 1;469(7):2081-5.

BackgroundDespite the widely reported success of total joint arthroplasty (TJA) in reducing pain and improving quality of life and function for patients with hip or knee osteoarthritis, rates of TJA use vary widely throughout the United States, with broad disparities based on geographic, racial, and socioeconomic factors. Shared decision-making approaches, which require an exchange of information between patients and their physicians, can be helpful in improving patient satisfaction with their treatment decision and appropriate use of TJA.Questions/HypothesesExpected-value decision analysis models incorporating evidence-based outcome data with individual patient preferences regarding health states and willingness to pay, when used in shared decision-making models, will improve satisfaction among patients with hip or knee osteoarthritis and lead to more appropriate use of TJA.Proposed ProgramPatients with hip or knee osteoarthritis will be randomized to usual care or participation in a shared decision-making intervention. Patients in the shared decision-making intervention arm will have their preferences for individual health states related to osteoarthritis and TJA measured using the time trade-off technique, and these values will be incorporated in an expected-value decision analysis model, which also will incorporate the patient's willingness to pay for a particular treatment intervention and evidence-based outcome probabilities. The patient's decision for operative versus nonoperative care and their level of satisfaction with their decision will be compared using chi square and Mann-Whitney rank-sum tests.SignificanceInformation regarding patient preferences for particular health states and willingness to pay can be combined with evidence-based outcome data in expected-value decision analysis models, which will help inform shared clinical decision making between surgeons and their patients with hip or knee osteoarthritis.

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