Interactive Multiobjective Optimization for Finding The Most Preferred Exercise Therapy in Knee Osteoarthritis

Background: The primary purpose of this study is to develop a decision support approach to support physicians or other healthcare professionals in comparing different exercise therapies and identifying the most preferred one by balancing among cost, ability of improving physical function and reducing pain in patients with knee osteoarthritis.Methods: Thirty-one exercise therapies were selected from twenty-one randomized controlled trials from a previous meta-analysis. A multiobjective optimization model was designed to characterize the goodness of an exercise therapy based on five conflicting criteria: minimizing cost, maximizing pain reduction and disability improvement, minimizing the number of supervised exercise sessions and the length of the treatment period. Costs were estimated based on personal expenses regarding the information given in the collected randomized controlled trials. A novel interactive multiobjective optimization method was introduced to solve the model, where the physician’s preferences were taken into account in finding the most preferred exercise therapy. Results: An experienced physiotherapist was involved as a decision maker in the interactive solution process testing the proposed decision support approach. He iteratively provided preference information until he was satisfied with the set of therapies shown. After a more in-depth detailed analysis of selected therapies, the decision maker was able to find the most preferred exercise therapy based on the patient's needs and health status. Conclusions: The proposed interactive multiobjective optimization method is promising in supporting the decision maker in balancing among conflicting criteria to find the most preferred exercise therapy for patients with knee osteoarthritis. Moreover, the proposed method is generic enough to be applied in any field of medical and healthcare settings, where several alternative treatment options exist.