The Usability and Feasibility of Conjoint Analysis to Elicit Preferences for Distal Radius Fractures in Patients 55 Years and Older.

PURPOSE: Eliciting patient preferences is one part of the shared decision-making process-a process of decision making focused on the values and preferences of the patient. We evaluated the usability and feasibility of a point-of-care conjoint analysis tool for preference elicitation for shared decision making in the treatment of distal radius fractures in patients over the age of 55 years. METHODS: Twenty-seven patients 55 years of age or older with a displaced distal radius fracture were recruited from a hand and upper extremity clinic. A conjoint analysis tool was created describing the attributes of care (eg, return of grip strength) of surgical and nonsurgical treatment. This tool was administered to patients to determine their preferences for the treatment attributes when choosing between surgical and nonsurgical treatment. Patients completed a System Usability Scale (SUS) to evaluate usability, and time to complete the tool was measured to evaluate feasibility. RESULTS: Patients considered the conjoint analysis tool to be usable (SUS, 91.4; SD, 10.9). Mean time to complete the tool was 5.1 minutes (SD, 1.4 minutes). The most important attributes driving the decision for surgical treatment were return of grip strength at 1 year and time spent in a cast or brace. The most important attributes driving the decision for nonsurgical treatment were use of anesthesia during treatment and return of grip strength at 1 year. CONCLUSIONS: A point-of-care conjoint analysis tool for distal radius fractures in patients 55 years and older can be used to elicit patient preferences to inform the shared decision-making process. Further investigation evaluating the effect of preference elicitation on treatment choice, involvement in decision making, and patient-reported outcomes are needed. CLINICAL RELEVANCE: A conjoint analysis tool is a simple, structured process physicians can use during shared decision making to highlight trade-offs between treatment options and elicit patient preferences to inform treatment choices.