Direct Weighting Interactive Design of Patient Preferences for Shared Decision Making in Orthopaedic Practice

Patients need the ability to accurately and efficiently communicate their preferences across outcome domains to their healthcare providers.1-7 No existing system provides an efficient and timely approach to collect and communicate patient preferences across outcome domains to support shared decision making (SDM) in orthopaedic practice.2-4,8-19 The overarching goal of this research is to design, build, and test an app that collects baseline patient preferences and health status across orthopaedic outcomes and reports this information to the provider for use in patient care. A core component of the app is a Direct-Weighting (DW) preference assessment approach, originated from our prior research, and applied in a touchscreen based interactive design. It is envisioned that patients will use the app after scheduling a first visit to a surgeon for a new orthopaedic condition. Direct weighting (DW) approaches calculate patient-specific preference weights across outcomes by asking patients to disperse portions of a hypothetical “whole” across outcomes in a manner that reflects a patient’s preferences.20 DW has low respondent burden but it requires respondents to make “implicit” comparisons which may be difficult to conceptualize.20 However, the DW approach has become generally accepted in the quality-of-life literature and it has been shown that patients dividing up pieces of a “pie” across quality-of-life domains yields valid representations of patient preferences across the domains.20-22 However, the DW approach has not been validated with specific clinical scenarios using a clinically focused set of outcomes or by using a mobile software app. Drawing on prior research, we iteratively design and develop the app with input from prior DW research, informaticians, and clinicians. We use a qualitative approach to pilot test the app with 20 first-time visit patients presenting with joint pain and/or function deficiency. Participants were interviewed about their outcome preferences for care, used the app to prioritize outcome preferences, answered interview questions about their experience using the app, and completed a mHealth App Usability Questionnaire (MAUQ). Interview questions focused on the utility and usability of the mobile app for communicating with their provider, and capability of the app to capture their outcome preferences. Results validated five core preference domains, with most users dividing their 100-point allocation across 1-3 domains. The tool received moderate to high usability scores. Patients with older age and lower literacy found the DW approach more difficult in terms of allocating 100 points across 5 domains. Suggestions for DW interface interaction improvement included instantiation of a token/points oriented DW preference scoring methodology rather than a 1-10 sliding scale approach for improved preference weighting cognition and SDM with a provider. As more patient reported outcome (PRO) apps hit the marketplace across a broad spectrum of health conditions, these results provide evidence for a DW approach and interactive design for patients to communicate their treatment preferences to their providers.References:1.Baumhauer JF, Bozic KJ. Value-based Healthcare: Patient-reported Outcomes in Clinical Decision Making. Clin Orthop Relat Res. 2016;474(6):1375-1378.2. Slim K, Bazin JE. From informed consent to shared decision-making in surgery. J Visc Surg. 2019;156(3):181-184.3. Damman OC, Jani A, de Jong BA, et al. The use of PROMs and shared decision-making in medical encounters with patients: An opportunity to deliver value-based health care to patients. J Eval Clin Pract. 2020;26(2):524-540.4. Sorensen NL, Hammeken LH, Thomsen JL, Ehlers LH. Implementing patient-reported outcomes in clinical decision-making within knee and hip osteoarthritis: an explorative review. BMC Musculoskelet Disord. 2019;20(1):230.5. Kamal RN, Lindsay SE, Eppler SL. Patients Should Define Value in Health Care: A Conceptual Framework. J Hand Surg Am. 2018;43(11):1030-1034.6. Charles C, Gafni A, Whelan T. Decision-making in the physician-patient encounter: revisiting the shared treatment decision-making model. Social Science & Medicine. 1999;49(5):651-661.7. Niburski K, Guadagno E, Mohtashami S, Poenaru D. Shared decision making in surgery: A scoping review of the literature. Health Expect. 2020.8. Selten EM, Geenen R, van der Laan WH, et al. Hierarchical structure and importance of patients' reasons for treatment choices in knee and hip osteoarthritis: a concept mapping study. Rheumatology (Oxford). 2017;56(2):271-278.9. Kannan S, Seo J, Riggs KR, Geller G, Boss EF, Berger ZD. Surgeons' Views on Shared Decision-Making. J Patient Cent Res Rev. 2020;7(1):8-18.10. Briffa N. The employment of Patient-Reported Outcome Measures to communicate the likely benefits of surgery. Patient Relat Outcome Meas. 2018;9:263-266.