Abstract
Shared decision-making (SDM) is the cornerstone of patient-centered care, where patients and clinicians work together to explore care choices, evaluate evidence of the benefits and risks, assess treatment goals and preferences, and jointly make informed care decisions. Over the past 2 decades, a growing body of research has demonstrated meaningful improvements in decision-making through SDM and patient decision aids (ptDA), tools supporting patients' decisions by providing thorough information and clarifying net benefits. The recent Cochrane meta-analyses (with over 200 studies, comprising approximately 107,000 participants, covering 70 different decision types) have reported that SDM and ptDAs significantly increased patient knowledge, improved the accuracy of risk perceptions, reduced decisional conflict, and enhanced clarity on personal values.1 Evidence that SDM and ptDAs improve health outcomes, however, is mixed as definitions and processes of SDM and ptDAs are inconsistent, reducing generalizability across populations and clinical conditions.2 Nevertheless, patients consistently indicate satisfaction with the decision process.1 Recent work has been expanding into digital and AI-enabled decision aids, exploring their feasibility; user experience; personalization; and barriers including health literacy, access, and risk of bias.3 Patients often report that AI-enabled decision aids are easy to use, provide a sense of ownership, and promote better adherence to treatments; however, clinicians have expressed concerns about the potential for overtreatment or undertreatment.