Development of a Data-Enabled Mixed Method for Designing for Patients From a Human-Centered Design Perspective: Explorative Case Study.

Background: In the early stage of human-centered design (HCD), qualitative and generative methods are commonly used to explore patients' contexts and needs, emphasizing active patient involvement to ensure that design insights accurately reflect real experiences and enhance both design effectiveness and patient empowerment. However, certain challenges arise in the early stage of the HCD process, including (1) high vulnerability of patient participants, (2) less diverse and representative patient groups due to recruitment challenges, and (3) insufficient problem framing across diverse patient experiences. Objective: To address these challenges while embracing the system-level HCD perspective, we propose a data-enabled mixed method combining large-scale patient digital research (module A) and in-depth patient engagement research (module B). This paper explores the feasibility and potential value of this mixed method in addressing the identified challenges through a case study. Methods: In module A, we analyzed a large-scale dataset of online forum posts and validated the extracted topics with medical experts to create a patient community journey map through cocreation sessions. Guided by these findings, module B involved a diary study using a sensitizing paper prototype and semistructured follow-up interviews with 4 patients. Results: In module A, 37 topics and 10 upper clusters were summarized from 212,107 online posts, revealing that topics associated with the home context exhibited a higher density of emotional content than those related to the hospital context. Patients placed more emphasis on social and mental health during the follow-up stage than in the diagnosis and treatment phases. This shift reveals a gap in current remote monitoring systems, which focus mainly on physical health. Addressing this identified gap, we developed a prototype for use in the module B diary study involving 4 patients. Patients responded positively to the prototype, noting that remote monitoring incorporating social and mental well-being could help them better understand themselves, enhance self-awareness, and improve communication with their physicians. Overall, this study explores the preliminary value of this mixed method in effectively reframing design problems and deeply contextualizing patient needs. Conclusions: This study provides preliminary evidence supporting the potential of integrating large-scale digital patient research (module A) with in-depth patient engagement (module B) during the early stages of human-centered health care design. The core strength of this mixed method approach lies in its ability to facilitate problem reframing and cultivate a deeper sense of empathy and understanding of patient vulnerability prior to direct engagement. Simultaneously, it captures both the breadth and depth of patient perspectives, offering evidence-based insights that enhance the overall efficacy of user research. Further research across diverse medical contexts is essential to establish the generalizability of these findings.