Forecasting the Impacts of Artificial Intelligence Assistance in Virtual Consultations for Chronic Obstructive Pulmonary Disease: Exploratory Futures Wheel Study.

Background: While digital health technologies promise to reshape the medical journey, their potential might not be realized due to unforeseen implementation challenges. Notably, the future impact of artificial intelligence (AI) in virtual consultations has been poorly investigated. Objective: This study aims to explore, across 8 areas, the future impacts of a bespoke, co-designed AI tool for remote chronic obstructive pulmonary disease care from the perspectives of patients and health care professionals (HCPs) with the Futures Wheel (FW) method. It provides practical recommendations for conducting FW activities involving novel digital health tools. Methods: A pilot FW workshop was conducted with public and patient involvement members to gather feedback on the process. Subsequently, an exploratory, in-person FW workshop was conducted with 2 patients with chronic obstructive pulmonary disease and 2 HCPs who had previously been involved in the co-design of the bespoke AI tool. The central statement was as follows: "The bespoke AI tool is used in every virtual consultation." Participants identified first- and second-order consequences across the following 8 areas of impact: HCP-patient relationship impact, psychological impact, social impact, educational impact, legal impact, ethical impact, health care delivery impact, and technology impact. Each participant discussed their individual input to provide additional context. Results: Regarding the HCP-patient relationship, patients foresee the tool's impact as redefining the remote care dynamic with enhanced patient involvement, while HCPs identify its meaningful communication assistance. On the psychological impact, patients expect an enhanced level of empowerment and confidence, and HCPs anticipate improved understanding of patients' emotional well-being with the AI tool's assistance. As for social impacts, patients view the AI support as beneficial for social patient-HCP interactions, and HCPs foresee their workflow being enhanced with flexibility and collaboration. The AI's educational impacts are expected to include, from patients' perspectives, better familiarization of HCPs with individual patient cases and, from HCPs' perspectives, improved support for training, upskilling, and administrative tasks. On the legal front, patients identify limited risks associated with the tool, and HCPs expect its features to lead to safer practices, contingent on regulatory compliance. Provided integrity and ethical use, the tool's ethical impact is not perceived as significant by patients, while HCPs see its personalized features as leading to fair, individual remote assessments. Patients envision the AI tool's impact on health care delivery as fostering patient-centricity, and HCPs anticipate strengthened remote care processes. Technologically, patients forecast a significant improvement to the current system, requiring adequate investment and resources, while HCPs expect complementarity between human input, AI, and the current system. Conclusions: The plausible AI-driven future of remote chronic care is a nuanced one. The FW method indicated that a bespoke, co-designed AI tool can positively support virtual care delivery and remote interactions while indicating potential risks. These insights can inform strategies related to early planning, governance, and implementation considerations.