JMIR Publications

ABSTRACT

Background:

Artificial intelligence (AI) is increasingly applied in medicine, including clinical decision-making. AI-based decision support systems (DSS) can enhance early risk detection and treatment optimization. However, the perspectives of patients and their support persons (SPs) on AI-based DSS in clinical care, particularly regarding shared decision-making (SDM), remain underexplored.

Objective:

This study investigates the expectations, informational needs, and perceptions of kidney transplant patients and their SPs regarding AI-based DSS and its influence on SDM in post-transplant care.

Methods:

In a longitudinal qualitative study, 36 semi-structured interviews were conducted with kidney transplant patients and their SPs at a German kidney transplant centre. Participants were asked about their views on AI’s role in follow-up care, its impact on communication, trust, and decision-making, and their informational needs regarding AI-DSS. Interviews were transcribed, pseudonymized, and analysed using framework analysis.

Results:

Participants recognized AI’s potential to support physicians by identifying risks of transplant loss, rejection, and infection, and by providing data-driven treatment recommendations. However, they emphasized that final decisions should remain with physicians. A majority (78%) expressed concern that AI might depersonalize care and diminish physician-patient communication due to a lack of “human touch.” Participants demonstrated limited understanding of AI-DSS functionality and highlighted the need for simple, accessible educational materials (e.g., leaflets) explaining AI operations. While most doubted AI could replicate human empathy, some acknowledged that AI might be perceived as more attentive than time-pressured physicians, offering consistent monitoring and support. Participants consistently stressed that AI should augment, not replace, clinical decision-making.

Conclusions:

Kidney transplant patients and SPs support the integration of AI in follow-up care when it enhances clinical decision-making without supplanting the physician’s role. Acceptance and trust depend on transparency, accountability, and preserving the “human touch” in care. Development of educational tools to communicate AI functions and limitations is crucial to empower patients and SPs in SDM processes and to ensure AI complements, rather than undermines, patient-centered care.