JMIR Publications

ABSTRACT

Background:

Managing multiple long-term conditions (MLTC) is a complex healthcare domain. It presents both challenges and opportunities for artificial intelligence (AI) tools. Understanding healthcare practitioners’ (HCPs) experiences of MLTC management and the factors influencing their attitudes towards using AI in complex clinical decision-making is crucial for successful implementation.

Objective:

We aimed to explore the perspectives of primary care HCPs on managing MLTC and their attitudes to using AI tools to support clinical decision-making in MLTC.

Methods:

Twenty HCPs including general practitioners, geriatricians, nurses and pharmacists, were interviewed. A patient case study was used to explore how an AI tool might alter the way participants approach clinical decision-making with a patient with MLTC. We derived concepts inductively from the interview transcripts and structured them according to the five categories of Buck’s model exploring determinants of attitudes to AI. These included the concerns and expectations that contributed to the minimum requirements for HCPs to consider using an AI decision-making tool, as well as the individual characteristics and environmental influences determining their attitudes.

Results:

HCPs perspectives on managing MLTC were grouped into three main themes: (1) balancing multiple competing factors including accounting for patients’ social circumstances, (2) managing polypharmacy, and (3) working beyond single condition guidelines. HCPs typically expected that AI tools would improve the safety and quality of clinical decision-making. However, they expressed concerns about the impact on the therapeutic clinician-patient relationship that is fundamental to the care of patients with MLTC. The key prerequisites for clinicians adopting AI-tools in this context included improving public and patient trust in AI, saving time and integrating with existing systems, and ensuring that the rationale behind a recommendation is apparent, to enable a final decision made by an experienced human clinician.

Conclusions:

This is the first study to examine the attitudes of HCPs to using AI-decision making tools in the context of managing MLTCs. HCPs were positive about the potential for AI tools to improve the safety and quality of care but unequivocal that the human touch is irreplaceable when managing patients with complex medical and social circumstances.