Artificial intelligence and health equity in primary care: A qualitative study with key stakeholders

Abstract

Artificial Intelligence (AI)-augmented interventions are currently being rolled out across primary care, but how it affects health equity remains insufficiently understood. This qualitative study addresses this gap through an ethnographical inquiry based on 32 interviews and focus groups with stakeholders including commissioners, decision makers, AI developers, researchers, GPs and patient groups involved in the implementation of AI in English primary care. We took a sociotechnical perspective in order to assess how the stakeholders can improve health equity through the implementation process of AI within the wider system. We found that regulation and policy alone cannot guarantee equitable implementation of AI but can provide a framework to enable other stakeholders to take measures to promote equity: fostering a shared understanding of the causal mechanisms of AI and health equity, how to measure health equity, and how to share data necessary for equity promotion. Further, all stakeholders need to be on board for equitable implementation, and currently innovation leaves clinicians and patients behind. Capacity building is needed to achieve this, in particular at local commissioning and clinician level. Careful implementation and pragmatically focused research are needed to make AI in primary care capable of advancing health equity.