Purpose People living with MLTCs attending consultations in primary care frequently have unmet social care needs (SCNs), which can be challenging to identify and address. Artificial intelligence (AI) derived clusters could help to identify patients at risk of SCNs. Understanding the views of people living with MLTCs and those involved in their care can help inform the design of effective interventions informed by AI-derived clusters to address SCNs. Methods Qualitative study using semi-structured online and telephone interviews with 24 people living with MLTCs and 20 people involved in the care of MLTCs. Interviews were analysed using Reflexive Thematic Analysis. Results Primary care was viewed as an appropriate place to have conversations about SCNs. However, participants felt health care professionals lack capacity to have these conversations and to identify sources of support. AI was perceived as a tool that could potentially increase capacity for this but only when supplemented with effective, clinical conversations. Interventions harnessing AI should be brief, be easy to use and remain relevant over time, to ensure no additional burden on clinical capacity. Interventions must allow flexibility to be used by multidisciplinary teams within primary care, frame messages positively and facilitate conversations that remain patient centered. Conclusion Our findings suggest that AI-derived clusters to identify and support SCNs in primary care have perceived value, but there were some concerns including the need to consider personal context. AI derived clusters can be used as a tool to inform and prioritise effective clinical conversations.

The authors have declared no competing interest.

This study is independent research funded by the National Institute for Health Research - the Artificial Intelligence for Multiple Long-Term Conditions, or "AIM". 'The development and validation of population clusters for integrating health and social care: A mixed-methods study on multiple long-term conditions' (NIHR202637). The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care. This study/project is funded by the National Institute for Health and Care Research (NIHR) School for Primary Care Research (project reference 667 FR6). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. AF is supported by the National Institute of Health Research (NIHR) Oxford Biomedical Research Centre (BRC).

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