Value of using artificial intelligence derived clusters by health and social care need in primary care: A qualitative interview study with patients living with multiple long-term conditions, carers and health care professionals
Our findings suggest that implementing AI-derived clusters to identify and support SCNs in primary care is perceived as valuable and can be used as a tool to inform and prioritse effective clinical conversations. But concerns must be addressed, including how AI-derived clusters can be used in a way that considers personal context.
Authors
- Leanne Morrison (ORCID: https://orcid.org/0000-0002-9961-551X)
- Hajira Dambha‐Miller (ORCID: https://orcid.org/0000-0003-0175-443X)
- S Holt (ORCID: https://orcid.org/0000-0001-5448-3499)
- Kaiming Zhou (ORCID: https://orcid.org/0000-0002-6011-1912)
- Miriam Santer
- Hazel Everitt (ORCID: https://orcid.org/0000-0001-7362-8403)
- Glenn Simpson (ORCID: https://orcid.org/0000-0002-1753-942X)
- Andrew A. Farmer (ORCID: https://orcid.org/0000-0002-6170-4402)
- Zhiling Qian (ORCID: https://orcid.org/0000-0001-9741-7571)
- Firoza Davies (ORCID: https://orcid.org/0009-0005-9218-8702)
Institutions
- University of Oxford (GB)
- NIHR Southampton Biomedical Research Centre (GB)
- University of Southampton (GB)
Publication Details
- Journal
- Journal of Multimorbidity and Comorbidity
- Published
- 2025-06-24
- DOI
- https://doi.org/10.1177/26335565251353016
- Citations
- 6
- Primary Topic
- Chronic Disease Management Strategies
- Type
- article
- Field-Weighted Citation Impact
- 8.13
Funders
- National Institute for Health and Care Research
- Department of Health and Social Care
- NIHR School for Primary Care Research