Clustering of Multimorbidity and Social Care Needs: 10-year all-cause mortality in a cohort study of more than 7 million people

Summary Background Research on multimorbidity, commonly defined as the presence of two or more long term conditions, has predominantly focused on biological and clinical needs. However, unmet social care needs (SCNs), including, for example, mobility limitations, financial hardship, and social isolation, can also adversely affect health outcomes. We aimed to identify distinct clusters of individuals with multimorbidity and SCNs, and to examine their associations with 10 year all cause mortality. Methods We analysed data from the Clinical Practice Research Datalink (CPRD) Gold and Aurum databases (Jan 1, 1987, to Dec 31, 2020) to identify adults in England living with multimorbidity. Latent class analysis was used to derive clusters based on long term conditions and eight predefined domains of SCNs. Threshold criteria were applied to determine meaningful representation of long-term conditions and SCNs within each cluster. Associations with 10-year all cause mortality were assessed using Cox proportional hazards models, adjusted for age, sex, ethnicity, deprivation, multimorbidity burden, SCNs, and year of multimorbidity diagnosis. Findings Amongst 7.2 million individuals with multimorbidity (mean age 54.4 years [SD 18.2]; 55% female), 37% had at least one SCN, with community care needs being the most common (28%). Four distinct clusters were identified: Cluster 1 (mean age 37.3 years [SD 14.5]) comprised individuals with predominantly mental and behavioural conditions, no SCNs, high deprivation, and the lowest mortality risk (reference group); Cluster 2 (mean age 57.9 years [SD 16.3]) included those with cardiovascular, musculoskeletal, and mental and behavioural conditions, no SCNs, and a higher mortality risk (adjusted hazard ratio [aHR] 1.47 [95% CI 1.45 to 1.48]);Cluster 3 (mean age 62.6 years [SD 16.4]) had similar clinical profiles to cluster 2 but the highest SCN burden, lower deprivation, and the greatest mortality risk (aHR 2.83 [2.75 to 2.92]); Cluster 4 (mean age 62.6 years [SD 15.2]) exhibited the highest burden of long-term conditions, two SCNs, high deprivation, and elevated mortality (aHR 1.49 [1.47 to 1.51]). Interpretation We identified four distinct clusters of individuals with varying profiles of multimorbidity, social care needs, and mortality risk. These findings underscore the importance of personalised, integrated care approaches and support the development of targeted interventions to address the complex and intersecting needs of the most vulnerable populations. Keywords: multiple long term conditions, social care needs, clustering, mortality, artificial intelligence