DOI: 10.1192/bjo.2026.12117 ISSN: 2056-4724

Healthcare use by people with dementia from diagnosis to the end of life: latent class and longitudinal analysis of linked healthcare data

Emel Yorganci, Robert Stewart, Elizabeth L. Sampson, Ewan Carr, Katherine E. Sleeman

Background

The first year after diagnosis and the last year of life are critical periods for people with dementia.

Aims

To (a) identify subgroups within a large sample of people with dementia, characterised by healthcare use in the year after diagnosis and the last year of life; (b) describe the biopsychosocial characteristics associated with these subgroups; and (c) explore moves between subgroups over time.

Method

A retrospective cohort of people diagnosed with dementia in London, UK, was assembled using linked clinical and administrative data-sets. We used latent class analysis to identify subgroups based on hospital and specialist mental healthcare service use in the year following diagnosis and the year before death. We used multinomial logistic regression to describe biopsychosocial characteristics and class membership, and latent transition analysis to explore moves between subgroups.

Results

Among 8623 people with dementia, we identified 3 subgroups of healthcare use in the year after diagnosis: ‘low use’ (49%), ‘hospital use’ (34%) and ‘mental healthcare use’ (17%). In the last year of life, four subgroups were identified: ‘low use’ (32%), ‘moderate hospital use’ (43%), ‘high hospital use’ (9%) and ‘community healthcare use’ (17%). Biopsychosocial factors, including age, ethnicity, and cognitive and physical problems, associated with subgroups differed for the time periods. Male gender, mixed dementia and vascular dementia diagnoses were associated with a higher risk of unplanned hospital use. Transition probabilities indicated unstable patterns of healthcare use after diagnosis and before death.

Conclusions

Distinct subgroups and healthcare patterns in two care periods can facilitate proactive, needs-based service provision while potentially reducing emergency hospital use.

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