Chronology in multimorbidity clustering and its effect on treatment burden and the utilisation of health and social care services

Talk Code: 
LM Kaluvu
Kaluvu L.M, Dey P, Moinuddin M, Jones R, Irving G
Author institutions: 
Faculty of Health, Social Care & Medicine, Edge Hill University


Multimorbidity, which is the co-occurrence of two or more long term chronic conditions within an individual, is common among the UK elderly as nearly two thirds of the population is affected. A rising physical-mental multimorbidity burden has also been observed among the younger individuals owing to an increased prevalence of mental health conditions, and a strong association between multimorbidity and lifestyle factors such as excessive smoking and alcohol consumption. Current studies have mostly examined disease clusters. Cardiometabolic clusters where type 2 diabetes and cardiovascular diseases are central have been linked to older age-groups whereas mental health clusters with depression and anxiety have been observed among the younger demographic.

Aim: The study seeks to examine the effect of chronology on the occurrence of chronic conditions and how it impacts on the formation of multimorbidity clusters. It will also compare how different clusters utilise health and social care services as well as the synergistic effect of socioeconomic status and lifestyle behavioural factors on the utilisation of these services. Lastly, it will explore the experiences of multimorbidity patients and how treatment burden might differ among those from different clusters.

The approach

A retrospective cross-sectional analysis of the St Helens shared care record, an integrated health and social care dataset for residents of the St Helens borough in the North West of England, will involve cluster identification and analysis. Findings from the analysis will inform the objectives of a follow-up qualitative study, where at least twenty multimorbidity patients belonging to high impact clusters will be purposively sampled and semi-structured interviews conducted.


By comparing how health service utilisation and treatment burden differs among the different multimorbidity clusters, study findings will enable the tailoring of multimorbidity programs for different cluster groups. Findings will also highlight social care utilisation within multimorbidity, which is less explored.


Funding acknowledgement: 
This research study is independent research funded by the National Institute for Health Research Applied Research Collaboration Northwest Coast (ARC NWC). The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care.