The development and validation of population clusters for integrating health and social care: A mixed-methods study on Multiple Long-Term Conditions

Conference: 
SAPC ASM 2022 - UCLan
Talk Code: 
3D.5
Presenter: 
Glenn Simpson
Co-authors: 
Prof Andrew Farmer, Dr Leanne Morrison, Prof Miriam Santer, Dr Zlatko Zlatev, Dr Mazen Ahmed, Prof. Michael Boniface, Dr Hajira Dambha-Miller, Dr Glenn Simpson*
Author institutions: 
University of Southampton

Problem

Evidence is urgently needed about how to generate clusters based on health and psycho-social need and to quantify the potential impact of clusters on improving long-term health and reducing care costs and other resources inputs. This project will develop and validate population clusters that consider health and social care determinants and subsequent need for people with MLTC, using data-driven Artificial Intelligence methods, which will be compared with expert-driven approaches.

Approach

Semi-structured interviews exploring patient, carer and professional perspectives on clinical and socio-economic factors influencing experiences of living with or seeking care for MLTC. Inductive reflexive thematic analysis will be used to analyse the data. Close re-reading of transcripts will generate a coding framework. Codes will be synthesised into themes. QSR NVivo software will support data management.

Findings

This research is a work in progress. Fieldwork is being conducted during February – March 2022. Interim findings from the fieldwork will be reported in April 2022. A full account of the findings will be available for presentation at the conference in July 2022. These findings will focus on the themes of: the lived experiences of people with MLTC; the experiences of those who provide care, treatment and support to people with MLTC; the healthcare, social care and wider social determinant ‘challenges’ of caring for people with MLTC; and insights relating to better approaches to providing care and support to those experiencing MLTC.

Consequences

The final research outputs will offer health and social care commissioners and policymakers reliable evidence for a new approach to managing MLTC, in particular, utilising a ‘whole patient’ approach to inform tailoring of intervention development specific to each MLTC cluster. The evidence generated by the study has potential to be a powerful tool for delivering holistic personalised care and in doing so, reduce the human cost and resource burden of MLTC.

Submitted by: 
Glenn Simpson
Funding acknowledgement: 
National Institute for Health Research funding, Artificial Intelligence for Multiple Long-Term Conditions (Multimorbidity) Programme.