E.7. Round Table: Translating multimorbidity patterns into practice: from research to implementation
Abstract
Multimorbidity (also referred to as Multiple Long-Term Conditions), the co-existence of two or more chronic conditions, is increasing globally and poses a challenge to health systems largely designed to provide care for single diseases. Multimorbidity is highly heterogeneous and over the past decade, epidemiological research identifying common patterns of co-occurring conditions – often using data-driven clustering methods – has been substantial. However, there remains a large gap between the insights from multimorbidity clusters and their application in clinical practice, health system planning and policy to support patient-centred care. This gap reflects two interrelated challenges. First, multimorbidity clustering studies are often methodologically complex, making the findings difficult to interpret, limiting translation to real-world clinical settings. Although clustering is perceived as data-driven, it is underpinned by multiple subjective choices, such as which data sources to use and how to select the clusters. These decisions are rarely informed by input from patients and clinicians, limiting clinical relevance. Second, even where reproducible clusters are identified, it remains unclear how clusters can be translated into actionable insights to improve quality of care, outcomes and service efficiency. This roundtable aims to critically examine learning from multimorbidity clustering research, and how the research and healthcare communities can support translation of clustering insights into practice to improve integrated and person-centred care.
Objectives: 1. Synthesise current evidence of multimorbidity clusters 2. Examine key methodological limitations that hinder translation and potential solutions 3. Discuss how current clustering insights can inform integrated and inclusive person-centred care The added value of this workshop is in bringing together researchers, clinicians and policymakers from different international contexts to discuss how to bridge the gap between methodological innovation and real-world application of multimorbidity clustering research. The goal is to support a move beyond description of clusters to identifying opportunities for risk stratification and prediction, integrated care and service organisation. The presentations are coherent in progressing from understanding what clusters have revealed about disease combinations, critically appraising their limitations and exploring solutions, and finally, discussing opportunities for translation. The workshop will consist of three 7-minute presentations: 1. What has clustering research taught us about multimorbidity? 2. Multimorbidity clustering: methodological challenges and solutions3. From clusters to care: how can multimorbidity clusters inform healthcare services today? A 30-minute roundtable discussion will follow, facilitated by the chairs, addressing audience questions. The session will conclude with a synthesis of key messages and priorities for research and practice.
Key messages: • Despite extensive research into multimorbidity patterns, real-world application of their insights remains limited due to methodological and translational challenges.
• This workshop will critically examine how research and healthcare communities can support translation of insights from multimorbidity patterns to improve integrated services and person-centred care.
Speakers/Panellists: Thomas Beaney
The George Institute for Global Health, Imperial College London, London, UK
Rachel Johnson
Bristol Medical School, University of Bristol, Bristol, UK
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BibTeX
@article{thegeorgeinstituteforglobalhealthuk2026round,
title = {{E.7. Round Table: Translating multimorbidity patterns into practice: from research to implementation}},
author = {The George Institute for Global Health (UK), Imperial College London (UK), NIHR Imperial Biomedical Research Centre (UK) and Chris Butler and Clare MacRae},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.397},
url = {https://doi.org/10.1093/eurpub/ckag169.397},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - E.7. Round Table: Translating multimorbidity patterns into practice: from research to implementation
AU - The George Institute for Global Health (UK), Imperial College London (UK), NIHR Imperial Biomedical Research Centre (UK)
AU - Chris Butler
AU - Clare MacRae
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.397
UR - https://doi.org/10.1093/eurpub/ckag169.397
AB - Multimorbidity (also referred to as Multiple Long-Term Conditions), the co-existence of two or more chronic conditions, is increasing globally and poses a challenge to health systems largely designed to provide care for single diseases. Multimorbidity is highly heterogeneous and over the past decade, epidemiological research identifying common patterns of co-occurring conditions – often using data-driven clustering methods – has been substantial. However, there remains a large gap between the insights from multimorbidity clusters and their application in clinical practice, health system planning and policy to support patient-centred care. This gap reflects two interrelated challenges. First, multimorbidity clustering studies are often methodologically complex, making the findings difficult to interpret, limiting translation to real-world clinical settings. Although clustering is perceived as data-driven, it is underpinned by multiple subjective choices, such as which data sources to use and how to select the clusters. These decisions are rarely informed by input from patients and clinicians, limiting clinical relevance. Second, even where reproducible clusters are identified, it remains unclear how clusters can be translated into actionable insights to improve quality of care, outcomes and service efficiency. This roundtable aims to critically examine learning from multimorbidity clustering research, and how the research and healthcare communities can support translation of clustering insights into practice to improve integrated and person-centred care. Objectives: 1. Synthesise current evidence of multimorbidity clusters 2. Examine key methodological limitations that hinder translation and potential solutions 3. Discuss how current clustering insights can inform integrated and inclusive person-centred care The added value of this workshop is in bringing together researchers, clinicians and policymakers from different international contexts to discuss how to bridge the gap between methodological innovation and real-world application of multimorbidity clustering research. The goal is to support a move beyond description of clusters to identifying opportunities for risk stratification and prediction, integrated care and service organisation. The presentations are coherent in progressing from understanding what clusters have revealed about disease combinations, critically appraising their limitations and exploring solutions, and finally, discussing opportunities for translation. The workshop will consist of three 7-minute presentations: 1. What has clustering research taught us about multimorbidity? 2. Multimorbidity clustering: methodological challenges and solutions3. From clusters to care: how can multimorbidity clusters inform healthcare services today? A 30-minute roundtable discussion will follow, facilitated by the chairs, addressing audience questions. The session will conclude with a synthesis of key messages and priorities for research and practice. Key messages: • Despite extensive research into multimorbidity patterns, real-world application of their insights remains limited due to methodological and translational challenges. • This workshop will critically examine how research and healthcare communities can support translation of insights from multimorbidity patterns to improve integrated services and person-centred care. Speakers/Panellists: Thomas Beaney The George Institute for Global Health, Imperial College London, London, UK Rachel Johnson Bristol Medical School, University of Bristol, Bristol, UK
SN - 1101-1262
SN - 1464-360X
ER -