Examining the Clustering of MLTCs in individuals Treating a patient with one long-term condition (LTC) is generally simpler than treating a patient with many. Multiple long term conditions (MLTCs) can involve managing numerous symptoms, treatments, prescriptions and side-effects. To deal with MLTCs more effectively, our first objective aims to create a picture of the most common combinations of long-term conditions across the United Kingdom. We will be using data from the Clinical Practice Research Datalink (CPRD), a government funded organisation that holds information from thousands of General Practices, and other linked sources such as cancer registers, death registration data, and Accident and Emergency data. Objective 1 will develop several data analysis methods to find groups or ‘clusters’ of individuals with similar long-term conditions within the CPRD dataset. Checking that our methods produce valid results is a crucial part of this objective. The results will then be fed into the other objectives. Clinical Bruce Guthrie - Principal Investigator Image Bruce Guthrie is Professor of General Practice at the Usher Institute, in the Edinburgh Medical School. He is also the director of the Advanced Care Research Centre. Bruce is a mixed methods health services researcher with an interest in the quality and safety of health and social care, particularly in relation to multimorbidity and polypharmacy. As well as research, he works clinically as a GP and works closely with the NHS and government to improve healthcare quality and safety. Find out more about Bruce at the link below: Bruce's profile page Atul Anand - lead on Complex Multimorbidity in Acute Care Image Atul Anand is an academic geriatrician, senior clinical research fellow and clinical lead for the Lothian DataLoch. His research focuses on routine data-enabled trials of accelerated care pathways and development of automated tools for identifying frail patients at the hospital front door. He will contribute clinical and frailty expertise across the programme, particularly in relation to examining adverse events associated with complex multimorbidity and polypharmacy in acute care. Find out more about Atul at the link below: Atul's profile page Nazir Lone - Co-Lead on Clinical and Health Services Research Image Nazir Lone is Senior Clinical Lecturer in Critical Care and Director of Research for UK Intensive Care Society. He has methodological expertise in epidemiology/data science, particularly applied to large datasets in acute/critical care health service settings. In national roles, he leads data-driven programmes focussed on healthcare improvement in Critical Care. He will contribute clinical and multimorbidity expertise across the programme and lead the work in relation to complex multimorbidity in acute care. Find out more about Nazir at the link below: Nazir's profile page Artificial Intelligence Jacques Fleuriot - Cross-programme Artificial Intelligence lead Image Jacques Fleuriot is Personal Chair of Artificial Intelligence, and Director of the Artificial Intelligence and its Application in the School of Informatics. is research focuses on AI modelling, which spans areas such as formal verification, process modelling, and explainable AI in healthcare and other complex domains. Find out more about Jacques at the link below: Jacques' research page Sohan Seth - Artificial Intelligence and Machine Learning lead Image Sohan Seth is a Senior Data Scientist at University of Edinburgh’s School of Informatics with a background in Machine Learning and Data Science. His research focuses primarily on building interpretable models for extracting information from scientific data. Find out more about Sohan at the link below: Sohan's profile page Valerio Restocchi - co-lead on multilayer network analysis (objectives 1, 3 and 4) Valerio Restocchi is a lecturer in Business Application of Informatics in the School of Informatics. Find out more about Valerio at the link below: Valerio's profile page Guillermo Romero Moreno - PDRA, multi-layer network in objectives 1, 3 and 4 Image Initially employed in industrial engineering, Guillermo subsequently obtained a Masters and then a PhD from the University of Southampton. His role in AIM-CISC involves applying tools from network science (with focus on multilayer networks – MLNs - and community detection) to the analysis and prediction of multimorbidity. Find out more about Guillermo at the links below: LinkedIn Researchgate GitHub This article was published on 2024-09-24