Using Real World Data to identify and plan interventions to reduce polypharmacy and transform prescribing in Multiple Long-Term Conditions

Using Real World Data to identify and plan interventions to reduce polypharmacy and transform prescribing in Multiple Long-Term Conditions

Around one in four adults in England, which equates to more than fourteen million people, are now living with two or more health conditions. People with multiple conditions have poorer quality of life and a higher mortality risk. Some combinations are associated with especially poor outcomes; people with severe mental illness live 10 to 20 years less than the general population. People’s problems do not fit neatly into the way the current service is configured. This is particularly an issue in relation to prescribing, where there is frequently little integration across co-existing diseases and polypharmacy can easily result. The intelligent use of data and AI could provide solutions to this growing problem in the NHS.

Asra Photo Rewired 2025

Dr Asra Aslam

Assistant Professor (Lecturer), University of Sheffield and Principal Investigator, The Alan Turing Institute, UK

Reecha Sofat

Prof Reecha Sofat

Chair, PRSB, Breckenridge Chair of Clinical Pharmacology, University of Liverpool and Associate Director, BHF Data Science Centre (HDR UK)

rafael

Prof Rafael Perera

Professor of Medical Statistics, University of Oxford

Monica_Fletcher

Monica Fletcher OBE

Co-Chair:
Honorary Research Fellow, Nuffield Department of Primary Care Oxford University and Non-Executive Director NHS Sussex ICB

Tony-Avery

Prof Tony Avery

Co-Chair:
Professor of Primary Healthcare, University of Nottingham and National Clinical Director for Prescribing, NHS England

March 19 @ 10:30
10:30 — 11:15 (45′)

Innovation Stage

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