AI MULTIPLY V1.0
Research type
Research Study
Full title
Using artificial intelligence (AI) to characterize the dynamic inter-relationships between MUltiple Long-term condiTIons and PoLYpharmacy and across diverse UK populations and inform health care pathways (AI-MULTIPLY).
IRAS ID
319020
Contact name
Nick Reynolds
Contact email
Clinicaltrials.gov Identifier
NU-009632, NU-Projects reference
Duration of Study in the UK
2 years, 5 months, 28 days
Research summary
Many people live with two or more ‘long-term health conditions’, which include lots of different illnesses, such as cancer, heart, and mental health problems. People living with multiple long-term conditions (MLTC-M) may progress to poor health and have a shorter life expectancy. Treating multiple health conditions is a balancing act. People are often prescribed many different medicines together (known as ‘polypharmacy’). Sometimes these medicines (and their side effects) can interact in unexpected ways, causing further problems.
Our interdisciplinary consortium brings together experts in data access/engineering, epidemiology, pharmacy, clinical medicine, AI, anthropology, trial emulation, PPI, and healthcare relevant to the management of MLTC-M. Our PPI and stakeholder groups have shaped and extended our research questions and methodologies. In the lead up to this project, we have developed a number of methodologies. These will be optimised during this project using well-curated data (UK-Biobank and CPRD) and then validated on routinely collected electronic health record (EHR) NHS data from the North-East of England and East London, with particular focus on intersectional contrasts, including ethnicity and deprivation. Findings will be interpreted in the local context, with PPI support, and validated in carefully selected cohorts in Bradford and Scotland.
The overarching aim of the research is to characterise MLTC-M and polypharmacy (MLTC-M-PP) trajectories and define the interrelationships between MLTC-M clusters, polypharmacy, inequalities and healthcare outcomes over the life-course.
REC name
North East - Tyne & Wear South Research Ethics Committee
REC reference
23/NE/0051
Date of REC Opinion
30 Mar 2023
REC opinion
Favourable Opinion