Data
Work Package 1: Collecting Data
“Data Access, Data Wrangling, Data Engineering” AI MULTIPLY researchers will make use of multiple, large patient datasets, both national and…
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 may progress to poor health and have a shorter life expectancy.
Treating multiple health conditions is a balancing act. It often requires taking multiple medications, known as polypharmacy (when more than five drugs are used). The relationship between MLTCs and polypharmacy is complex, and sometimes these medications (and their side effects) can interact in ways that can cause further health issues.
The AI MULTIPLY project aims to improve treatment for individuals with MLTCs by exploring the connections between these conditions and polypharmacy. It will also investigate the personal and social factors that contribute to polypharmacy. By gaining insights into these relationships, the project will support the development of strategies to address the issue with the goal of reducing healthcare inequalities.
Our group has experience in applying new developments in computer technology, termed artificial intelligence (AI) and machine learning, to healthcare data. We will develop these methods to look for new patterns linking MLTCs and prescribed medicines. The information and patterns generated will feed into the design of a larger collaborative project.
Outcomes
Health Outcomes: The project is expected to improve patient care by offering personalised treatment plans.
Cost savings: Streamlined treatment can reduce hospital visits and healthcare costs.
Health Equity: Addressing inequalities by improving access to care and treatment options for disadvantaged communities.
In the long term, we hope our research will lead to the development of strategies for prevention and improved management of multiple long-term conditions.
The AI MULTIPLY consortium is directed by Nick Reynolds, Professor of Dermatology at Newcastle University and Michael Barnes, Professor of Bioinformatics and Director of the Centre for Translational Bioinformatics at Queen Mary University of London.
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