Vision and aims
Using artificial intelligence (AI) to characterize the dynamic inter-relationships between polypharmacy and multiple long-term conditions across diverse UK populations and inform health care pathways
People who live with a number of medical conditions (multiple long-term conditions or MLTCs) are at high risk of poor health. They are often prescribed multiple medicines. When the number of medicines is greater than five, this is called polypharmacy. The relationship between MLTCs and polypharmacy is complex and not well understood.
We know that some patients enter a downward spiral, developing an increasing number of conditions and being prescribed more and more medicines.
This can cause health problems, as individual medicines may interact with one another or have side-effects. Other medicines may modify the downward spiral by preventing the development of conditions such as heart disease and cancer. All of this makes it difficult to design interventions to ensure medicines are prescribed in combinations that do more good than harm.
Our long-term goal is to better understand the dynamic relationship between MLTCs and polypharmacy, to optimise the medicines prescribed for individual patients. This research will also identify key points for intervention, to maintain the best possible health trajectory for people with MLTCs.