Drugs represent 10% of total UK health expenditure and for cardiovascular disease, which is the major cause of burden of disease in the UK, 18% of spending is on drugs. Despite polypharmacy (multiple drugs) and multi-morbidity (multiple diseases), there is poor adherence (whether drugs are taken as prescribed) and persistence (whether drugs continue to be taken over time) for drugs across cardiovascular diseases and this is associated with poor outcomes. There is limited understanding of the factors causing poor adherence and the impact across drugs and diseases, and interventions to improve adherence and persistence have proved to be elusive.
A cascade of missed opportunities exists from guideline recommendation of a drug and prescription by the health professional, through adherence and persistence by the patient, to the “real-world” impact of the drug at population level. Big data science allows the steps in the cascade to be studied together across drugs and diseases in ways which were previously not possible. We will be using electronic health records and data from the Global Burden of Disease Study to model prescription, adherence and persistence, as well as the population impact of drugs in individuals with coronary artery disease, heart failure and atrial fibrillation. Our research will span several disciplines, including informatics, epidemiology, computer science and pharmacy. The aim is to develop tools for measurement, prediction and improvement of drug adherence in routine clinical practice. A new branches of science such as genomics consider the biology of drug effects, our research will provide a framework to consider the prescription-persistence cascade.
Professor Harry Hemingway
Dr Amitava Banerjee
Professor Aroon Hingorani
Professor Rob Horne
Professor Anthony Hunter
Dr John Robson
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