Matthew is a doctor by background, and is taking time out of his clinical training to pursue further research. He completed my MBBS at King’s College London and undertook an intercalated BMedSci at Sheffield University where he investigated the role of coronary physiology in bystander disease in patients suffering a heart attack. He recently completed an NIHR-funded specialised foundation programme. During this time he used linked electronic health records and social care data to identify and characterise a new cohort of care home residents. This cohort will improve our understanding of this hard-to-reach population.
Project Information
Research Driver Programme: Medicines in Acute and Chronic Care
Project Title: Addressing anticholinergic burden in the secondary care setting
Summary:
Older adults are more likely to be living with multiple long-term conditions, for which they will be taking multiple medications (polypharmacy). Whilst these medication will provide benefits, they also carry a risk of side-effects which older adults, particularly those living with frailty, are more vulnerable to. In order to make informed decisions on starting or stopping medication, we need to identify those individuals who are at a high risk of suffering adverse effects from taking multiple medications. The aim of the project is to use routinely collected hospital data to develop a risk stratification tool which will identify individuals admitted to hospital at risk of adverse effects from their medication.
What inspired you to pursue this project and how will HDR UK funding benefit your work?
As a hospital doctor, I see the burden of polypharmacy on a daily basis and the devastating impact delirium and falls can have a patient’s trajectory. Decisions on whether to stop or start medication require a discussion around the potential benefits and risks. However, the current tools available to identify those at high risk of suffering side-effects from medication are not widely used because they are not integrated into our electronic prescribing systems, are not based on outcomes and do not account for a patient’s co-morbidities.
I hope that by developing a tool which identifies those taking a potentially harmful combination of mediation and those most likely to suffer a harm as a result, it will provide clinicians and patients with the necessary information to facilitate shared decision making on starting/stopping medication. The funding from the UK HDR Clinical Doctoral Fellowship will give me the time and training to develop a model. It will provide with the funding to develop my skills in prognostic research and health data science so that I can become a future leader in health data science.
