Overview

Cohort: 6
PhD start date: August 2022

I have been committed to pursuing a combined clinical and academic career since early in medical school.

As a second-year undergraduate at the University of Leeds, I was awarded an EXSEL Scholarship (sponsored by Heart Research UK) to undertake a research project in cardiovascular pharmacogenetics. I was inspired to complete an intercalated degree (BSc Clinical Sciences, sponsored by the Wolfson Foundation), for which I was awarded First Class Honours and the Willis Prize. I completed my undergraduate medical training in 2014, graduating with Honours, followed by a cardiology-themed Academic Foundation Program in Newcastle upon Tyne.

In 2016 I was awarded a Knox Memorial Fellowship from Harvard University, enabling me to pursue a Master of Public Health (MPH) degree at the Harvard T.H. Chan School of Public Health, with a concentration in Quantitative Methods (Biostatistics and Epidemiology). Following this, I returned to the UK and completed Core Medical Training, becoming a Member of the Royal College of Physicians in 2018 and gaining the Diploma in Geriatric Medicine in 2019. I was subsequently awarded my National Training Number in Cardiology in the Northern Deanery.

Early in cardiology training, I recognised the need for clinicians to have greater understanding of the application of data science and machine learning algorithms to diverse healthcare data and as such, embarked upon a BSc (Hons) in Computer Science (with a concentration in Data Science) alongside cardiology registrar training, for which I completed and was awarded First Class Honours in 2022.

PhD title

Multimorbidity and myocardial infarction: an investigation using linked, routinely collected health record data.

Brief summary of PhD project

My PhD project is focussed on developing actionable clinical insights regarding the impact of multimorbidity on clinical treatment responses and clinical outcomes in patients with acute myocardial infarction. During my PhD, I will apply advanced analytic methods to a large volume of routinely-collected, linked patient data from the Clinical Practice Research Datalink (CPRD), Hospital Episode Statistics (HES) and Office for National Statistics (ONS) datasets.

Key collaborators/supervisors

• Dr Marlous Hall (University of Leeds)
• Dr Ben Brown (The University of Manchester)
• Dr Mark Kearney (University of Leeds)

Specialty interest/techniques

My primary clinical and academic focus is to improve the prevention, diagnosis and management of myocardial infarction. During my PhD, I will gain an understanding of how machine learning algorithms and advanced statistical methods can be applied to derive insights from routinely-collected clinical data.

Career aspirations

My ultimate ambition is to become an academic interventional cardiologist. I wish to lead my own research group, focussed on using routinely-collected healthcare data to build tools that aid clinicians in their decision-making and lead to improved patient outcomes.

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