A third-year PhD student and Health Data Scientist, specialising in developing clinical decision-support tools. I use predictive analytics to provide health experts with actionable insights for care pathways in primary and secondary care services. Possessing a fair amount of experience in collaboration with health and care providers across NHS Scotland, I aim to provide solutions that can contribute to better quality of life for burdened patients and better resource management in care settings.

My current interests lie in the field of Population Health Data Science, more specifically, analysis of care pathways, risk prediction and resource management in complex patients. This includes, but is not limited to older, multimorbid, frail groups and COVID-19 related conditions. Throughout the years, I’ve been primarily involved with incorporating Electronic Health Record (EHR) data collected from hospitals and emergency care services for determining risk trajectories and unmet clinical needs. The current work of my PhD is focused on developing an EHR-based risk score for rehabilitation complexity in older patients, estimated through novel NHS Lothian data describing received multidisciplinary and out-of-hours specialist care. As a Health Data Scientist, I use Machine Learning techniques (e.g. Ensemble Learning) to predict hospital mortality, readmission and adverse events in time-sensitive cohorts (e.g. diabetes and hip fracture patients). Additionally, I have some experience in the field of Explainable AI (XAI), specifically for adapting Process Mining techniques to explore care patterns and abnormal behaviour in sub-populations, as well as identifying important model predictors.