Health data, turned into decisions.
Clinical instinct.
Technical toolkit.
I trained in clinical sciences in Nigeria, then in health data science at the University of Manchester. I understand what the variables mean, not just how to model them.
I build rigorous, interpretable analysis that clinicians and managers trust, and that actually changes a decision.
More about meCardiovascular, kidney and metabolic disease in North West A&E
A short brief turned into a clinically approved definition and a reusable pipeline. Now supporting an ICB commissioning proposal.
Different problems. One aim.
Analysis that improves how care is planned and delivered.
NHS & operational analytics
Capacity, demand and missed appointments. Analysis managers can act on this quarter.
See projectsHealth inequalities
Clinical coding and fair denominators, so gaps in data are not mistaken for gaps in need.
See projectsClinical machine learning
Interpretable models for triage, screening and pathology that clinicians can trust.
See projectsPipelines & reporting
Reusable SQL pipelines and outputs built in Python that rerun in seconds.
See projects
From the notebook.
The Architecture of Care: Decoding Health Data Quality in the UK vs. the US
Two nations, two philosophies. The UK built a unified data goldmine through the NHS; the US created a fragmented marketplace. What it means for anyone building in health data.
The Automation Imperative: Why "Do Once and Automate" Is a Survival Strategy
Why your first contribution to an NHS Trust will be a script that saves four hours a week, not a deep learning model.
The UK Health Data Business
Who owns the pipes, who moves the money, and why health data scientists should understand the business they work in.