
About
David Jenkins is a Lecturer in Health Data Science at the University of Manchester's Division of Informatics, Imaging & Data Sciences. His work focuses on clinical prediction models, opioid-associated adverse events, and musculoskeletal disease outcomes. He holds a PhD in Dynamic Modelling Methods for Clinical Prediction Model Updating (2022), an MSc in Statistics (2014), and a BSc in Mathematics (2014).
His research explores AI-driven solutions for improving healthcare decision-making, with particular emphasis on stroke triage, opioid risk stratification, and diabetes comorbidity analysis. Notable collaborations include work with the Christabel Pankhurst Institute and Digital Futures initiative. Jenkins leads projects like 'Drug-repurposing thiazolidinediones for vascular dementia' (2024–2025) and actively supervises PhD candidates in clinical prediction modelling.
Recent studies highlight trends in opioid prescribing among rheumatology patients, prehospital stroke diagnosis innovations, and SARS-CoV-2 impact on diabetes patients. His work aligns with UN SDG 3 (Good Health & Well-being) through advancing equitable healthcare through predictive analytics.
Key contributions include over 40 peer-reviewed publications, methodological advancements in dynamic prediction models, and evidence-based guidelines for opioid risk mitigation. He collaborates with NHS Greater Manchester on prehospital stroke protocols and leads national-level epidemiological analyses of chronic disease outcomes.
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