SITU - Surgical Trials Intervention Unit
Oxford-Berlin Partnership for Enhancing Measurement in Clinical Trials
Colleges
Conrad Harrison
BSc MBBS MBA DPhil MRCS FHEA
NIHR Academic Clinical Fellow in Plastic & Reconstructive Surgery
I am a clinical academic, spending 75% of my time in the NHS as a specialist registrar in plastic and reconstructive surgery, and 25% of my time as a postdoctoral researcher at NDORMS. My work applies data science to improve the way we measure healthcare outcomes. Valid, accurate and interpretable outcome measurement is important for studying the effectiveness and cost-effectiveness of different treatments, and also for benchmarking and quality improvement exercises, clinical commissioning, and helping patients to make informed decisions about their care. My current workstreams include the EMCAT study and the Oxford-Berlin Partnership for Enhancing Measurement in Clinical Trials.
Previously, I studied medicine at Imperial College London before moving to Oxford in 2015 to undertake Academic Foundation and Core Surgical Training programmes. I then completed an NIHR-funded DPhil at Oxford, where I was a Clarendon Scholar. My thesis looked at the potential for modern psychometric techniques (item response theory and computerised adaptive testing) to improve patient-reported outcome measurement in reconstructive surgery. In 2022, I was awarded a Hunterian Professorship from the Royal College of Surgeons of England for my work on surgical outcome measurement more generally. I’m now embedded in the Surgical Intervention Trials Unit within NDORMS, learning how contemporary measurement science might interface with advances in trial methodology. Besides my work on theoretical measurement science, I have also completed an MBA with research into value-based healthcare models within the NHS, and spent time as a scholar at NICE, where I was involved in evidence review for pharmaceutical market access decisions.
Recent publications
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Artificial Intelligence in Fracture Detection: A Systematic Review and Meta-Analysis.
Kuo RYL. et al, (2022), Radiology, 304, 50 - 62
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Machine learning in medicine: a practical introduction to natural language processing
Harrison CJ. and Sidey-Gibbons CJ., (2021), Bmc medical research methodology, 21
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Applying Computerized Adaptive Testing to the FACE-Q Skin Cancer Module: Individualizing Patient-Reported Outcome Measures in Facial Surgery.
Ottenhof MJ. et al, (2021), Plast reconstr surg
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Recursive Partitioning vs Computerized Adaptive Testing to Reduce the Burden of Health Assessments in Cleft Lip and/or Palate: Comparative Simulation Study.
Harrison CJ. et al, (2021), J med internet res, 23
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Automated conversational agents for post-intervention follow-up: a systematic review.
Geoghegan L. et al, (2021), Bjs open, 5
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Long-Term Outcomes after Surgical Treatment of Radial Sensory Nerve Neuromas: Patient-Reported Outcomes and Rate of Secondary Surgery.
Singh GV. et al, (2021), Plast reconstr surg, 148, 146e - 147e