Colleges
Conrad Harrison
NIHR Doctoral Research Fellow
I graduated from Imperial College London in 2015 with distinctions in my medical degree and a first class intercalated BSc in neuroscience. I then moved to Oxford where I completed Academic Foundation and Core Surgical Training programmes. I now hold an honorary contract with Oxford University Hospitals as a Specialty Registrar in Plastic and Reconstructive Surgery and have taken time out of clinical training to complete a DPhil (PhD) at the University of Oxford, where I am an NIHR Doctoral Research Fellow and Clarendon Scholar.
I am interested in how we measure the outcomes of reconstructive surgery and what we do with this information. Valid, accurate and interpretable outcome measures are important for studying the effectiveness and cost-effectiveness of different treatments, benchmarking exercises, clinical commissioning, and helping people to make informed decisions about the risks and benefits of surgery.
My research applies contemporary psychometrics and data science to improve the way we measure and interpret the effectiveness and value of healthcare interventions. For example, by developing computerised adaptive tests that can predict patient reported outcome scores from fewer, individualised questions, and exploring the potential for machine learning algorithms to provide clinical decision support. I additionally hold a scholarship at the National Institute for Health and Care Excellence, where I have contributed to evidence review for NHS commissioning decisions.
I am supervised by Prof Dominic Furniss and Prof Jeremy Rodrigues at NDORMS, Mr Marc Swan at the Spires Cleft Centre, and externally by Prof Chris Sidey-Gibbons at the University of Texas. We work closely with teams at the Psychometrics Centre (University of Cambridge), the PROVE Center (Harvard University), and the MD Anderson Center for INSPiRED Cancer Care.
Recent publications
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Machine learning in medicine: a practical introduction to natural language processing
Journal article
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.
Journal article
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.
Journal article
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.
Journal article
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.
Journal article
Singh GV. et al, (2021), Plast reconstr surg, 148, 146e - 147e
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Response to Barriers and Facilitators to the International Implementation of Standardized Outcome Measures in Clinical Cleft Practice.
Journal article
Harrison CJ. et al, (2021), Cleft palate craniofac j