Oliver Redfern
BSc PhD MBBS
Clinical Researcher
Oliver is a post-doctoral researcher in the Critical Care Research Group (CCRG), based in the Kadoorie centre. His primary research interest is in developing effective systems to identify and optimise the management of patients who acutely deteriorate on hospital wards.
He works on the Hospital Alerting via Electronic Noticeboard (HAVEN), which uses statistical and machine learning techniques to improve the identification of deteriorating patients. He also leads the statistical modelling workstream for an NIHR-funded project to derive evidence-based protocols for vital sign monitoring in hospitals.
Prior to working in the CCRG, Oliver undertook a PhD and post-doctoral work in protein bioinformatics with Professor Christine Orengo FRS at University College London. He then trained in medicine at the University of London before completing foundation training in south London. After working in clinical outcomes research at the University of Portsmouth, he joined the CCRG in June 2018.
Key publications
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Journal article
Pimentel MAF. et al, (2021), American Journal of Respiratory and Critical Care Medicine
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Journal article
Griffiths P. et al, (2019), BMJ Quality & Safety, 28, 609 - 617
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Journal article
Redfern OC. et al, (2018), Resuscitation, 133, 75 - 81
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Journal article
Redfern OC. et al, (2019), BMJ Open, 9, e032157 - e032157
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Journal article
Pimentel MAF. et al, (2019), Resuscitation, 134, 147 - 156
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Journal article
Dall’Ora C. et al, (2019), Journal of Nursing Management, 27, 19 - 26
Recent publications
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Preprint
Rison SCG. et al, (2023)
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Journal article
Rison S. et al, (2023), British Journal of General Practice, BJGP.2023.0077 - BJGP.2023.0077
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Journal article
WATKINSON P., (2023), Safer and more efficient vital signs monitoring to identify the deteriorating patient: An observational study towards deriving evidence-based protocols for patient surveillance on the general hospital ward
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Preprint
Vollam S. et al, (2023)
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Preprint
Rison S. et al, (2023)
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Journal article
Harford M. et al, (2022), Physiological Measurement, 43, 115001 - 115001