Dr Peter Watkinson, Associate Professor of Intensive Care Medicine, is joint clinical lead for the Critical Care Research Group based at the Kadoorie Centre for Critical Care Research & Education at the John Radcliffe Hospital, Oxford.
He is an NHS consultant in intensive care and acute medicine and is part of the senior clinical team at the Oxford University Hospitals NHS Foundation Trust. His research interests focus on the identification of the deteriorating patient in hospital and he has designed and run a number of studies in the field of wearable monitoring devices. The research group is now exploring the opportunities offered through non-contact monitoring and standard electronically-recorded descriptors of a patient's condition.
The research group has a strong link with the University of Oxford Institute of Biomedical Engineering. Using data collected from thousands of patients' vital signs in Oxford and elsewhere the multi-disciplinary team investigates ways to locate patterns which precede and predict clinical deterioration in hospitalised patients.
Other areas of interest for the research group include development of electronic monitoring systems, use of human factors techniques to introduce new technology into the healthcare environment, and assessing the longer-term effects of critical illnesses on patients' quality of life.
Cerebral ischemia during hemodialysis-finding the signal in the noise.
MacEwen C. et al, (2018), Semin Dial, 31, 199 - 203
Critical Care Health Informatics Collaborative (CCHIC): Data, tools and methods for reproducible research: A multi-centre UK intensive care database.
Harris S. et al, (2018), Int J Med Inform, 112, 82 - 89
Artificial intelligence in health care: enabling informed care.
Tarassenko L. and Watkinson P., (2018), Lancet, 391
Outcome of Critically ill Patients Undergoing Mandatory Insulin Therapy Compared to Usual Care Insulin Therapy: Protocol for a Pilot Randomized Controlled Trial.
Watkinson PJ. et al, (2018), JMIR Res Protoc, 7
External validation of the National Early Warning Score 2 (NEWS2) prediction of in-hospital death in patients with type II respiratory failure: a multi-centre database study [protocol]
Watkinson P. et al, (2018)