Steve Harris Honorary Associate Professor at the Institute of Health Information and Consultant in Critical Care and Anaesthesia
Organisation: University College London Hospital
- Improvement Science Fellowship
- 4
About me
Steve is an Improvement Science Fellow, Honorary Associate Professor at the Institute of Health Information at University College London, and Consultant in Critical Care and Anaesthesia, University College London Hospital.
He has over 20 years’ experience in general, emergency and tropical medicine. After graduating in clinical medicine from Oxford University, he worked at various London hospitals and led a team of clinicians at a Médecins Sans Frontières hospital in Congo.
Steve’s Wellcome Trust Research Training Fellowship and time as a National Institute for Health Research (NIHR) Clinical Lecturer in Anaesthesia and Intensive Care have given him a strong research background in biostatistics, epidemiology and clinical trials. He designed and implemented the largest observational study of deteriorating patients in NHS hospitals, which won international accolades.
Steve is currently the clinical technical lead for the NIHR Health Informatics Collaborative critical care theme, which is making routine clinical data available to researchers to accelerate improvements in care, and co-lead for a £2.4m programme to build a data science platform at UCLH for the NHS. He has received funding from Wellcome, NIHR, NHS-X, EPSRC, and the Health Foundation. He has more than 25 peer reviewed publications in just the last 3 years including PLOS Medicine and the Lancet.
During his Improvement Science Fellowship, Steve worked on a project to improve the allocation and evaluation of critical care. This involved using existing electronic health records to monitor patients at risk of deterioration outside of intensive care units, enabling health care teams to make decisions on critical care admissions.
‘Phase 1 will build a near future forecasting system for ICU bed occupancy that takes into account the current workload and planned high-risk surgical admissions. Phase 2 will evaluate whether this decreases surgical cancellations, allows fairer allocation of beds and reduces harm by admitting the right patient at the right time’.
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