Professional background

Steve Harris is a principal research fellow in Translational Data Science at UCL, a consultant in critical care, and the Chief Research Information Officer at the UCLH NIHR Biomedical Research Centre.

He has held fellowships from Wellcome, and the Health Foundation, and won more than £10m in grant funding.

He is co-director of the Central London NIHR Patient Safety Research Collaborative, and co-investigator for CHIMERA, the Wellcome Innovation Flagship Critical Care Asia, and co-leads the NIHR Health Informatics Collaborative for Critical Care.

At UCLH, he led the implementation of the Experimental Medicine Application Platform (EMAP) and FlowEHR that aim to bridge the 'AI chasm', and deliver algorithms and inference to the bedside.

Research interests

Dr Harris uses observational clinical datasets to answer questions about treatment efficacy that cannot be addressed experimentally (via randomised controlled trials).

He leads a Translational Data Science lab group at at UCL's Institute of Health Informatics, and founded 'Data Science for Doctors' in 2015. He also co-leads the NIHR Critical Care Health Informatics Collaborative programme for the BRC, and UCLH's Experimental Medicine Application Platform.

Publications

Selected publications in the last 5 years

  • Arulkumaran N, Wright T, Harris S, Singer M (2020) Uncontrolled interventions during pandemics: a missed learning opportunity. Intensive Care Med
  • Banerjee A, Pasea L, Harris S, Gonzalez-Izquierdo A, Torralbo A, Shallcross L et al. (2020) Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study. Lancet 395: 1715-1725.
  • Krishnamoorthy V, Wong DJN, Wilson M, Raghunathan K, Ohnuma T, McLean D et al. (2020) Causal inference in perioperative medicine observational research: part 1, a graphical introduction. Br J Anaesth
  • Palmer E, Post B, Klapaukh R, Marra G, MacCallum NS, Brealey D et al. (2019) The Association between Supraphysiologic Arterial Oxygen Levels and Mortality in Critically Ill Patients. A Multicenter Observational Cohort Study. Am J Respir Crit Care Med 200: 1373-1380.
  • Wong DJN, Popham S, Wilson AM, Barneto LM, Lindsay HA, Farmer L et al. (2019) Postoperative critical care and high-acuity care provision in the United Kingdom, Australia, and New Zealand. Br J Anaesth 122: 460-469.
  • Grieve R, O’Neill S, Basu A, Keele L, Rowan KM, Harris S (2019) Analysis of Benefit of Intensive Care Unit Transfer for Deteriorating Ward Patients: A Patient-Centered Approach to Clinical Evaluation. JAMA Netw Open 2: e187704.
  • Harris S, Singer M, Sanderson C, Grieve R, Harrison D, Rowan K (2018) Impact on mortality of prompt admission to critical care for deteriorating ward patients: an instrumental variable analysis using critical care bed strain. Intensive Care Medicine 44: 606-615.
  • Harris S, Shi S, Brealey D, MacCallum NS, Denaxas S, Perez-Suarez D et al. (2018) Critical Care Health Informatics Collaborative (CCHIC): Data, tools and methods for reproducible research: A multi-centre UK intensive care database. Int J Med Inform 112: 82-89.
  • Wong DJN, Harris SK, Moonesinghe SR, SNAP-2: EPICCSC, Health Services Research Centre NIOAA, Study SG et al. (2018) Cancelled operations: a 7-day cohort study of planned adult inpatient surgery in 245 UK National Health Service hospitals. Br J Anaesth 121: 730-738.
  • Moonesinghe SR, Wong DJN, Farmer L, Shawyer R, Myles PS, Harris SK et al. (2017) SNAP-2 EPICCS: the second Sprint National Anaesthesia Project-EPIdemiology of Critical Care after Surgery: protocol for an international observational cohort study. BMJ Open 7: e017690.
  • Harris SK, Lewington AJ, Harrison DA, Rowan KM (2015) Relationship between patients’ outcomes and the changes in serum creatinine and urine output and RIFLE classification in a large critical care cohort database. Kidney Int 88: 369-377.