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Critical Care and Peri-operative Medicine Research Group

Data Science

There is growing interest in using routinely collected data, and modern data science techniques to explore the outcomes patients experience after surgery, to identify high-risk groups and potential avenues for improvement in their care.



Our Group has studied the epidemiology of surgery extensively, leading and participating in a number of international cohort studies including:



Alongside traditional epidemiological methods, increasingly data driven approaches are being employed by members of the Group. 

Ongoing projects include:

  1. OSIRIS programme - using routinely collected data to explore outcomes after surgery and develop a Bayesian Network based shared decision making tool
  2. Developing novel models of length of stay amongst inpatients
  3. Describing the outcomes experienced in primary and secondary care after surgery
  4. Exploration of the impact of multi-morbidity amongst acute medical patients using locally held healthcare records
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