Predicting postoperative complications in critical care
Research type
Research Study
Full title
Developing Real-Time Predictive Algorithms for Postoperative Complications in Critical Care
IRAS ID
247588
Contact name
Matt-Mouley Bouamrane
Contact email
Sponsor organisation
UNIVERSITY OF STRATHCLYDE
Duration of Study in the UK
2 years, 6 months, 6 days
Research summary
Complications after cardiac surgery are becoming more prevalent. Postoperative complications are a major contributing factor in worsened patients' quality of life after surgery, delayed discharges, and resource usage, in particular with the aging population. These can be improved by optimising perioperative medicine patient care pathways, using data analytics and predictive modelling.
In this project we are linking six databases and analyse the available data in Golden Jubilee National Hospital to develop a real-time algorithm predicting postoperative complications after cardiac surgery, based on vital signs and laboratory results recorded in intensive care unit (ICU). The databases include critical care, cardiac surgery, anaesthetic data, and information on hospital bed management.
ICU is a data rich environment, and utilising this data to predict future outcomes could help simplify decision-making and reduce hospital stay, but also improve patients’ quality of life after surgery.
This is a data science study carried out as a co-operation between the University of Strathclyde and Golden Jubilee National Hospital.REC name
Yorkshire & The Humber - South Yorkshire Research Ethics Committee
REC reference
18/YH/0366
Date of REC Opinion
21 Sep 2018
REC opinion
Further Information Favourable Opinion