RESPOND Study (Rescue for Emergency Surgery Patients Observed to uNdergo Acute Deterioration)

Patient safety researchers study problems in healthcare systems which harm patients. The investigators wish to study a healthcare situation where system problems are costing lives. In Emergency General Surgery (EGS), dealing mainly with patients with severe abdominal pain, the death rate after abdominal surgery to find out what's wrong (called 'laparotomy') is 5 times higher than for similar routine surgery. Studies of serious complications after major operations show that when patients deteriorate after surgery, their chances of survival depend on how quickly and how well clinical teams react. The investigators plan to analyse how EGS teams currently treat deteriorating patients, and help them develop and test better response systems. Up to 3000 deaths per year could be avoided if these systems were improved . Human Factors science analyses how complex work systems succeed or fail, and how to improve them. The investigators will conduct a Human Factors analysis of real life responses to deterioration in EGS laparotomy patients, examining how staff actually deal with deteriorating patients (referred to as "work as done"), and how this differs from official guidelines (referred to as "work as imagined"). A modern approach to Human Factors called "Safety II" studies both strengths and weaknesses of systems to design solutions. The investigators will use this method to analyse current EGS rescue systems, and develop a new system for managing deterioration, including ways of involving patients or carers effectively. The investigators will test and modify this system until it can be shown that it improves team performance during rescue. Once it appears stable and effective, the investigators will test it in a multi-hospital trial. Hospitals will start using the new system at different dates (decided by chance), and the investigators will compare their performance before and after they start.

The investigators will study the cost-effectiveness of the intervention and analyse what worked well and why, to make sure the lessons are learned effectively.