Researchers have harnessed Artificial Intelligence (AI) to improve a tool currently used in emergency departments across Scotland to identify individuals at high risk of needing urgent hospital care within the next year.
Emergency hospital admissions routinely account for around half of all hospital stays in Scotland, placing tremendous strain on the healthcare system. Researchers from the Universities of Edinburgh and Durham, supported by Health Data Research UK (HDR UK) and The Alan Turing Institute, worked with Public Health Scotland to develop an improved tool to help manage this growing issue.
Published in npj Digital Medicine, the team demonstrates that SPARRAv4 – Scottish Patients At Risk of Readmission and Admission version 4 – is better able to identify emergency admissions than the previous version. SPARRAv4 was also found to be better at gauging individual patients’ level of risk of needing urgent hospital care.
The AI-powered update will help healthcare providers in Scotland plan more effectively for emergency cases and manage healthcare resources more efficiently.
Dr Catalina Vallejos, Reader at the University of Edinburgh’s MRC Human Genetics Unit, said: “In an era where healthcare systems are under high stress, we hope that the availability of robust and reproducible risk prediction scores such as SPARRAv4 will contribute to the design of proactive interventions that reduce pressures on healthcare systems and improve healthy life expectancy.”