A new care model using artificial intelligence has been developed at County Durham and Darlington NHS Foundation Trust with health tech supplier C2-Ai, to reduce the number of people with acute kidney injury (AKI).
The AI-driven model includes a predictive AKI risk app at the point of care, combining risk stratification digital tools developed by C2-Ai with new care processes including the recruitment of a new specialist nursing team to provide staff with expert advice and education for staff, patients and carers. Education is also provided for primary care teams to help to prevent unnecessary admissions, and a standardised referral process has been developed for patients requiring specialist renal support.
The trust have observed a reduction in both community and hospital acquired AKI since the introduction of the new model, with overall AKI incidence falling from 6.5 percent between March and May 2020, to 3.8 percent during the same period in 2021. Overall, they say, the project has led to a reduction in hospital acquired AKI of more than 80 percent, from an average of 44 cases per month in 2019/2020 to an average of five cases per month in 2020/2021.
In addition, the project has reported financial gains, estimated at more than £2 million in direct costs from reductions in AKI incidence.
County Durham and Darlington NHS say that the model has the potential to be adopted in hospitals across the NHS.
Claire Stocks, Early Detection, Resuscitation and Mortality Lead Nurse for CDDFT, said that the project has been “very much about using collaborative partnerships to enhance patient safety and quality. An idea that was developed in a ‘cupboard conversation’ is now a fully operational specialist nurse service. Utilising digital innovations supports rapid triage, early detection and treatment to improve outcomes.”
“There has been a big policy emphasis on the importance of data in saving lives in the NHS in recent months,” commented Dr Mark Ratnarajah, a practicing paediatrician and UK Managing Director at C2-Ai. “This project is a prime example of how using technology to give healthcare professionals near real-time and quantifiable risk information, combined with a culture focused on learning and driving forward clinical best practice, can make a big difference to patient safety and ease pressure on busy NHS hospitals.”