Title: SMARTT Critical Care Pathways - (Safe, Machine Assisted, Real Time Transfer) An artificial intelligence based decision support tool to enable safer and more timely critical care transfer
Funder: Department of Health and Social Care

Abstract: Background: With an approximate cost of &pound;2000 per bed per day for ICU patients and no evidence of consistent guidance between or within sites for when a patient is ready to be discharged back to the ward, there is an urgent need for better use of routine data to support discharge decisions. We have been working on this problem for several years and are ready to design and integrate a smart dashboard into the ICU. Aims and Objectives: To refine the discharge algorithm and develop a product, tested across multiple NHS sites, with data on clinical safety, efficacy and with a strategy for commercialisation. Project Plan and methods used: There are 5 work packages including, governance, core algorithm development, back end development and infrastructure, user-centric design, and testing and evaluation. Timeline for delivery: 36 months Anticipated impact and dissemination: The use of a dashboard with AI enabled decision support to improve the co-ordination and delivery of timely discharge information will Improve system efficiency by ensuring resource use in the critical care pathway is optimised. Patients that are suitable for discharge to the ward will leave sooner freeing up more ICU beds for patients that need them. Improve the safety of ICU patients by ensuring only those ready to be discharged are considered, reducing ICU readmission rates. Reduce cognitive stress on staff within the ICU and free up time for direct patient care rather than wasting time coordinating and administrating multiple steps in the discharge pathway. We are uniquely placed to scale this solution across an entire health system with 3 acute hospitals working very closely at a clinical, technical and research level to deliver optimal ICU pathways. From here we will have a strong case to scale further across our regional network and throughout the NHS.

Lay abstract: The NHS is under strain and more people than ever need intensive care. This research will help us make better use of our precious critical care beds. We will develop and test an artificial intelligence tool that will help us work out who is well enough to leave intensive care. Our tool will free-up bed spaces faster and ensure we keep patients in intensive care until they are well enough to leave. This will improve the safety and health of patients and help hospitals run more efficiently. Intensive care doctors make hundreds of difficult decisions every day. Deciding if someone can leave intensive care is just one of these critical decisions. Unfortunately, doctors can t always make this decision right away, and they often get it wrong due to all the other demands on their time and brain power. This means around a quarter of patients stay in intensive care for too long or not long enough. Monitors and blood tests provide thousands of pieces of information about each patient. Over several years we have formed a team of doctors and scientists to develop artificial intelligence technology that takes this information and works out when patients are ready to be discharged. We have shown that this method performs better than humans can. In this project we plan to improve this artificial intelligence solution and test it in a real intensive care unit. We will create a tool for hospital staff that displays a constantly updated and reliable list of patients who are fit to be discharged. Artificial intelligence is very new in hospitals and we need to understand how patients feel about doctors and nurses using it to look after them. Patients may worry about computers having their health information and making decisions about their care. To ensure that our work is people-focused, we will set up a panel of patients to oversee the project and provide feedback at all stages. Some doctors and nurses may also be worried about a change to their practice. We will work with them to make sure the technology is well-suited to their working environments. This technology will improve the use of intensive care beds, help NHS staff in their high-pressured work and save lives. Starting with two local NHS trusts, our ultimate goal is to get this tool to doctors and nurses in intensive care wards across the country.

Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: GENERIC HEALTH RELEVANCE