Title: Evaluating the safety and patient impact of an Artificial Intelligence Command Centre in the UK National Health Service
Funder: Department of Health and Social Care

Abstract: Background _x000D_ In most UK NHS hospitals the operational planning of health service delivery is fragmented across multiple departments and services with major implications for patient safety, efficiency and good patient care. The UK is making major strategic investments in digital health technologies such as artificial intelligence (AI) in the belief this will lead to major improvements in health services delivery. There is however very limited research on the impact of such large and complex digital interventions in our hospitals to inform the major investments that are being made. _x000D_ _x000D_ Our proposal directly addresses this evidence gap by conducting a scientifically rigorous, in-depth study of one of most ambitious initiatives in the UK NHS, an “AI Command Centre” which is being implemented in a large 800 bed NHS hospital in Bradford. It has been presented at NHS Expo 2019, to the Secretary of State for Health and to the NHS, patients and public as the “first of type” in Europe. Similar to an air traffic control command centre, hospital staff at Bradford now work together in a purpose built operations room and monitor a ‘wall of analytics’ of high definition screens that display real-time data from the hospital’s information systems. The system will use AI to create algorithms that intelligently alert the team to urgent issues such as a deteriorating patient who has not received the required support, where bottlenecks might occur and where performance and safety breaches are predicted. _x000D_ _x000D_ The effectiveness of such a system and the implications for patient safety, care quality and patient and public opinion are largely unknown in the UK but there are huge opportunities for better, safer care in our hospitals. _x000D_ _x000D_ Aims of the research _x000D_ We aim to understand how the AI Command Centre impacts on the quality, safety and organisation at Bradford to generate findings that can be applied to other hospitals in the UK. _x000D_ _x000D_ Design and methods _x000D_ Our team in the NIHR Yorkshire & Humber Patient Safety Translational Research Centre (Y&H PSTRC) are based in Bradford and in a unique position to study the evidence. We will combine a range of methods to measure trends in patient care, safety and outcomes with the implementation of the Command Centre. We will compare these trends with those of a similar hospital without a command centre to understand how command centre technologies can improve the quality, safety and organisation of NHS hospitals. _x000D_ _x000D_ Patient and Public Involvement _x000D_ We have an established network of Patient and Public Involvement (PPIE). They helped us shape this proposal and will help us maintain a strong patient perspective. We recognise that patients may be very concerned about how AI technologies might affect their care and we will explore this and other concerns through patient focused workshops. Our PPIE lay leader is a co-applicant for this bid and a member of our project management team. _x000D_ _x000D_ Dissemination _x000D_ We will work with our PPIE representatives to communicate the progress and findings of the work to a wider audience. We will run workshops with volunteers to ensure the findings from this work are represented in an accessible format to share through patient and public networks. We will also produce academic papers, a report to inform commissioning decisions by senior management in other NHS hospitals. Our work will also be used to inform the developers on design feedback and risk factors for patient safety.

Lay abstract: Background:_x000D_ Command centres in safety critical industries are well-evolved and linked to reliability, resilience and shared situational awareness for operational control. In the safety sciences, studies of High Reliability Organisations (HRO’s), such as nuclear power plants and air traffic control systems, demonstrate how safety can be maintained in the face of dynamic risks and organisational complexity [1, 2]. In most National Health Service (NHS) hospitals the operational planning of health service delivery is fragmented, rather than integrated, and investment in digital health technologies with advanced capabilities, such as artificial intelligence (AI), is limited. Our proposal directly addresses this evidence gap by conducting a scientifically rigorous study of an ambitious initiative to implement an “AI Command Centre” in a large 800-bed NHS hospital in Bradford._x000D_ _x000D_ Research aims:_x000D_ Our proposed research objective is to conduct a robust evaluation of the impact of a novel AI Command Centre (CC) on patient safety, operational efficiency and organisational outcomes, within an acute care setting. We hypothesise that the command centre will improve patient flow, reduce bottlenecks and delays, enhance situational awareness to support operational decision-making and facilitate identification and timely mitigation of threats to patient safety._x000D_ _x000D_ Methods:_x000D_ We propose a mixed-method evaluation, incorporating quasi-experimental and longitudinal qualitative research in order to understand processes and outcomes linked to implementation of the Command Centre at our experimental site (Bradford Teaching Hospitals NHS Foundation Trust), compared with a control. The quasi-experimental study will employ Interrupted Time Series Analysis to analyse variation in patient safety, patient flow and data quality. The qualitative component will employ ethnographic methods both within the CC itself and in the broader care system from governance to frontline level, along with a longitudinal process evaluation based upon stakeholder and user interviews. In order to contextualise the findings and inform the data synthesis, a cross-sector and cross-industry review of data-driven command and control systems and processes will be conducted, based upon literature review, consultation with an expert panel and a survey of Hospital Chief Information Officers in the NHS._x000D_ _x000D_ Timelines for delivery:_x000D_ The project will be delivered over an 18 month period. Ethnography and qualitative work will take place from months 1 – 12. Data extraction and analysis for the quasi-experimental analysis of patient safety and patient flow outcomes will be staggered from month 7 – 15. Comprehensive data synthesis across work streams will occur from month 13, along with dissemination of findings. _x000D_ _x000D_ Impact and dissemination:_x000D_ In addition to academic outputs in peer reviewed publications and international forums, we will share learning concerning the costs-benefit of investment in hospital command centre technology, within NHS management and Chief Information Officer networks and will construct an empirically-informed implementation framework to facilitate knowledge transfer and support future implementations.

Research activity codes: 7.1 INDIVIDUAL CARE NEEDS;8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: GENERIC HEALTH RELEVANCE