About the reportThe Health Foundation is an independent charity committed to bringing about better health and health care for people in the UK.Health Data Research UK (HDR UK) is the UK's national institute for health data science. HDR UK's mission is to bring together the UK's health and care data to enable discoveries that improve people's lives by uniting, improving and using data as one national institute. HDR UK's Better Care programme aims to equip clinicians and patients in the UK with the best possible data-based information to make decisions about their care. 1 Over the past 2 years, as part of this wider programme, the Health Foundation and HDR UK have been working in partnership to deliver the Better Care Catalyst programme. This has funded three projects to develop data-driven tools that aim to improve health care decision making 2 and also supported three workstreams to set out the training, knowledge mobilisation and policy actions required to support data-driven learning and improvement in health care. This report is the final output of the Better Care Catalyst programme's policy and insights workstream, which researched the barriers and enablers for implementing learning health system approaches in the UK. It supports the wider Better Care programme and community by providing analysis and advice to further the use of data to improve health care services. It also identifies a range of opportunities and actions that policymakers and organisational and system leaders can take to advance the learning health systems agenda across the UK. 3

Nowhere are these concerns more relevant than with health technology and automation, where too often the temptation is to focus on the technology itself rather than on how people use it or experience it. And where too often the temptation is to see the algorithm, the software or the new piece of kit as the answer, rather than as an enabler of change -one that will only help if responding to an accurate diagnosis of what is needed. It is these kinds of issues and concerns that we seek to explore in this report.Switched on: How do we get the best out of automation and AI in health care? 6 Content overviewChapter 1 provides background on automation in health care. It briefly explores the concept of automation, its relationship to AI and robotics, and the impact it could have on the future of work. It also highlights some recent policy responses to automation and AI in the UK, and looks at public and professional attitudes to automation.Chapter 2 considers the types of task most amenable to automation. It then explores some of the different ways in which automation and AI are being applied, or could be applied, in health care, to both clinical and administrative tasks.Chapter 3 looks at the main constraints and challenges that will need to be understood and addressed in order to make the most of automation and AI in health care. These include the challenges of replicating human skills, the indispensability of human agency in certain aspects of health care and the complexity of many kinds of health care tasks. This chapter also explores some challenges of implementing and using automation and AI technologies effectively in practice.Chapter 4 highlights the implications of these constraints and challenges for policymakers, organisation and system leaders, and those leading change on the front line. It reflects on how automation might affect work in health care, explores public and NHS staff views on the benefits and risks of automation in health care, and concludes with recommendations for policymakers, practitioners, organisation and system leaders (including leaders in providers, health boards, integrated care systems, and regional and national bodies) and industry.Switched on: How do we get the best out of automation and AI in health care? 8 *One fact that is often cited is the ongoing growth of the health care workforce. See for example The health care workforce in England: Make or break? The Health Foundation, The King's Fund and the Nuffield Trust; 2018. * Some are concerned by the use of robotic surgery for common surgical procedures with limited evidence and unclear clinical benefit. A recent UK study found no evidence of a difference in 90-day postoperative hospital days between robotic and laparoscopic ventral hernia repair. Sheetz and colleagues argue that the use of robotic surgery has outpaced the generation of evidence to demonstrate its effectiveness.

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