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Report
Description

This report offers in-depth analysis into the challenges and potential presented by automation and AI in health care and highlights wider implications for the future, setting out considerations for policymakers and the NHS. As well as describing some of the most promising areas of application of automation and AI to health care, the report also explores the challenges, constraints and practical considerations for making the most of automation and AI. The report goes beyond simply considering their potential, to engaging with what it will take to realise the long-term benefits for patients, the public and NHS staff.

Key points:

  • Informed by YouGov online surveys of more than 4,000 UK adults and more than 1,000 NHS staff, the report finds that while automation and AI hold huge potential for improving care and supporting the NHS to increase its productivity, in developing and deploying them we must be careful not to squeeze out the human dimension of health care, and must support the health and care workforce to adapt to and shape technological change.
  • Health care is a service that is fundamentally co-produced between patients and clinicians, making the human, relational dimension critically important to the quality of care. Given the nature of work in health care is different to many other industries, the impact of these technologies on work will also tend to be different. In many cases, automation and AI technologies will be deployed to support rather than replace workers, potentially improving the quality of work rather than threatening it.
  • The benefits of a new technology don’t come from how it performs in isolation, but from fitting it successfully into a live health care setting and redesigning ways of working for maximum gain. Teams and organisations will need to consider the human infrastructure and processes needed to accompany the technology, and policymakers and system leaders will need to fund ‘the change’ – not just 'the tech'.
Publication Details
DOI:
10.37829/HF-2021-I03
ISBN:
978-1-911615-58-3
License type:
All Rights Reserved
Access Rights Type:
open