What The F(ederation): Synthesising the many recent data strategies, white papers, and reviews
Updated: Jul 7
Apparently Government strategies that have implications for NHS data are like other public services - namely buses; you wait ages for one and then they all come at once.
The NHS Tech Vision ‘The future of healthcare: our vision for digital, data and technology in health and care’ was published in October 2018 and the NHS Long-Term Plan was published in January 2019. After that, although there were a myriad of ‘individual’ policy documents published, such as the NHSX what good looks like framework and the NHS’s ‘buyer’s guide to AI’, there were no subsequent strategic documents published until the Laura Wade-Gery Review Putting data, digital and tech at the heart of transforming the NHS published in November 2021. Since April of 2022, however, there have been no fewer than 21 major strategic documents, including statutory guidance, published, including:
Better, Broader, Safer: Using Health Data for Research and Analysis ‘The Goldacre Review’ (April 2022)
Announcement of the forthcoming Federated Data Platform tender (April 2022)
Data saves lives: reshaping health and social care with data ‘The Data Strategy’ (June 2022)
The UK Digital Strategy (June 2022)
A plan for digital health and social care (June 2022)
Women’s Health Strategy for England (August 2022)
Our Plan for Patients (September 2022)
Medical Technology Strategy (Feb 2023)
Commercial Clinical Trials in the UK The Lord O’Shaughnessy Review - Final Report (April 2023)
Data Access Policy Update: Proposed Draft (May 2023)
NHS England’s Protection of Patient Data (May 2023)
NHS Long Term Workforce Plan (June 2023).
This dramatic increase reflects a shift in the attitude of central policymakers regarding the role data (and data-driven technologies) plays in the everyday operation of the NHS and its longer-term future. Where data was once an 'exhaust' or byproduct of the service, it is now central to all activities from direct patient care to the NHS's participation in global health initiatives. The fact that priority 3 in the NHS's 2023 mandate is "Deliver recovery through the use of data and technology", makes this centrality clear:
"It is also crucial that the NHS makes progress in adopting the latest innovation and technology to digitally transform the NHS and help to ensure its long-term sustainability. The system must utilise the power of technology and the skills, leadership and culture that underpins it, to drive a new era of digital transformation. This will allow the health and care system to thrive long into the future, delivering vast benefits for patients - such as using AI to give better treatment, the latest screening techniques to detect illness sooner and equipment that allows more people to be treated at home. We know that there is significant variation in performance on electives, urgent and emergency care, and primary care. NHS England should continue to prioritise tackling variation, supporting digital transformation in areas where there is greatest challenge. To support digital transformation, it is vital that staff have the skills and resources to implement and utilise new digital tools effectively to deliver high quality services for patients."
Similarly, 'data science' is now viewed as a priority cross-cutting methodology for all of the Department of Health and Social Care's research priorities and digital and data feature prominently in the long-term workforce plan:
"To meet the changing healthcare needs of the population in a cost-effective way, the NHS workforce will need to take full advantage of digital and technological innovations [including AI]. "
More broadly, this apparent increase in interest in data from health and social care policymakers, reflects a broader Government-wide ambition to become a 'science and technology superpower. This is an ambition that is particularly focused on encouraging the development and adoption of AI technologies as evidence by the recent raft of publications designed to make the development, deployment, and use of AI technologies in the UK easier:
A pro-innovation approach to AI regulation (March 2023)
Pro-innovation Regulation of Technologies Review: Digital Technologies The Vallance Review (March 2023)
The UK Science and Technology Framework (March 2023)
The challenge for those who are interested in this area of policy development is that, collectively these documents represent hundreds of pages, thousands of words, an uncountable number of recommendations, and millions of public pounds. This makes paying attention to the very rapid evolution of NHS-data-relevant policy a little overwhelming, as it has become very hard to 'see the wood for the trees.' To help with this overwhelm, therefore, I have - in what follows - attempted to bring these various documents together and summarise the overarching, strategic direction and implications for NHS data.
Four Use Cases, Four Goals, and Four Themes
The starting point for understanding how all these myriad documents fit together (and sometimes diverge from each other), is recognising that at a strategic and high level of abstraction, the UK Government (particularly the NHS Transformation Directorate) views NHS data as having four disparate uses:
Managing Population Health
Planning NHS Services
Research (and Innovation)
There are a number of reasons why I personally believe these divisions are somewhat arbitrary and unhelpful, but I will not go into that here. For the purpose of this blog, it is simply necessary to understand that the various strategic documents listed above treat each of these use cases as separate, and thus policy commitments covering one use case do not necessarily cover the other commitments.
As set out in the Plan for Digital Health and Social Care, it is hoped that by combining these four use cases, the Government can equip the health and care system to:
Prevent people’s health and social care needs from escalating
Personalise health and social care and reduce health disparities
Improve the experience and impact of people providing services
These are extremely ambitious goals (I will not comment here on their deliverability) and so, to break them down, the various documents make commitments/recommendations at lower levels of abstraction that, in theory, will enable the delivery of these goals. Although these commitments/recommendations are numerous, it is possible to see them as being grouped into four themes:
Platforms, Privacy and Security
Ethics, Participation and Trust
Workforce and Ways of Working
Combining these four themes with the four use cases can be used to create a map to help us navigate through the dense foliage of the aforementioned wood.
Goal: Use data to enable integrated and joined-up care.
Aim: Ensure the right information is available for the right person at the right time.
This will be achieved by:
Reducing the number of individual data collections
Making more detailed individual-level data available from central sources
Making this feasible by increasing the reliance on cloud infrastructure rather than physical databases
Improve the cybersecurity provisions of these centralised data sources
Further enhancing the resilience and protection of these centrals stores by improving the information governance training of frontline staff
Improving the ways in which frontline staff use data for decision-making by:
providing them with decision-support-tools; and
making the workforce more data literate
Specifically the following commitments/recommendations are made (verbatim text - you might need to zoom!):
Goal: Use data for public health surveillance
Aim: Ensure the health and care system as a whole can predict, prevent, and (if necessary) respond to threats to public health.
This will be achieved by:
Providing regional health and care teams (ICSs mostly) with access to all health and care data for the people they are responsible for caring for via accessible and secure real-time platforms
Providing regional staff with the skills and knowledge to analyse the data available to them
Requiring regional analytical teams to openly share their analytic code so that specific analyses can be done in the same way in multiple locations
Creating an underpinning technical architecture that enables the combining of analytical results from multiple regions when it is necessary to gain a whole-population perspective
Revising information governance requirements so that sharing for the purposes of planning is not blocked by monopolistic behaviour of multiple data controllers
Specifically the following commitments/recommendations are made (verbatim text):
Goal: Use data for the effective and efficient commissioning and monitoring of services.
Aim: ensure the right services are provided in the right geographical locations; providers are paid for the services they provide; and unwarranted variations in care are detected and investigated.
This will be achieved by:
Reducing the number of individual data collections
Providing central analytics teams with access to aggregate performance data via secure data environments
Providing central analytics teams with the skills and knowledge to analyse the data available to them
Providing senior management with data literacy training to enable them to be ‘smart customers’ of data
Ensuring data is used for performance management in a way that is sensible and acceptable to both publics and professionals
Requiring central analytics teams to openly share their analytic code so that specific analyses can be done in the same way in multiple locations; and so all analytic code can be inspected for errors
Revising information governance requirements so that sharing for the purposes of planning is not blocked by monopolistic behaviour
Put in place standards and mechanisms that ensure transparency of data use for analytical purposes
Specifically the following commitments are made (verbatim text - you might need to zoom!):
Goal: Use data to analyse patterns of disease; identify new treatments; monitor the efficacy and safety of existing treatments; drive innovation; and more.
Aim: ensure researchers can access NHS data to conduct lifesaving research without compromising patient privacy and public trust.
This will be achieved by:
Reducing the extent to which the system relies on providing researchers with access to data via insecure ‘Pseudonymise and Disseminate’ methods
Providing researchers with access to population-level datasets via accredited ‘Trusted Research Environments’ (referred to as Secure Data Environments in Data Saves Lives) that meet a set of minimum technical specifications regarding privacy protection, governance, and open working
Simplifying Information Governance, once Trusted Research Environments are in place, to ensure it does not act as a barrier to life-saving research and innovation but continues to provide appropriate scrutiny regarding purpose of research
Upskilling the academic workforce to work in modern, open, computational ways so that all research code is shared openly for scrutiny and re-use
Funding research into the development of secure analytical platforms, and code and methodological innovation for data curation, privacy preservation, and more
Putting in place standards and contractual requirements for those looking to use NHS data for commercial purposes to ensure a fair return on investment, and public acceptability
Improving the quality of ‘Patient and Public Involvement and Engagement’ activity conducted by researchers
Putting in place standards and mechanisms that ensure meaningful public transparency over data use for research purposes
Specifically the following commitments/recommendations are made (verbatim text - you might need to zoom! ):
Once the information, recommendations, and commitments in each of the myriad documents has been synthesised in this way it becomes clear that, even if the exact nature of how varies between the four data use cases, the what of the overarching strategic aims remains fairly consistent throughout:
Reduce the number of places data is collected, stored, and disseminated.
Instead ensure it is made accessible to trusted individuals, teams, organisations, and businesses (where appropriate) via a smaller number of secure, performant platforms that provide greater privacy and security protection.
Upskill the clinical, analytical, academic, and senior management communities to ensure they are all capable of working in a modern, open, collaborative fashion and all have the required digital and data literacy.
Put in place legislation, standards, and mechanisms that ensure NHS data cannot be monopolised and is instead made readily accessible (in a secure fashion) for those who need it to provide care; monitor population health; manage & plan services; and conduct high-quality research.
Put in place legislation, standards, and mechanisms that ensure meaningful transparency and accountability over how data is used - particularly for secondary purposes.
Standardise the ways in which patients and publics are informed and involved in all uses of NHS data to ensure all uses are socially acceptable as well as legally com
Of course there are some areas where the how of one use case appears to contradict with the how of another. Similarly, there are some areas where the how is more detailed than others. This is natural, and to be expected, when an extremely important area of policy is undergoing such a rapid and intense period of development and change. The important thing is that at least we now know where we are going.