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Chapter 1: Modernising NHS Service Analytics

Professional Structures

NHSA 1. Create an NHS analyst service modelled on GES, GSS, GORS
NHSA 2. Create clear job descriptions for NHS analysts at a range of levels
NHSA 3. Revise Agenda for Change, and ensure technical staff are paid realistic salaries
NHSA 4. Support an NHS analyst community
NHSA 5. Develop an annual data conference for NHS service analysts
NHSA 6. Find good staff, and empower them quickly with ‘data pioneer’ fellowships
NHSA 7. Identify 3 ‘data pioneer’ analytics teams in ICSs and trusts
NHSA 8. Commission intermittent code and analysis audits of organisations and analyst teams for service improvement
NHSA 9. Create an Analytical Capability Index

Training

NHSA 10. Create an Open College for NHS Service Analysts
NHSA 11. Devise the content of a national training programme for NHS analysts: initial and CPD
NHSA 12. Oversee funding and delivery of training, both open online and one-to-one
NHSA 13. Establish new core training for analysts
NHSA 14. Outline clear, non-onerous CPD training requirements for analysts
NHSA 15. Embrace RAP and modern, open working methods
NHSA 16. Ensure training focuses on RAP as much as Machine Learning
NHSA 17. Create a technical team to house and develop continuing professional development resources
NHSA 18. Ensure all training is open by default
NHSA 19. Create and maintain a curated national open library of NHS analyst code
NHSA 20. Create training specifically for senior leaders to help them become better customers for data analysis
NHSA 21. Commission a rapid review of medical school curricula and similar

Platforms and data access

NHSA 22. Improve the provision of data analysis environments
NHSA 23. Revise NHS IT policy for analysts to ensure it is fit for purpose
NHSA 24. Rationalise national audits, RightCare, GIRFT, and Model Health System
NHSA 25. Make change practical

External collaborations

NHSA 26. Commission and promote best practice on outsourcing analytics
NHSA 27. Require all outsourced or external work to comply with RAP and open working methods
NHSA 28. Support NHS/academic collaborations on RAP data science for NHS service improvement

Chapter 2: Open Working

Establish clear expectations around RAP and open code for the whole system

Open 1. Create a RAP and Open Code Oversight Group
Open 2. Create a public policy setting out expectations on open code
Open 3. Make open code a boilerplate feature of all public contracts
Open 4. Create an ‘exceptions framework’ whereby publicly funded code can be closed by prior arrangement if this meets NHS and UKplc strategic objectives
Open 5. Create an Open Code Ombudsman and Assistance Unit
Open 6. Assert that publicly funded code is publicly owned: cautiously consider ‘Crown Copyright for code’
Open 7. Data Controllers should require RAP and open code sharing from data users
Open 8. Amend the Code of Practice for the Research Powers of the Digital Economy Act
Open 9. Make it ‘okay to ask’ about access to publicly funded code

Develop Guidance on Open Code from Specific Key Organisations

Open 10. Health and Care Information Governance Panel guidance should facilitate open code
Open 11. The Information Commissioner’s Office should produce guidance to facilitate code sharing
Open 12. The Medicines and Healthcare products Regulatory Agency should address code sharing and device regulation
Open 13. Negotiate co-ownership of claimed commercial innovations from NHS data

Support NHS service analysts to work with RAP and open methods

Open 14. Write an ‘open analytics policy for the NHS’
Open 15. Make open a standard contractual requirement
Open 16. Commission intermittent open code audits to drive improvement
Open 17. Establish a technical writing and documentation team for the NHS

Build workforce capacity for RAP and modern, open, collaborative working

Open 18. Create a ‘Code For Health’ training programme for NHS service analysts and academic researchers

Combine NHS and academia
MOOCs and practical work
Build on prior work but maintain focus on RAP
Open competitive procurement

Open 19. Create a ‘Data for NHS leaders’ training programme
Open 20. Create an ‘NHS data for developers and data scientists’ training programme

Make code a central feature of work in universities using health data

Open 21. Modify the Research Excellence Framework (REF) to reflect computational work
Open 22. Embrace research software engineering (RSE) in health data work
Open 23. Pay realistic salaries to software developers
Open 24. Create a working group to develop an attribution model for code and data
Open 25. Clarify the need for authorship for software developers and data scientists as equal core contributors
Open 26. Proactively address sharing during the pandemic
Open 27. Academic journals should be encouraged to make code-sharing a requirement
Open 28. Embrace research software engineering with 3 data pioneer groups leading by example
Open 29. Use research funding to drive modernisation around better use of code and data
Open 30. Make code sharing a core feature of all standard funding contacts
Open 31. Provide guidance and training on RAP and code sharing

Fellowships for software developers in health data
Entry fellowships scheme for developers from other sectors
Training fellowships in computational methods

Open 33. Open funding calls for projects and programmes around Code for Health Data.
Open 34. Treat ‘data Infrastructure’ as open code
Open 35. Use open competitive funding for code projects
Open 36. Review prior delivery of open code by applicants
Open 37. Ensure experts on code select and oversee code projects
Open 38. Ensure the objectives and outputs of all investments are open
Open 39. Ensure funding for code and platforms does not get diverted
Open 40. Avoid ‘regressive funding models’ built around short-term bursts of funding
Open 41. Focus on sustainability for software projects: set aside a third of resource for this task

Encourage open working through Trusted Research Environment design and implementation

Open 42. All Trusted Research Environments for NHS data must facilitate and require code sharing
Open 43. TREs themselves should be built on principles of RAP and open code
Open 44. Produce clear guidance on disclosure risk and open code

Chapter 3: Privacy and Security

There is no new emergency, but TREs should be used, and data dissemination should not expand
UKRI/NIHR should resource applied methods research into privacy preservation
Revise the definitions of “anonymous” “identifiable” and “linked” data; add a new category of “pseudonymised but re-identifiable”

Chapter 4: Trusted Research Environments

National TREs
Local TREs
Academic TREs

Delivering a national TRE programme

TRE 1. Create the role of national lead on NHS TREs and data curation
TRE 2. Rapidly create a substantial multidisciplinary TRE technical delivery team
TRE 3. Rapidly agree and publish features for the minimum viable National TRE
TRE 4. Agree and publish proposed features of the full National TRE
TRE 5. Produce a minimum viable TRE in 6 months
TRE 6. Rapidly scale over 18 months
TRE 7. Include GP data and certain commonly used national datasets from the start
TRE 8. Expand the National TRE in time to accept bespoke datasets
TRE 9. Evaluate new developments in privacy engineering; adapt accordingly
TRE 10. All TREs must support code sharing and RAP

Develop Trustworthy, Agile, Standard Governance for National NHS TREs

TRE 11. Build a TRE governance team to create a robust framework around TRE access
TRE 12. Create a single standard service wrapper model for NHS TREs
TRE 13. Create a national standard approach to “output checking” and support automation
TRE 14. Establish a standard scheme to accredit NHS TRE users
TRE 15. Ensure TRE access is faster and easier than data dissemination
TRE 16. All TREs must share live detailed activity logs
TRE 17. Create clear rules for undeclared analyses in TREs
TRE 18. Switch off data disseminations, without undue panic
TRE 19. Conduct an annual access audit
TRE 20. Publish all technical steps taken to prevent and detect misuse of data

Ensuring National TREs are Accessible, and Used

TRE 21. The National TRE should be open to all legitimate users
TRE 22. No special cases for working outside a TRE
TRE 23. Ideally one national TRE, never more than 3

Local NHS TRE provision

TRE 24. Create a local NHS TRE programme
TRE 25. Work to rapidly standardise local TRE and DAE provision, starting with ICSs
TRE 26. Create a single service wrapper model for local NHS TREs
TRE 27. Ensure all ICSs use a standard TRE approach
TRE 28. Ensure any other local NHS TREs use the same standard TRE approach
TRE 29. Manage diverse local datasets by creating and sharing standard data curation tools and methods
TRE 30. Ensure all local implementations of national or commonly used datasets such as SUS/HES conform to a single standard
TRE 31. Ensure all datasets extracted from national datasets in NHS Digital are requested using standard data management code
TRE 32. Work towards federated analytics with standard local TREs
TRE 33. Ensure local analysts use a national TRE wherever possible
TRE 34. NHS Trusts and Data Access Environments
TRE 35. Listen carefully to local NHS analysts and TRE managers who describe shortcomings in standard approaches and address these wherever possible

TREs for national audits and registries

TRE 36. Use the same TRE approach as above
TRE 37. Start with data pioneers who can demonstrate computational maturity
TRE 38. Review the current registry and audit landscape; work towards wider access and use
TRE 39. Work towards audits and registries using national NHS infrastructure, RAP, and TREs

Academic TRE implementation

TRE 40. Academics should use NHS data infrastructure to access NHS patient records
TRE 41. Academic TREs should use standard NHS TRE Service Wrapper and governance
TRE 42. Academic TREs should use standard NHS TRE and curation approaches where possible
TRE 43. All academic TREs should aim to use shared standard infrastructure
TRE 44. All academic TREs must support, and should require, RAP and open working
TRE 45. Start with data pioneers who can demonstrate computational maturity in research cohorts

Academic TRE funding

TRE 46. All funding for academic work on TREs should pass through a single national organisation
TRE 47. All TRE and related funding should be openly disclosed
TRE 48. There should be follow-up on all TRE projects resourced
TRE 49. Academic work around TREs should be funded through conventional open competition
TRE 50. Funders should avoid short-term funding for infrastructure
TRE 51. Funding for TREs should be separate to funding for single academic analyses
TRE 52. All best practice and teams should be identified and augmented
TRE 53. An overview of prior investments

What to fund

TRE 54. Standard, national, shared, core compute infrastructure
TRE 55. TRE infrastructure as code and teams

Methodological innovation and code for automated data release from TREs
Methodological innovation and code for data minimisation
Methodological innovation and code for detection of data misuse
Methodological innovation and code to detect unwarranted variation in care
Methodological innovation and code for federated analytics

TRE 56. Exceptions to TRE usage

Consented cohorts
Clinical trials

TRE 57. Address TREs for Artificial Intelligence, but as a separate workstream, funded by existing AI resource

Objections to TREs

Chapter 5: Information Governance, Ethics and Participation

Enhanced usability for IG and ethics processes

IG 1. Create a single form for all ethics, IG, and other data access permissions
IG 2. Streamline the number of approvals meetings
IG 3. Get researchers in the room
IG 4. Create an arbitrator for disagreements over specific access requests
IG 5. Create a single map of all approvals
IG 6. Provide rapid unambiguous guidance when approval is not required
IG 7. Establish 2 modest Centres for Regulatory Science
IG 8. Establish a clinic to help users who are blocked on data access

Two-track approval for TREs

IG 9. Create a 2-track approval system to incentivise use of TREs
IG 10. Maintain excellent standards around governance issues not addressed by TREs
IG 11. Review the National Data Opt Out Policy after TREs are established
IG 12. Uphold the commitment that the NHS Digital GPDPR dataset will not be disseminated

Regulation and Legislation

IG 13. Revise the definitions of ‘anonymous’, ‘dentifiable’ and ‘linked’ data; add a new category of ‘pseudonymised but re-identifiable’
IG 14. Consider including health data in the Digital Economy Act
IG 15. Appropriately sanction those who are caught deliberately and maliciously attempting to re-identify individuals in patient records
IG 16. Disclose all data flows leaving NHS organisations in one place
IG 17. Create a central repository of DPIAs, DSAs and related documents for local NHS data flows
IG 18. Produce boiler-plate templates for patient consent for data use and dissemination
IG 19. Simplify the rules governing use of posthumous data
IG 20. Address the ‘multiple permissions’ problem

Addressing specific roles and uses

IG 21. Start an overdue public and professional discussion on performance management
IG 22. Ensure DHSC can access data when appropriate
IG 23. Start an overdue public discussion about commercial access
IG 24. Negotiate co-ownership of claimed commercial innovations from NHS data
IG 25. Address exclusive commercial arrangements

Patient and Public Involvement and Engagement

IG 26. Ensure PPIE expectations are proportionate to the sensitivity and scale of the project.
IG 27. Provide researchers with easy access to practical guidance, and examples of best-practice
IG 28. Resource and give a platform to experts in building public understanding.
IG 29. Consider centrally commissioning PPIE on common causes of concern

Chapter 6: Data Curation

Cur 1. Adopt the principles of RAP
Cur 2. Set up an NHS Data Curation planning and delivery team, or similar, to own the challenge
Cur 3. Produce and maintain an open public library of data curation code

Generate NHS data curation code, and surface existing work

Cur 4. Mandate that all publicly funded data curation code is shared openly
Cur 5. Identify 5 data pioneer teams to adopt open curation methods
Cur 6. Ensure national programmes lead by example
Cur 7. Capture, and openly share, existing curation knowledge around commonly used national datasets
Cur 8. Use consistent environments to facilitate re-usable curation code
Cur 9. Require use of national TREs for tasks using national datasets wherever possible
Cur 10. Create and enforce consistent standards for local implementations of national datasets
Cur 11. Create and enforce standards for local TREs

Develop tools to facilitate re-usable curation code

Cur 12. Develop standard tools to convert raw data into analysis-ready datasets
Cur 13. Develop portable representations of data management code
Cur 15. Insist that all dataset requests are made in code

Develop capability in Clinical Informatics

Cur 16. Ensure there is clinical informatics training on medical school, post-graduate, and other clinical curricula
Cur 17. Ensure universities have core capacity in clinical informatics
Cur 18. Support core capacity in clinical informatics