Data science in the NHS

Data science in the NHS #

The GOV.UK service standard is widely regarded as representing good practice in delivering digital services in the public sector. It is mandatory for certain digital services within government but the latest guidance includes standards which can be adopted across the public sector regardless of whether they would require mandatory assessment. It includes fourteen standards.

This document examines these standards from the point of view of data science teams, and particularly data science teams within the NHS. The NHS service standard reproduces the 14 standards, and provides extra information to teams in the NHS in recognition of some of the ways that the NHS can differ from other areas of the public sector. The NHS service standard also includes 3 extra service standards, again recognising the unique environment of the NHS.

Examples of the difference between working within the NHS and the rest of the public sector include:

  • multi-disciplinary teams are not common in the NHS - by “multi-disciplinary” we mean teams made up of product and delivery managers, designers, developers, user researchers and content designers
  • NHS delivery teams are less likely to be practising user-centred design and agile service delivery
  • measuring outcomes is often more complex for health
  • more products and services are commissioned locally, for example in hospital trusts, and they are more likely to rely on suppliers, long-term contracts and “off the shelf” solutions

These issues are clearly equally important in data science, particularly the last point, and I propose in this document that data science teams across the NHS begin to work more closely in line with the GOV.UK service standard, as expressed within the NHS digital service standard and including the extra three points on it. The fourteen GOV.UK points area listed following, followed by the three extra NHS points.

  1. Understand users and their needs in the context of health and care
  2. Work towards solving a whole problem for users
  3. Provide a joined up experience across all channels
  4. Make the service simple to use
  5. Make sure everyone can use the service
  6. Create a team that includes multidisciplinary skills and perspectives
  7. Use agile ways of working
  8. Iterate and improve frequently
  9. Respect and protect users' confidentiality and privacy
  10. Define what success looks like and be open about how your service is performing
  11. Choose the right tools and technology
  12. Make new source code open
  13. Use and contribute to open standards, common components and patterns
  14. Operate a reliable service
  15. Support a culture of care
  16. Make your service clinically safe
  17. Make your service interoperable