Code of conduct for data-driven health and care technology

DoHSC

Updated guidance from Department of Health & Social Care - Code of conduct for data-driven health and care technology

Today we have some truly remarkable data-driven innovations, apps, clinical decision support tools supported by intelligent algorithms, and the widespread adoption of electronic health records. In parallel, we are seeing advancements in technology and, in particular, artificial intelligence (AI) techniques.

Combining these developments with data-sharing across the NHS has the potential to improve diagnosis, treatment, experience of care, efficiency of the system and overall outcomes for the people at the heart of the NHS, public health and the wider health and care system.

Innovators in this field come from sectors that are not necessarily familiar with medical ethics and research regulation, and who may utilise data sets and processing methods that sit outside existing NHS safeguards.

It is the duty of NHS England and central government to capitalise on these opportunities responsibly. People need to know that their data is being used for their own good and that their privacy and rights are safeguarded. They need to understand how and when data about them is shared, so that they can feel reassured that their data is being used for public good, fairly and equitably.

Their responsibility as an internationally trusted health and care system is to use all the tools at our disposal to improve the quality and safety of care, including data-driven technologies, in a safe, ethical, evidenced and transparent way. For this reason, they have developed 10 principles in a code of conduct to enable the development and adoption of safe, ethical and effective data-driven health and care technologies.

The code of conduct clearly sets out the behaviours expected from those developing, deploying and using data-driven technologies, to ensure that all those in this chain abide by the ethical principles for data initiatives.

The principles:

  1. Understand users, their needs and the context
  2. Define the outcome and how the technology will contribute to it
  3. Use data that is in line with appropriate guidelines for the purpose for which it is being used
  4. Be fair, transparent and accountable about what data is being used
  5. Make use of open standards
  6. Be transparent about the limitations of the data used
  7. Show what type of algorithm is being developed or deployed, the ethical examination of how the data is used, how its performance will be validated and how it will be integrated into health and care provision
  8. Generate evidence of effectiveness for the intended use and value for money
  9. Make security integral to the design
  10. Define the commercial strategy

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