On 5 September, in response to the opportunities presented by data-driven innovations, apps, clinician decision support tools, electronic health care records and advances in technology such as artificial intelligence, the UK Government published a draft “Initial code of conduct for data-driven health and care technology” (Code) for consultation. The Code is designed to be supplementary to the Data Ethics Framework, published by the Department for Digital, Culture, Media and Sport on 30 August, which guides appropriate data use in the public sector. The Code demonstrates a willingness of the UK Government to support data sharing to take advantage of new technologies to improve outcomes for patients and accelerate medical breakthroughs, while balancing key privacy principles enshrined in the GDPR and emerging issues such as the validation and monitoring of algorithm-based technologies. For parties considering data-driven digital health projects, the Code provides a framework to help conceptualise a commercial strategy before engaging with legal teams.
The Code contains:
- a set of ten principles for safe and effective digital innovations; and
- five commitments from Government to ensure the health and care system is ready and able to adopt new technologies at scale,
each of which are listed further below.
While the full text of the Code will be of interest to all those operating in the digital health space, the following points are of particular note:
- the UK Government recognises the “immense promise” that data sharing has for improving the NHS and social care system as well as for developing new treatments and medical breakthroughs;
- the UK Government is committed to the safe use of data to improve outcomes of patients;
- the Code intends to provide the basis for the health and care system and suppliers of digital technology to enter into commercial terms in which the benefits of the partnerships between technology companies and health and care providers are shared fairly (see further below); and
- given the need of artificial intelligence for large datasets to function, two key challenges arise: (i) these datasets must be defined and structured in accordance with interoperable standards, and (ii) from an ethical and legal standpoint, people must be able to trust that data is used appropriately, safely and securely as the benefits of data sharing rely upon public confidence in the appropriate and effective use of data.
The Code provides sets out a number of factors consider before engaging with legal teams to help define a commercial strategy for data-driven digital health project. These factors include: considering the scope of the project, term, value, compliance obligations and responsibilities, IP, liability and risk allocation, transparency, management of potential bias in algorithms, the ability of the NHS to add value, and defining the respective roles of the parties (which will require thinking beyond traditional research collaboration models).
Considering how value is created and realised is a key aspect of any data-driven digital health project, the Code identifies a number of potential options: simple royalties, reduced payments for commercial products, equity shares in business, improved datasets – but there is also no simple of single answer. Members of Covington’s digital health group have advised on numerous data-driven collaborations in the healthcare sector. Covington recently advised UK healthcare technology company Sensyne Health plc on pioneering strategic research and data processing agreements with three NHS Trust partners. Financial returns generated by Sensyne Health are shared with its NHS Trust partners via equity ownership in Sensyne Health and a share of royalties (further details are available here).
The UK Government also intends to conduct a formal review of the regulatory framework and assessing the commercial models used in technology partnerships in order to address issues such as bias, transparency, liability and accountability.
The UK Government is currently consulting on the Code (a questionnaire on the Code is available here) and intends to publish a final version of the Code in December.
The Code’s principles and commitments are listed below. For further details please see the full text of the Code.
Define the user
- Define the value proposition
- Be fair, transparent and accountable about what data you are using
- Use data that is proportionate to the identified user need (data minimisation principle of GDPR)
- Make use of open standards
- Be transparent to the limitations of the data used and algorithms deployed
- Make security integral to the design
- Define the commercial strategy
- Show evidence of effectiveness for the intended use
- Show what type of algorithm you are building, the evidence base for choosing that algorithm, how you plan to monitor its performance on an ongoing basis and how you are validating performance of the algorithm
- Simplifying the regulatory and funding landscape
- Creating an environment that enables experimentation
- Encouraging the system to adopt innovation
- Improving interoperability and openness
- Listening to our users