Women looking at computer screen

There is much uncertainty about the impact of recent developments in data and technology on our health, and health and care services. New technologies offer significant potential, but active, and timely, monitoring and evaluation is crucial so that we are aware of the positive or negative impact on health, and can therefore respond.

With many of these technologies being developed by innovators in the private sector, attempts to evaluate their impact requires cooperation and collaboration between the private and public sector – particularly the bringing together of data from public and private sector sources.

We worked with the Health Foundation – an independent charity committed to bringing about better health and health care for people in the UK – on a joint research project from January to July 2020, exploring the potential of new models to collect and steward data, to support how we evaluate the impact of data and technology on health and healthcare.

Why new stewardship models?

At the ODI, we have been looking into methods for increasing access to data while retaining trust. We have developed a map of different data access models and have particularly focused on the role of data stewards, data intermediaries and institutions that support bringing together data from multiple organisations. Our work has centred on data trusts – legal structures that support independent third party stewardship of data on behalf of a community – but has also explored related models such as data commons and data cooperatives.

Our approach

We used real-world use-cases to explore which data stewardship models are able to help private and public sector organisations share sensitive data in trustworthy ways given different technologies, contexts, ecosystems etc. We made sure we selected use-cases that would be relevant and useful in the Covid-19 context. We also selected them depending on their location in the health sector, the level of engagement with people, the extent of adoption, type of technology, and the scale of impact.

These use cases are:

  • Assessing the safety, effectiveness and efficiency of digital-first primary care services designed to advise patients about their symptoms and direct them to other, non-digital primary care services.
  • Understanding the spread of information and misinformation online, and the impact of misinformation on vaccine hesitancy and public health.
  • Evaluating patient flow automation systems which are designed to improve clinical pathways and operational efficiency within hospitals and across regions.

We ran interviews and workshops throughout the spring of 2020 with innovators, evaluators, regulators and experts from the health and care sector, in order to scope and co-create these use cases that will best help us achieve these aims.

By focusing on these, we have been able to take an in-depth look at the data ecosystems that surround these new technologies, their potential value, the relevant stakeholders involved, and the challenges and barriers to accessing and sharing data for evaluation purposes.


Our findings can be found in this report:

Key challenges identified were related to the data needed for evaluation not being collected, as well as the data not being accessible. Access issues can be due to a variety of causes, such as a lack of incentives to share, worries related to sensitive data, lack of clarity on what is permissible. When accessed, the data can also sometimes not be as useful as expected (this can be due to a lack of quality, consistency or standards).

In doing so, we explored where a data institution could make sense, and where it should be coupled with other elements to be put in place such as the need to convene key stakeholders and explore data needs, push for new rules related to procurement, and adopt new standards.

We also have identified key recommendations and next steps for key stakeholders such as evaluators, funders, innovators, health and care providers, and patient and practitioner groups. Some evaluators could play a role of data institutions, some funders could help explore some areas of research not being covered yet, innovators could prepare for evaluation earlier on, providers could act as convenors in the sector, and patients and practitioner groups could take a more active role in the data collection.