Interview: 2023 Florence Nightingale Award winners

The 2023 Florence Nightingale Award for Excellence in Health and Care Analytics was jointly won by two teams  whose tireless work greatly impacted their communities during the Covid-19 pandemic.The mass Covid testing pilot in Liverpool (COVID SMART) pioneered population-scale Covid testing, while a project looking into the impact of long Covid in Scotland (EAVE II) tackled some of the complexities of the condition that had previously made it difficult to measure. One year on, we sat down Iain Buchan from Liverpool COVID SMART and Karen Jeffrey from EAVE II for a catch up.

Apply for this year’s Florence Nightingale Award
How has winning the Florence Nightingale award impacted the team?

Iain Buchan: There is no better recognition for your work than from peers, so the award meant a great deal to us.

Karen Jeffrey: The validation of a prestigious institution like the RSS is particularly meaningful for early career researchers, as it provides tangible evidence of their excellence that can be cited in applications for future research funding. And it’s always nice to receive positive feedback too!

It was a good second opportunity for promoting the research on social media as well.
EAVE II received a lot of media attention before the award too. How did this contribute to raising public awareness about long Covid in general?

KJ: Raising public awareness is a continuous process, and our role has been to contribute rigorous scientific analysis. However, that is just one piece of the puzzle. Tireless patient groups have been the driving force behind raising awareness about long Covid. These groups are the ones who continue to keep it on the agenda.
As the world’s first large-scale voluntary use of lateral flow tests for people without symptoms of Covid-19, community engagement must have also been very important in COVID SMART too …

IB: Absolutely. The Liverpool City Region Civic Data Cooperative opened just before the start of the pandemic, with a mission to make data work for our residents and with their guidance. The very high participation rate seen in the Liverpool pilot also reflected a 175-year history of public health innovation with deep community involvement. In the most intensive parts of the pilot, there was community focus group feedback every few days – even door-to-door knocking!
What lessons have you learned that might be applicable in the future of public-health data analysis?

KJ: In this project, we were fortunate to have the resources and support to engage patients, members of the public, clinicians, policymakers and senior decision-makers. There is no doubt in my mind that doing so improved the research and the impact we were able to achieve. For me, this underscores the value of ‘designing in’ such engagement.

IB: Above all, we learned that trust and teamwork can move mountains for public health, especially when the call comes to respond to an emergency. At one point in the testing pilot, we were challenged for sharing data between the former Public Health England and NHS England, but city-wide support showed us that doing this with best practice in mind was the right thing to do.
Is that something that’s reflected in the feedback you’ve received since the project’s completion?

IB: Yes, the civic pride, national purpose and international impacts of our Covid-19 response is reflected a lot in the feedback we get. And we recently formed the Data into Action programme in NHS Cheshire & Merseyside to build on our Covid-19 data responses such as CIPHA – which were as much about teamwork as about tooling to turn data into actions.
Are there any other upcoming projects or initiatives that have been inspired by the success of the COVID SMART mass testing evaluation and CIPHA analytic legacy?

IB: We recently opened a new University of Liverpool centre, the Civic Health Innovation Labs (CHIL),  which includes an embedded NHS data centre. CHIL is a multidisciplinary ‘data lab’ designed for team collaboration and public involvement, with those authorised to access the secure data area able to mix just outside with the public, statisticians, researchers – sharing the same coffee room, design lab and hybrid meeting facilities.
What about in Scotland? Has Public Health Scotland’s approach to service provision for long Covid patients been informed by the EAVE II project?

KJ: Definitely. We have advised Public Health Scotland on several options for using data recorded in electronic health records to assess the prevalence of long Covid going forward, which will inform how they monitor it.
What advice would you give to other teams undertaking similar projects?

KJ: In the study, we had to deal with many limitations – like the way GPs record patient data being difficult to use in research – so we had to use several different measures to identify long Covid, including using free-text data. I would advise other researchers who plan to work with primary-care data to consider this carefully when developing a methodology.

IB: I’d say to pull together across disciplines and organisations to work as one team, acting in the public interest – this builds trust and efficient operations. If the imposed structures split the team into siloes, then beg forgiveness not permission to unify efforts as a civic whole.

KJ: And, of course, I would also advise others to nominate their studies for the Florence Nightingale Award!
Thank you very much! How do you see the integration of data analytics in public health evolving in the coming years?

KJ: It’s an exciting time to be working in data analytics for public health. In recent years, we’ve seen enormous growth in the amount of health data being generated. At the same time, increasingly sophisticated AI tools are emerging that can be used to identify patterns in very large datasets. These developments offer immense potential. However, ensuring that the public can trust that their data is used in a responsible way is a huge challenge.

IB: Yes, AI that augments data governance, extraction, cleaning and exploration – and to some extent causal reasoning – will support dataflows and good analytics pulled through from a more action-oriented public health environment. But health systems are likely to be offered tools that over-simplify the challenge of good causal inference. Extensively training teams, not just individuals, to use these AIs and to question assumptions carefully will be important.

KJ: Transparency and public participation in data collection, analysis and decision-making processes will be paramount here too. 
Load more