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Sarah Dougan is Chief Analytical Officer at London Borough of Islington, where she leads a partnership project funded by the Health Foundation that’s developing an innovative linked dataset between the NHS and local government. She also leads on population health analytics for the North Central London STP and as is part of the One London local health and care record exemplar (LHCRE) programme. We spoke to her about how the work is enabling analysis of the social determinants of health at a household level, and the exciting ways data analytics can be used to drive whole system change.

What are the most exciting ways you’ve seen data analytics being used to help make care better? 

Data plays a crucial role in improving people’s experiences of health and care, as well as enabling strategic planning, needs analysis, and evaluation. 

I get most excited about using data to effect whole system change locally, which doesn’t happen often. By far the most exciting thing I’ve seen is when we first started using our GP data for public health analysis in Islington. Working with local GPs, we extracted a pseudonymised GP dataset (where the identifiable fields such as name and address have been irreversibly removed but a unique person identifier (such as NHS number) has been replaced with a random identifier) from all of our GP practices to undertake population health needs assessments. 

It represented a large step change in what we understood about people with multiple conditions, their needs, and opportunities for prevention and early intervention. The really exciting part was how people from across health and care, including GPs, practice managers, and commissioners, responded to the analysis and made changes – commissioning differently, investing more in prevention, and making improvements in their own areas of work. At that time, for example, we used the data to directly inform the model of delivery for NHS Health Checks, including location and local eligibility criteria, enabling programme efficiencies and one of the highest levels of uptake nationally.

It also laid the foundations for us to create a more data-driven system locally as there was a greater understanding of how data can be used to improve outcomes, as well as in our neighbouring boroughs where we replicated the analysis.

Tell us about the project you're working on now to link NHS and local government data in order to understand the social determinants of health? 

The social determinants of health (the conditions in which people are born, grow, live, work and age) are the key drivers of inequality and of poor health and wellbeing. In our local area this is well understood, but to date we have not been able to quantify the impact a factor like housing for example, has on someone’s health and use of health services (and vice versa). 

In Islington we are working with the NIHR Collaboration for Leadership in Applied Health Research and Care (CLAHRC) and North Thames and NEL Commissioning Support Unit (NEL) to link pseudonymised data from the NHS with council data on the social determinants of health. We are fortunate to be funded as part of the Health Foundation’s Advancing Applied Analytics programme to help us do this and we will also build upon the work that the Health Foundation’s in-house analytics team has been doing on households

By linking council data with NHS data about each local household, we’re hoping the resulting analysis will give us insights into the needs of local residents. This information will directly inform the work of local health care and council services, to deliver a more integrated system across the public sector. Assuming we can access the data, we’re planning to have early analysis done by Christmas 2018.

The Health Foundation has been saying that a big challenge for the NHS is to develop better analytical capability. Individual examples like these are exciting, but what is really needed is to move towards everyday use of data to improve health and social care. What are you doing in Islington to develop better capability for analytics?

There’s a lot of momentum to work more collaboratively, which is great as it’s the only way we are going to do things at scale, particularly given that the specialist analytics skills needed are in short supply. We also need to make the most of new technologies. 

North London Partners in Health and Care (our local sustainability and transformation partnership (STP)), with NHS England funding, has recently procured Cerner's Health Information Exchange and population health management platform, HealtheIntent, to enable our system to deliver our aspirations for population health at scale.

We’ll also be contributing to the One London local health and care record exemplar programme. We’ll be inputting around social care and the social determinants of health, working with NEL and other partners to help us to develop things once for London. 

While the investment in these technologies to date is very welcome, there is still a huge amount of work to do on the content to ensure systems take a holistic approach to population health. 

The Health Foundation's review into analytical capability found that sometimes analysts in the NHS are isolated. What opportunities do you think there are for analysts to collaborate and share ideas?

There are lots of opportunities for learning and collaboration. I’d encourage analysts to get out and meet other analysts, including those working in different public sector organisations. It’s amazing how much you can learn, even from a quick coffee with someone! There are also some great dedicated networks for analysts, including the Association of Professional Healthcare Analysts (ApHA), supported by the Health Foundation. 

And if you’re responsible for managing analysts then I’d encourage you to think about how you can proactively support them to gain new specialist skills and knowledge, as well as skills around collaboration and networking. 

If organisations and STPs are serious about using their data better then they need to be thinking about how senior leadership understand and encourage data analytics. Perhaps we need to consider whether a model similar to digital, where most organisations now have dedicated specialist and clinical roles (such as chief information officer and chief clinical information officer), could work for analytics. 

Finally, we all need to be thinking about how analysts across the system could be working differently together to make the most of our specialist knowledge and skills to improve health and wellbeing.  

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