The NHS's ten-year plan sets out three big changes: moving care from hospitals into communities, moving from analogue to digital, and shifting the focus from treating illness to preventing it.
The first two are relatively easy to see. More care happening at home. An appointment moves online. A paper record becomes digital. You can point to the change and measure it.
The third shift, prevention, is much harder to measure.
To some extent, I would argue that prevention can start with the everyday activities people find in their communities. A walking group that gets forty people out of the house on a Tuesday. A parent who volunteers with their child's sports team. A food project that people keep turning up to. I visited one such project only last week, Community Roots in Porthtowan. Amazing place.
These activities can make a real difference to people's lives, but we don't always collect the evidence to show it. And without evidence, prevention risks being judged on anecdotes rather than results.
Over the last few days, I've been building an impact measurement dashboard for Devon Connect and our other Enterprise platforms. My aim has been to reveal not just how much activity takes place, but what it tells us about local needs, community support and the difference we might be making.
Start with three simple questions
I've built the dashboard around Results-Based Accountability (RBA) and its three questions:
- How much did we do?
- How well did we do it?
- Is anyone better off?
It sounds straightforward, but it's easy to focus on the first question and overlook the other two. Counting activities, members and events tells us how much is happening, for example, but it doesn't tell us whether those activities are useful, whether people are getting the support they need, or whether their lives are improving.
So I've kept these three questions separate, rather than rolling everything into a single set of headline figures.
What we can measure
We can measure how many people visit a platform, how many connect with an activity or service, how many members return to take part again, and how often searches lead people to relevant support.
Each measure tells us something different. We need to understand what each number means, how it's calculated and what it can realistically tell us.
We also need to be careful about what we claim, and find better ways to capture people's experiences and feedback through our platforms. The dashboard is a starting point for doing that.
Moving care into communities means looking at neighbourhoods
If health and support services are moving closer to where people live, we also need to understand what's happening in individual neighbourhoods, not just across an entire county, city or region.
Devon Connect, for example, has thousands of activities and members. That's a positive picture, but it doesn't tell the whole story. Some areas of Devon have plenty of activities listed, while others have far fewer. A single total can hide those differences.
That's why I've been building the dashboard to show information at two levels: across the whole platform and within individual neighbourhoods / areas.
We can now see how many active members there are in each area, how that compares with the platform as a whole, and how "priority neighbourhoods" are doing. I've also been careful about what counts as an active member, rather than simply counting every account ever created.
But there's another question worth exploring: does the support available in a neighbourhood match what people are looking for?
Our platforms record what people search for, giving us a picture of the help and activities they're trying to find. However, people don't usually tell us which neighbourhood they're searching from, so we can't directly match every search to a local area.
Instead, I've been exploring how we can compare what people are searching for across the platform with the types of activities available in each neighbourhood.
This isn't a direct measure of unmet need. It doesn't tell us exactly where every person lives or prove that a particular service is missing. But it can help us identify potential gaps and decide where to look more closely.
I've also been working on reports for individual neighbourhoods. This means conversations about local needs can start with information relevant to that area, rather than relying on an overall figure that might hide what's happening locally.
Going digital means making data useful
Building the dashboard has reinforced something I already knew: collecting data is only part of the job.
The real value comes from what we do with it. Can we use it to understand what's happening in our communities? Spot potential gaps in local support? Challenge our assumptions about what's working and what isn't? Make better decisions about where time, effort and money should go?
Good data isn't just about collecting the right information. It's about using it to make better decisions.
Measuring prevention means being honest about what we know
As I've already mentioned, moving from treating illness to preventing it is probably the hardest of the three shifts to measure.
Community activities can help people stay active, build relationships, develop confidence and find support before their problems become more serious, for example, but proving that a particular activity has prevented an illness or reduced demand on health services is much more difficult.
Nevertheless, our dashboard can measure things such as repeat participation, connections to services, volunteering pledges, completed exchanges, hours given and received. These help convey what's happening in our communities and how people are getting involved.
Activity alone doesn't tell us whether someone's health or wellbeing has improved of course. Someone clicking on an activity, signing up for it and actually attending are three different things. And even if someone attends an activity or service regularly, we can't automatically assume their health or wellbeing has improved as a result.
To understand that, we need to look beyond activity figures. We need to find ways to capture people's experiences, ask whether they're getting the support they need, and understand what has changed for them over time.
That doesn't mean every activity needs a formal evaluation, or that we can always prove a direct link between community support and better health. But it does mean being clear about the difference between what we can count, what we can reasonably infer, and what we still need to find out.
For me, that's an important part of measuring impact. It's not about making the numbers look positive. It's about building an honest picture of what's happening, learning from it and using that understanding to improve the support available in our communities.
What this means for neighbourhood health services
Better local data can help people planning and delivering neighbourhood health services build a more rounded picture of what's happening in their communities.
Looking beyond overall activity figures can reveal differences between neighbourhoods. Comparing the support available with what people are searching for can highlight potential gaps worth exploring. And looking beyond participation numbers can help us understand whether community activities are making a difference to people's lives.
Data won't provide all the answers. It needs to be considered alongside local knowledge, professional experience and the voices of the people using services.
But it can give us a stronger starting point for understanding local needs, deciding where to focus attention and assessing whether things are improving.
That's what I've been exploring through the impact measurement dashboard for Devon Connect. We're bringing together information about platform activity, neighbourhood provision, search demand and estimated social value to build a clearer picture of what's happening locally.
I'm hoping to share the dashboard with the Devon Connect steering group next week.