An evidence-driven journey to understanding equality

Hold onto your data hats my fellow analysts in arms! As I’m about to tell you how statistics has played a crucial part in our mission to provide the best care for Essex citizens.

Essex County Council is committed to listening to, and understanding, the people of Essex. One of our responsibilities is to obtain more knowledge around potential inequalities that may have exist for people accessing our services. To continually improve service delivery, we need to know who our customers are, consider the diversity of their needs and possible barriers to equal access – both in terms of how representative the customer base is of the wider population, but also the difference that those services make.  This is to ensure that support can be equally obtained and that services are adapted if people have outcome differentials.

Let me start by sharing the problem statement: In tackling and understanding differential equality outcomes, and understanding the experience of different groups, there is a need to comprehend what we are and can collect around equality data so that we can effectively monitor and constructively challenge the organisation.

Inequalities aren't a one-dimensional puzzle. They're a complex, multi-layered tapestry that require different lenses to unravel. And so, although a statistical approach has for sure been a trusty ally in focusing in on the things that matter, the work was shaped by the expert eyes of a multidisciplinary team (MDT)– something like an Avengers-style team - featuring Researchers, Analysts, and Heads of Professions across the Policy Unit. Each professional brought something unique to the table, and together, we formed a powerhouse to tackle inequalities from every angle.

Our MDT started off with an awareness of what information we  currently have about equalities, and how well recorded that information is (i.e. do we collect ethnicity information? How well populated is the religion information in our databases? etc). Here, Performance and Business Intelligence colleagues played an important part in understanding our current data. They provided clarity to functions on where our data needed to be collected.

Then, Data and Analytics members contributed statistical knowledge that helped the MDT to focus in the right places. As we delved into the intricacies of Essex's population through the equalities lens, we quickly realised that mere observations weren't going to cut it.

To better understand peoples' experiences by different protected characteristics, according to the Equality Act 2010 we looked at age, gender, ethnicity, marital status and disability. We decided to use Chi-square tests, Kruskal-Wallis tests, among other methods to seek the truth and obtain robust findings. It wasn't just about spotting variations in the data; it was about ensuring those variations were more than just random quirks. We needed robust evidence, the kind that stands up to scrutiny, the kind that you can confidently present to the sceptics.

How we used statistics in this deep dive?? (This is the part where I may get a bit excited.. so be prepared)

We jumped straight into the data-ocean that led us to the specifics of service users’ access and outcomes. We covered areas such as how we connect with Essex citizens (Direct Contacts, Interventions, through Health Settings, etc), how we evaluate people’s situations and how we can help them (adults and carers), what services we provide, how we did after the services provided were finished, and so much more!

In each area, we then analysed user’s proportion for each of the protected characteristics to try to answer questions such as: are more male users contacting us after being discharged from hospital? Are more younger users more likely to contact us using more modern technologies?

I can tell you that, like I said at the beginning, statistics did help us to look in the right places; for example, that we have an over-representation of female users over 75 years old and an under-representation of males in their 75 or over years old. The difference of that finding with the census figures was so significant that was basically saying "pay attention to this!" It's a clue, a beacon of interest, but we need the full story. And here is where our amazing MDT played its part.

We gathered the granular findings to compare those proportions with the population of Essex (are we seeing the same proportion of female residents reflected in the proportion of female users?) Again, more statistics! But this time around, it was Research and Citizens Insight colleagues that brought all that knowledge about Essex and provided us a greater understanding on those numbers around protected characteristics looked like at a county level. And not only that! They also brought into the conversation further information that made us understand why we were seeing specific patterns, proportions that seemed a bit out of context,

The MDT approach was critical to this work. Without bringing all the skillsets from these different teams into the conversation, we would not have been able to create a complete picture of Equalities from our data.

So here we are, my fellow analyst warriors, knee-deep in the battle for equality, armed with spreadsheets and statistical hammers, ready to change the game and pave the way for a brighter, more inclusive, tomorrow for the people of Essex.

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