Data loves a binary but as any social worker would I’m sure tell you - people don’t fit neatly into boxes! For much of our analysis there is a need to segment individuals into various groups, whether its budget code, age group, support reason or a health condition such as dementia, the true picture is so often much more complicated than a checkbox yes/no.
Something I’ve found really exciting that’s come out of our Complexity in Adult Social Care workstream is the way it has helped us to better understand and communicate the range of different needs that individuals have. By considering social care need as a spectrum across multiple domains we have found a really useful compromise between the analytical need to classify and measure, and the need to recognise individuals’ unique circumstances. Recognising that two people with the same basic demographic profile, even if they receive similar services, will have a completely unique experience and adding nuance to the existing groups that we use, without losing the ability to compare or summarise.
Using a combination of structured data fields and text insights from case notes we’ve been able to aggregate some of the key information that social workers already capture and reflect it in a profile that more closely fits the nuanced picture our frontline staff have of individuals and their multifaceted social care needs.
There are a huge range of potential applications for this but one of the practical ways we have been applying this approach has been to explore the impact of dementia and cognitive impairment within our caseload, something which has been perhaps surprisingly difficult to quantify in the past.
Over the time I’ve been at ECC I have been involved in multiple pieces of work focusing on dementia and one of the recurring challenges is that we do not have access to formal diagnosis data. Typically reporting has been reliant on using Primary Support Reason, the ‘main’ need that an individual approaches us for support.
Around 1,200 people on our caseload approach us primarily for ‘Support with Memory and Cognition’, but if we analyse unstructured and free text data to include everyone with cognitive impairment support needs as part of their overall picture of need, we identify that five times the original number of people are impacted. This not only helps us plan our current service provision by identifying ‘hidden’ demand where individuals might benefit from certain forms of support, but also helps us prepare for the future by highlighting potential emerging demand.
We are using this approach to help to support and inform the Dementia Strategy Implementation Plan, to identify cohorts with health conditions at an increased risk of developing dementia such as Parkinson’s, or Mild Cognitive Impairment who might go on to need additional support in the future.
While the needs based social care approach does not address the known issue of underdiagnosis of dementia, a needs-based approach allows us to target support to groups of individuals who may benefit, regardless of formal diagnosis.