Four priorities to advance social care data analytics in the new year

I usually wait until the very end of December to reflect on the year’s changes and to look ahead to new resolutions, but this year a couple of things have prompted me to take a slightly premature view. Namely, an evaluation of our Strengthening Social Care Analytics programme has just been completed by consulting organisation SQW. This has made me take stock of the challenges that persist in social care, and consider how projects like those we have been supporting can help.

In the spring of 2020, during those first bewildering months of the pandemic, we began to set up our Strengthening Social Care Analytics programme. We spoke to as many people as we could who worked in or had lived experience of social care, to get a sense of what issues could be addressed with better use of data. Those conversations pushed us to work as quickly as possible to make funding available to care providers and commissioners under pressure. In the intervening 1.5 years, we’ve seen unparalleled political turmoil resulting in a lack of meaningful leadership on the subject, extraordinary poverty revealed in care workers’ lives amid a workforce crisis, and long waits for ambulances due in part to insufficient social care capacity. These are urgent challenges affecting many peoples’ lives.

The five projects we funded have shown how collecting and using data well can inform decision making, empower people who give and receive care, support service planning and help in the measurement of progress. Reflecting on the findings of these projects and the programme evaluation, I would like to suggest four considerations for government as it implements the health and social care data strategy recommendations.

1. Listen. The voices and experiences of people giving and receiving care are vital, both in the shaping of what data are collected, and in the actual data. One project, led by Equal Care Co-op, highlighted how opaque the social care system is to those who use it and emphasised the importance of co-production.
2. Include smaller providers in efforts to develop digital and analytical capability. Small providers may not have the capacity to use data analytics and may feel more acutely the burden of data collection as requirements shift to more detailed, person-level data. The data strategy commits to funding training that will help the workforce develop digital literacy, which is welcome. However, there must be long-term work to ensure that providers of every kind are supported to derive meaningful insight from the data they collect and submit, which will pay dividends as integrated care systems mature into learning health systems. This requires an investment not only in digital literacy but also in analytical capability.
3. Help broker partnerships between the social care sector and other organisations that can provide the necessary skills, such as technical and analytical skills, research skills and expertise engaging with service users. The best partnerships will be value-driven, produce shareable and open resources that others can learn from, and will help each organisation build their own skills. Organisations should be supported to find one another, listen to others’ experiences and work together well.
4. Encourage learning across organisations. The Social Care Analytics Community of Practice, established by Future Care Capital but soon to be hosted by NHS England’s Transformation Directorate, has provided a national space for discussion and peer learning. Mencap is an example of a care provider that has used this forum actively to share their progress and their code.

Advancing these four priorities could equip the social care system with the tools it needs to share and learn from one another, to listen and be heard, and to ensure that efforts to improve capability reach every provider, big or small. As new year’s resolutions go, I think the government could do worse.

Ellen Coughlan (@EllenCoughlan) is programme manager in the data analytics team at the Health Foundation.