Data can transform social care – five projects show how it’s done

An online event heard how intelligent use of data can make a difference to the lives of people receiving care

14th November 2022 about a 8 minute read
“Delivering home care is a logistics problem – the right person has to be in the right place at the right time.” Mark Russell-Smith, Procomp Solutions Oy

Strengthening Social Care Analytics is a programme funded by the Health Foundation with the aim of investigating different ways in which data analytics could be used to improve social care. Five teams across the UK received up to £60k each to run different projects, and the social research organisation SQW evaluated the programme. Future Care Capital (FCC) developed a community of practice to bring together stakeholders to discuss and share good practice.

At an online event in November, panellists representing the five teams talked about the projects – the outcomes, the challenges and what they’d learnt. In the second half of the event, SQW gave the results of its evaluation, while the Department for Health and Social Care (DHSC) presented its roadmap for social care data in the next three years.  The event was chaired by the Health Foundation.

The panellists were:

Muyi Adekoya, NHS North Central London

Emma Back, Equal Care Co-op

Peter Bloomfield, Future Care Capital

Owen Bowden, Mencap

John Bryant, Torbay Council

Ellen Coughlan, Health Foundation

Raj Malhi, Department of Health and Social Care

Jane Meagher, SQW

Lauren Roberts, SQW

Mark Russell-Smith, Procomp Solutions Oy

Joanne Starkie, London Association of Directors of Adult Social Services (ADASS)

Simon Whitehouse, Open Data Services

The paucity of data in social care is a longstanding problem that makes it hard to effect improvement in the sector. Each of the projects sought to address this paucity in an innovative way, though almost all were hindered in part by timing, with the projects starting roughly at the same time as the Covid pandemic.

A sense of powerlessness

Emma Back and Simon Whitehouse spoke about how Equal Care, a social care co-operative, created a project to show the impact that open tendering could have on a social care service. Social care tendering is generally an opaque process, with no attempt, Emma said, to “make those specifications more accessible to the community that it is supposed to be serving.”

One of the surprising things about the project, Emma said, was the discovery that everyone they spoke to in the sector “felt powerless to effect change and to improve the lot of social care” – including people usually perceived as having power. That sense of powerlessness, she said, was “strongly reinforced by the lack of available data in social care”: commissioners, for example, are unable to make the case that social care enables family members to return to work to create economic wealth, simply because that data isn’t available.

The project was governed by the principles that social care tendering commitments should be accountable to the people who give and receive care; open and transparent to the communities they serve; and make it possible to see easily what does and doesn’t work. The use of a tool from Open Data Services to query metrics data has enabled Equal Care to publish structured data about their performance.

Owen Bowden of Mencap spoke about the charity’s use of the Personal Outcome Scale, a questionnaire tool consisting of 48 questions designed to collect data about the quality of life of Mencap’s clients, enabling support staff to make changes that would enhance that quality of life. The project included creating an analytics platform that could analyse both the quantitative and qualitative data to draw out particular themes – one finding, for example, was that many clients felt they would benefit from learning digital skills, while others were keen to learn how to cook.

Robust governance is key

Joanne Starkie of Brent Council and Muyi Adekoya from NHS North Central London talked about their project to tackle the low response rate in London to the Adult Social Care Workforce Data Set (ASC-WDS), a workforce survey carried out by Skills for Care. While the national response rate is 59%, London’s is only 35%. London, Joanne pointed out, has “more cross-borough activity than other England regions” and a “very fluid care market.” Local authorities, she noted, “often want to be able to view data in different ways,” but are hindered by the lack of data. The project aimed to develop and share adult social care workforce data across London to support operational and strategic decision-making. In each of the 32 boroughs, a nominated person was given responsibility for working with providers.

One of the project’s best decisions, Muyi said, was to allow providers to specify whether they wanted data to be shared with others or not: “It gave providers the confidence that whatever they supplied to us we would use it as they needed it to be [used].” Robust governance, senior management buy-in and service user engagement were all key, and the response rate has now risen to 42.9%.

John Bryant of Torbay Council and Mark Russell-Smith of analytics firm Procomp Solutions Oy set out the problem of domiciliary care provision in Torbay. The council uses multiple providers covering an area with a 75-mile perimeter, and the social care workers who travel to clients’ homes by car criss-cross each other frequently – a hugely inefficient use of resource. Every year the carers drive 832,124 miles and create 235 tonnes of carbon. The solution was first to collect the data – who was driving where and when – and to use it to make the process more efficient. As Russell-Smith said: “Delivering home care is a logistics problem – the right person has to be in the right place at the right time.” Analysis of the data has shown that, if providers co-operate with each other, care workers can stay within a small local area, with some even walking to clients’ homes. By spreading the workload (so that some early morning visits are made a little later), care workers’ time can also be used more efficiently throughout the day.

Ellen Coughlan of the Health Foundation talked about the project run by Manor Community, a small care provider in East Bristol offering rehabilitative care to people of working age with learning disabilities or complex mental health problems (a representative from the organisation was unable to attend). The aim of the project was to look at how machine learning and advanced analysis tools can strengthen the voices of the clients it supports. There were two elements to the process ­– working with clients to identify the most appropriate questions, which focused on how care providers could improve the care they offered, and then creating and administering a survey that asked those questions. As a result of this work, it was able to build a sharable anonymised data collection tool underpinned by data analytics.

Improved confidence and skills

Reflecting on the five projects, Jane Meagher and Lauren Roberts of SQW spoke of the programme’s successes in improving participants’ knowledge and understanding of data analytics, and in encouraging collaboration and co-production with those in receipt of care. There had, said Jane, been a “knock-on effect in benefits to caregivers and service users who had been involved in the delivery of projects or participated in data collection.” These included “improved confidence, improved skills and an opportunity to reflect on their own experiences of care in safe spaces.” Their programme recommendations included providing ongoing support to projects to disseminate learning and ensuring that project leads can evidence that they have the capacity to drive the projects forward.

Raj Malhi of the DHSC noted that before the pandemic there was “very limited data on adult social care”, and that it had been captured through annual returns from local authorities. The pandemic had led to the government announcing emergency measures to capture data used to respond to emerging risks and issues – and this, he said, had “led to a step-change in our understanding of how the system works and the sector-wide benefits that can accrue from increased access to data.” In the next three years, the department’s work will include identifying data gaps, reviewing the data being collected, making sure that frameworks are in place to monitor outcomes, and improving data capability at all levels. Next year will see a data project piloted in 43 local authorities with a view to adoption across all 152 by April 2023. The DHSC will outline its plans in more detail in a draft publication in December.

Closing the event, Peter Bloomfield highlighted FCC’s contribution in running the community of practice for the programme, bringing together analysts and care sector professionals, and holding events to disseminate findings and best practice. It was important, he said to keep people in care “at the centre of analytics” to make sure that we use analytics in a way that works for the people we want to benefit from the use of the data.

FCC wants to make sure that this important work will not only continue but be scaled up, and so it has found the community a new home: the Digitising Social Care team in the NHS Transformation Directorate. This will help spread the benefits of these projects more widely – and Peter is confident that the programme’s achievements to date will “help transform the sector as a whole.”