‘The Bridge’ is a tool for data visualisation, designed to display public sector data and provide effective economic forecasting and market insights. Follow-on funding was granted to share the project and its learning with other councils.
In 2018, Social Care Digital Innovation Programme (SCDIP) funding was granted to support the development of a new intelligence platform, utilising both quantitative data on needs and assets, and qualitative data across different areas and demographics in the region. The Bridge was developed as a result of this funding and can be used to understand and map how current and future care needs overlap with community assets. The economic forecasting and data visualisation capabilities can be used to inform commissioning decisions, strengthen local care provider markets, and inform the development of future strategy.
Social care providers are facing increasing pressure due to growing demand, exacerbated by an ageing population. In the West Midlands the population of over-65s is expected to increase by 19 per cent by 2025.
The Bridge was designed to address:
The poor-quality spatial understanding of the health and social care economy, which hinders strategic planning.
This negatively impacts the quality and efficiency of services, particularly during the current period of increasing demand. The project team highlighted the importance of displaying data in a convenient and understandable way and ensuring that it is not overwhelming for those utilising it. This can allow decision-makers to make informed decisions about commissioning and addressing demand quickly and efficiently.
Key aims and achievements
- Visualising and mapping data across health, social care, housing and economic development to inform decision-making.
- Use the tool to visualise supply and demand to negotiate better rates for care and deliver cost savings.
- Combine health care and housing data to predict future needs, for example thermal mapping has informed HeatSavers interventions reducing the likelihood of entering A&E by 20 per cent.
Additional funding was provided to build upon the work undertaken to develop the Bridge, and to share the product, project outcomes, and learnings with other councils. In its application, Shropshire Council outlined that alongside investment in learning and collaboration, the follow-on funding would be used to attract match-funding for the West Midlands Data and Digital Collaborative.
Part of the follow-on funding was allocated to support regional data and digital collaborative events. In February 2020, the team held an event with the Academic Health Science Network (AHSN) and a Microsoft ‘tools for improvement’ event. A ‘technology in the home’ event was held with the LGA in April 2020. The team also used the follow-on funding to attend a West Midlands Academic Health Science Network event. Capacity was also purchased from Shropshire Council to assist in sharing the learning from the Bridge within the region, as well as promoting data visualisation more generally.
The team also appointed an associate to assist with building the understanding around data science, artificial intelligence, and machine learning. This assignment involved investigating the relevance and potential of these technologies in adult social care.
Finally, the follow-on funding was used to produce a guide outlining the partners active in this field, with a view to building stronger collaboration between West Midlands ADASS, the Commissioning Support Unit, AHSN, and the National Institute for Health Research.
The tool provides data across several sectors (eg health, social care, housing, economic development) to decision-makers in a way that is designed to better communicate the data’s meaning and value. This allows decision-makers, budget holders, and politicians to gain better insight and more “actionable intelligence” from what has been traditionally seen as “an overwhelming mess of data, graphs and pie charts”.
For example, the tool could be used to examine the impact of a new care home and how it could contribute to wider economic and social objectives. This functionality is being used to inform strategic discussions within Shropshire Council.
Commissioners could also use the tool to visualise areas of supply and demand, as well as compare care package prices across the region. This means that they can potentially negotiate better rates and therefore deliver significant savings over time. Finally, the Bridge can be used to indicate areas of hidden future demand by using household occupancy data, care records, and thermal mapping to indicate those at high risk of attending A&E within a year. Research from the SCDIP 2018/19 phase found that using this data to inform HeatSavers interventions reduced the likelihood of entering A&E by 20 per cent.
At the Association of Directors of Adult Services (ADASS) Spring Conference in 2019, 71 per cent of attendees agreed / strongly agreed that the Bridge would help to address challenges faced locally. Respondents were asked what they would use the Bridge for and 42 per cent said commissioning, followed by 21 per cent for prediction, and 17 per cent for business intelligence.
The team suggested that the ability of the Bridge to predict future demand would support decision-makers to make preventative interventions, leading directly to savings through reductions in costs, improved efficiency, and better outcomes for people. The Bridge also visualises spend across the county to identify patterns and outliers in care packages, and this has proven to be a key advantage for commissioners when negotiating prices for care packages. Direct savings through reductions in A&E visits can be measured monetarily.
The team also suggested that by automating analysis and data visualisation, capacity can be created for data, intelligence, and performance teams in local government by reducing the burden of reporting. This additional capacity could then be put to better use improving the quality of local authority data and collection, and utilising the valuable talent of these teams for more creative data analysis. This could translate to monetary savings if these employees can be redeployed elsewhere.
The team highlighted that this project is not just about collecting more data; its focus is on having quality analysis in place. It was suggested that other areas within the council are looking to invest in better analysis as a result of seeing how well data can be used to target resources. This reflects the project’s success in sharing the benefits of utilising the Bridge.
- Ability to experiment: The project team highlighted that innovative work like this is only possible due to schemes like SCDIP, which encourage experimentation. As the intention of the work is to develop new and exciting opportunities, the team felt as though they could explore options and experiment in a way not always practical in the public sector. The culture of innovation had a positive impact on the project.
- Improved collaboration: The project helped to open doors within the council to encourage data sharing in areas where they had previously been reluctant to share information. This allowed for a richer picture to be realised by expanded datasets.
- Data quality: The team have identified numerous areas for change and improvement in the data that has been collected, as well as measures that could improve the quality of public sector data in the future. This will make it possible to integrate systems and collaborate more effectively across boundaries and systems.
- Improved user research: Working with new technologies has led to the development of new user research methods that have helped understand what people need from their data. This insight has resulted in better data and informatics designs, making it easier for decision-makers to understand and make sense of increasing amounts of data and information.
Challenges and lessons learned
- Conducting user research: Regardless of the impact of Covid-19, the team suggested that access to training and support for conducting user research would have been beneficial as this was a steep learning curve for them. Guidance on conducting effective user research within innovation specifically would have been helpful, as explorative and iterative project culture is less prominent in the public sector.
- Learning from previous work: The team spoke to many individuals who referenced previous projects with similar aims and outputs. They often found that these were successful, but other factors like funding or staff changes caused them to end. Evidence and learnings from these projects were not widely available, and it would have been useful to have access or be aware of these upfront.
- Scale and coordination: The team recognised that the project has made significant progress but believed that more could be achieved with a more coordinated approach to research, developments and innovation for adult social care. The team pointed to examples of health care coordination (eg NHSD, NHSI, NHS AI Lab) but suggested that there was no social care equivalent that they knew of.
- Prioritisation: Although there has been enthusiasm for innovation and change in care it is not yet a stated priority with targets or performance indicators. As a result the team has found it difficult to keep work on data, technology and innovation from slipping down agendas impacting the rate of progress for the team's project and others like it.
Impact of Covid-19
- User research: The team noted that it was difficult to get people involved in user research or engagement, as this was often not seen as a high priority during the pandemic. It was hard to encourage people to think about and discuss the future when they were being presented with the more pressing challenges of the pandemic.
The project team were positive about the future potential and possibilities for expansion of this project. They had been working on expanding the capabilities of the Bridge with EY, looking into information governance and releasing more data for a richer dataset.
In terms of external scaling-up, the team had received interest from a neighbouring council, who were in discussions about implementing the Bridge at the time of writing. Discussions around the development of a version of the Bridge for this interested council highlighted the idea of ‘productising’ the tool to ensure that its functionality and usefulness are transferable to other areas. Progress on this was noted to be dependent on continued interest and the advancements made in the first few months of 2021.
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Discovery phase review (PDF)