Exploring an evidence-based, shared and scalable digital resource approach which enables local authorities to match technology enabled care with older adults' needs in order to deliver efficiency gains.

Full Application: Not funded at this stage

We collected evidence during our initial LDF project that slow progress and duplication was due to the lack of a sector specific structure, organisation, and network for coordinating efforts across the West Midlands.

The problems and causes revealed by this project were: 

1 – No single technology product suits all citizens because they are a diverse group with individual complex needs.

2 – Working out which product to choose for a particular citizen is extremely difficult because of the huge number of products available on the market and the lack of evidence for how well they meet the targeted needs.  Some are used by other local authorities (LAs) some are not; some are commercially sustainable but not in a care setting. 

3 – Anecdotal evidence suggests that LAs and NHS Trusts are bombarded on a daily basis from technology and equipment organisations, all stating how their product is the best thing to come to market and how it can enable citizens to remain independent in their homes for longer.

4 – There is little robust assessment or awareness of these products and no single widely used methodology for collecting evidence.

5 – Where testing does take place it often duplicates efforts elsewhere within LAs and potentially the NHS, without any widespread sharing of results.

In short, LAs are wasting resources of people, productivity and funding when implementing technologies and equipment with limited knowledge of best practice. 

This project will explore whether the concept of a collaborative approach, through a not-for-profit organisation, using robust methodology on behalf of all LAs would a) be of interest to LAs and b) would work.

Dependencies and Stakeholders

We need to work with:

  • 152 LAs with adult social services responsibilities to obtain their thoughts on having a single co-ordinated approach through a not-for-profit organisation. 
  • The Association of Directors of Adult Social Services (ADASS).
  • Citizens in the community. 
  • West Midlands Combined Authority (WMCA).
  • West Midlands Academic Health Sciences Network (WMAHSN).
  • Senior Social Workers and Occupational Therapists. 
  • Care providers and their Carers.
  • Care Quality Commission.

Findings from LDF 1

Summary report: https://localdigital.gov.uk/wp-content/uploads/2019/05/LDF-Homecare-User-Research-Report.pdf

Supporting Research report: https://localdigital.gov.uk/wp-content/uploads/2019/05/LDF-Homecare-Appendix-3-User-and-desk-based-research-on-Improving-Home-Care-for-Older-Adults.pdf

Hypotheses for this proposal are:

  1. the methods in our LDF report for evaluating technology can build a shared evidence-based decision support system of best practice to inform all LAs and self-funders;
  2. there is widespread duplication of effort within councils assessing technology and equipment, with varying rigour;
  3. shared evidence-based data provides a basis for machine-learning to automate matching of users to technology;
  4. there is an appetite within LAs to make use of an independent not-for-profit to advise on choices.

We will test our hypotheses by applying the methods detailed in (1) via action research with potential users and their carers. The aim will be to understand needs and abilities, enable the creation of detailed ‘user personas’ to enable technology matching, and demonstrate how the evidence database can be accumulated.

The outcome measures will represent success for LAs but with a user feedback loop. We will give all parties in the care network access to a health and wellbeing assessment web service. For speed of implementation for this project it will be adapted from the GRiST decision support platform (www.egrist.org), developed by Aston University and used by the NHS. 

This testing and matching system will generate a rich set of quantitative data that can empirically determine which technologies work best in different circumstances and for different user personas. We will assess how machine-learning techniques could be applied to generate matches.

We will engage with LAs in the West Midlands (and wider if necessary) using a questionnaire initially with the following themes:

  • what is currently used for Adult Social Care (ASC) and what are the outcomes;
  • what if anything is being researched and what testing is undertaken and by whom;
  • how are the results of testing shared across LAs and beyond; and
  • what level of co-production is undertaken with citizens during the research and testing and with what impact.

We will work with the West Midlands ADASS group to undertake workshops that evaluate the findings of the questionnaire and develop ideas.

Results will inform the feasibility of a not-for-profit organisation providing LAs with a decision support system, including:

  1. independent and impartial assessment of individual technology products against the agreed methodology, including feedback from users; 
  2. test pilots in real world conditions to ensure it meets operational needs;
  3. machine-learning algorithms;
  4. published ratings, in an interactive website for self-funders and informal carers;
  5. protocols for how stakeholders can provide and share information.

 In our first discovery round we showed that deploying the right technology and equipment to meet a citizen’s need has the potential to improve outcomes and lead to savings in adult social budgets of up to 15%. We estimate there could be a potential saving of around £1bn from an overall ASC budget of £15 bn, on the basis that not all citizens will be willing or able to use technology and equipment. (Information source: NAO Report, 2018)

The personalisation of equipment and technology for citizens enables them to leave residential care or remain at home, which is of significant benefit to their health and wellbeing.

With the plethora of digital and sensory products, most LAs have not had time or ability to totally explore the use and impact of these products. This has resulted in equipment being provided that cannot be sustained in the UK.

Our LDF research also revealed concerns from some citizens and their carers about using technology and equipment. They were worried that they would not be suitably supported  and did not always trust what information was being collected or how it was being used. Others were more positive, seeing significant opportunities in enabling them and their carers to remain independent and at home for as long as possible. 

The appetite for councils to deploy personalised technology to citizens can be clearly evidenced in the investment by Hampshire County Council of £67m

Worcestershire Telecare stated that technology deployed to their citizens assessed by a Technician rather than a Social Care Worker has contributed to savings of around 15%, in their citizens’ care packages funded by ASC; or for every £1 invested £18 has been saved in ASC.

A recent care technology landscape review undertaken by SOCITM (June 2019) concluded that:  

“digital transformation is having significant, wide-ranging impact on every aspect of our lives. At the same time, the UK is facing a health and social care crisis due to an ageing population and budget constraints. National and Local Government leaders see digital technology as a key factor in helping to improve sustainability of services”

They further conclude that: 

“despite a suite of national initiatives over the last decade only a fraction of the potential of care technology has been deployed. A key reason for this has been limited sound evidence on the benefits in investing in care technology, especially cashable savings”

We are partnering with Shropshire Council who are keen to build on the innovative adult social care technology called “The Bridge” developed as part of the LGA Social Digital Innovation Programme (SCDIP).  The results of this work were demonstrated at the ADASS national spring conference and can be utilised within this project. 

The other partners are experienced in working together on the previous LDF project and have a good understanding of each other’s strengths and working styles. 

We will have a project management team meeting of all partners each week, attending in person or via conference call. 

We will continue to use the online product, Trello, that was used to coordinate the LDF Round 1 project. 

An independent project manager to lead the project on behalf of the four councils will be identified.  

The GRiST website that will be developed and extended for the care technology decision support system already has a sophisticated group collaboration software and will be exploited for this project. 

A separate project website will be set up for the LDF but built on and sharing the same underlying platform. It will enable methods, data, and results to be integrated, shared, and evolved throughout the project.

Support from the LDCU would be welcome, for collaborating with other councils who have an interest in digital innovation. This would greatly help test our methods, collect results, and demonstrate how an evidence base can be grown and shared. At the same time, it will publicise the work and improve the likelihood of organisations paying for the resource so that it can be sustained and evolved.

Support from innovation hubs, clinical academic units, and other resources that help translate health research into practice would also be useful, both in terms of the translational elements and commercial considerations.

It would be beneficial to move quickly to understand how this type of organisation can be set up to benefit public services because the problems with choosing and implementing technology are experienced daily. It would also help prevent providers entering the market with products that do not deliver on promises or cannot be sustained and therefore disappoint citizens, putting them off alternatives that might have been much more beneficial.

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