Kingston Council: Using AI in Adult Social Care administration

To reduce the time burden administrative tasks place on social workers, Kingston Council has been working collaboratively with Beam to pilot Magic Notes. This AI-powered solution aims to streamline the process of writing case notes and assessments, freeing up valuable time for social workers to focus on direct client care.

The demand for adult social care services has been steadily increasing across most local authorities, posing a significant challenge to the sustainability of existing care frameworks. According to the NHS’s Adult Social Care dashboard, there has been an average annual increase in new case demand of 2 to 5 per cent since 2017, with Kingston experiencing a surge of approximately 14 per cent. Traditionally, social workers take minimal notes during care visits to maintain personal, face-to-face interaction with clients, but this can mean it takes longer to complete a report afterwards. By using Beam to automate the transcription and summarisation of care visits and to output those summaries in a format that can be easily input to the case management system, Kingston seeks to make a substantial impact not just on the efficiency but also the effectiveness of adult social care delivery.

The project aimed to adapt Beam's existing product, which was initially designed for their own caseworkers, to be used by social workers on mobile ‘phones during real-world conversations. The primary objective was to create a simple and user-friendly solution, accounting for the varying technical proficiency of social workers. The development process involved creating new user journeys to ensure the solution was intuitive and easy to use on mobile devices.

To train the AI model, anonymised data from templates and assessments previously written by social workers was provided to Beam’s AI. This data was used to ensure that the AI's output matched the required level of detail and populated the correct fields within the case management system.

The development process was completed at pace. Launched in January, the solution was ready for pilot by the start of February. The pilot initially included only three social workers, but quickly expanded to encompass over 10. Use cases grew from the initial case reviews only to include supervisions, occupational therapy assessments, and care needs assessments, enhancing the tool's functionality and value.

Kingston has made keeping our client’s data safe a primary principle of the project. As a result, Beam deployed an enterprise version of ChatGPT within their environment, ensuring all sensitive data remained under their control. A comprehensive Data Processing Agreement (DPA) was established with Beam, outlining data access, processing protocols, and employee Disclosure and Barring Service (DBS) checks.

Furthermore, a thorough Data Protection Impact Assessment (DPIA) proactively identified and mitigated potential data privacy concerns. By meticulously examining data flows, storage mechanisms, and access controls, the council pinpointed and addressed potential risks.

As a result have been made to Kingston’s online privacy notice to encompass Magic Notes usage, but practitioners will be expected to obtain consent for recording from meeting participants and explain the purpose of it to service users.

The rollout plan, along with full-scale implementation details, has been approved by Kingston’s Adult Social Care Transformation Board and a staged implementation is now under way.

Although the project is now live, we haven’t finished working with Beam to improve the system by continuing to test new templates, gathering user feedback, and making necessary adjustments to ensure Magic Notes remains effective and compliant. Beam and Kingston have developed a feedback process for staff to document how much time they’re saving and, most importantly, what they are managing to achieve with that time. Kingston receives a weekly digest of the feedback; it helps Kingston and Beam tune the templates as well as highlighting areas where training or further engagement may be necessary to improve takeup.

Kingston Council prioritised stakeholder engagement throughout the Magic Notes pilot. Social workers and the Adult Social Care operations manager witnessed a live demonstration to assess the tool's potential. Beam and Kingston’s digital team then collaborated with participants to define use cases for the proof of concept. Regular feedback sessions with participants and the manager ensured continued progress and addressed any concerns. To gain leadership buy-in, the heads of Adult Social Care and Digital & Data were also kept informed.

The training was designed to empower social workers for successful Magic Notes adoption. The comprehensive sessions covered project goals, benefits, and impact on daily workflows. Hands-on training familiarised participants with the application, its key features, functionalities, and best practices. Social workers explored the app
in a controlled environment, practising logging in, navigating, and using features. Role-playing exercises with colleagues further solidified learning by simulating real-world scenarios with Magic Notes. Finally, Beam offered shadowing support for additional on-site guidance.

Initial results from the Magic Notes pilot are promising. Social workers reported significant time savings in completing case notes and assessments, with an average reduction of 50 to 60 per cent. The most dramatic impact was observed in supervision write-ups, where the process went from taking 40 minutes to less than 10 minutes using Magic Notes.

The accuracy of Magic Notes' transcripts surpassed expectations. While the project team initially aimed for 85 per cent accuracy, the results yielded an impressive 96 per cent plus. This efficiency extends beyond on-site visits, as social workers have utilised the tool to dictate notes for AI transcription and summarisation.

Social workers highlighted that they regularly alter the transcriptions and summaries to tailor them to their own writing style and add in additional detail, emphasising Magic Notes as an assistive tool rather than a replacement for their expertise.

Kingston Council employed a data-driven approach to assess Magic Notes' financial viability. Focusing on time savings demonstrated, the council have been able to provide an efficiency saving to improve our prevention services.

To further strengthen the case, the council analysed specific use cases like supervisions, where Magic Notes reduced note taking by around 75 per cent. They calculated the net financial benefit per supervision, factoring in both time saved and the Magic Notes solution cost.

Recognising the tool's scalability, the council could potentially reduce their cost of time writing assessment and case notes by up to 50 per cent.

The evaluation identified limitations for service users with low verbal skills or mental capacity. Magic Notes relies on clear audio, and conversations with reduced detail or poor audio quality resulted in inaccurate transcripts. This shows that Magic Notes is not a perfect solution for all user groups. Testing continues with these user groups
though to see if the product can be improved.

Technical challenges emerged during the initial proof of concept, including name misrecognition, information repetition, and background noise impacting accuracy. However, the strong partnership between Kingston Council and Beam ensured a swift resolution. Beam introduced features to reduce the impact of background noise and improve accuracy and also provided feedback mechanisms for social workers to refine templates, fostering continuous improvement.

One thing that came out during testing was different use cases for what was initially thought of as a single process - supervision. Managers supervising seniors or team leaders talked about different things to seniors supervising case workers and so a different template was required.

The iterative improvement of the tool driven by Kingston social workers has paved the way for several other councils to pilot Magic Notes.

Contact [email protected] if you would like to find out more.