Using AI in adult social care
An introduction to artificial intelligence (AI) in adult social care and best practice for adult social care providers.
Summary
AI has sparked important discussions around ethics. These discussions help us to make informed decisions to achieve the best possible outcomes for those receiving care and support.
The Oxford Project on the responsible use of generative AI in social care has brought together organisations from across the sector to discuss these issues. They have co-produced guidance on the responsible use of AI in care.
As AI continues to evolve, its influence on adult social care is expected to grow. New AI solutions are likely to emerge that will further enhance outcomes and experiences for care recipients. However, many adult social care providers are still in the early stages of exploring AI and have yet to implement AI solutions within their organisations.
AI solutions in adult social care delivery
A range of AI solutions are already being used to support the direct delivery of adult social care and support. They include:
- sensor-based technologies, including acoustic monitoring
- chat bots
- facial recognition technology
- data collection and analytics technologies
These types of solutions can deliver improvements in hands-on, immediate care to individuals in accommodation-based settings. They can also deliver life-changing preventative and reactive care for people living in their own homes.
Care planning and care assessment tools
Generative AI is being used to create individual care plans and care assessments. AI tools can fast track high workload tasks such as auditing and writing care plans, daily monitoring and logging data. These AI-backed care planning software technologies can also improve understanding and communication within care planning documentation.
AI care planning software may cut down the time spent doing administrative tasks. This can allow care staff more time to give people care, and lead to better outcomes for them.
Issues to be aware of
Evidence that generative AI can create truly personalised care plans is currently limited.
If AI is used in care planning, a member of care staff must review the plan to make sure it’s accurate. Care organisations must ensure that any use of AI does not breach data protection legislation - see ‘Best practice guidance’ below.
Sensor-based technology
AI-backed sensors can:
- monitor movement
- monitor sound
- automatically switch on lights for someone who is getting up in the night
- keep track of vital signs like heart rate, breathing and body temperature in real time and send alerts to caregivers if any deterioration is detected
- monitor and detect changes in a person’s gait which may suggest an increased risk of frailty
This type of monitoring can enable caregivers to spot problems early and address health issues before they get more serious. AI-backed sensor-based technology does more than track and report data. It also analyses patterns to intelligently predict when a potentially critical situation will arise.
Much like a human, the AI system has the capability to think independently and alert care givers. This allows for a timely response, and for appropriate interventions or changes in care and support to be activated immediately.
Acoustic monitoring is a subset of sensor-based technologies. It’s typically used to monitor falls and to enable maximum independence. Acoustic monitoring systems rely on sensors that pick up sounds in an environment and some of them now incorporate AI.
These systems are especially useful at night in care settings. They can listen for disturbances and alert caregivers, reducing the need for frequent intrusive nightly checks that might disrupt residents’ sleep.
For more information, read:
- WCS Care case study on the benefits of using a night-time acoustic monitoring system
- How an AI technology cut falls by 84% for Hartland House Care Home on their experience of using optical care sensor-based AI technology (the Nobi Smart Lamp) to prevent falls and improve the sleep patterns of residents in care homes
Facial recognition technology and pain management
Facial recognition AI can be used as a pain assessment support tool. The software looks at a person’s face and analyses the images using AI-driven facial recognition. It picks out and records facial muscle movements that indicate pain.
This is particularly useful when the individual may not be able to vocalise that they are in pain, or may be reluctant to report that they are in pain.
The caregiver then uses the AI tool’s guided framework to observe and record pain-related behaviours, such as movement and how the person vocalises their pain. Finally, the AI technology calculates an overall pain score. The caregiver can then decide how to respond appropriately to the person.
Read the Heathfield Residential Home: facial analysis technology to identify pain .
Data collection and analytics technologies
AI-backed data collection and analytics technologies are being used to highlight patterns in behaviour or interactions that affect an individual’s wellbeing. For example, a digitised residential care home incident reporting system highlighted that several residents were experiencing falls within the care home.
Using AI to analyse the data, it was determined that the incidents were taking place in the same location, at the same time of day. Staff investigated and found out that the cause of the falls was strong sunlight coming in through the window, impairing vision and leading to unsteadiness.
Using the AI outputs, staff were able to take proactive and preventative action to adjust the physical environment by installing blinds. This led to a decrease in the number of falls and subsequent hospitalisations for residents.
Chat bots
Chat bots are now being introduced into front line care and support to provide conversations and resources to those who need them.
AI-based chat bots can respond to questions or conversations and mimic a human-like response. This can be delivered as the first step in helpline response for those needing support, for example in mental health and community reablement services.
A chat bot service can be delivered 24 hours a day, 7 days a week and can provide an immediate conversational support function.
Administrative and support services
A range of AI-driven apps and platforms are now available and are being used in adult social care settings. These may be able to:
- reduce the burden of administrative, planning and auditing tasks
- increase service efficiencies
- allow staff to spend more meaningful face-to-face time with those who access care and support services
Meetings administration
AI applications such as Microsoft Copilot and Claude can be used in meetings to record and produce both detailed and summary meeting notes, action lists and next steps. This functionality can automate administrative tasks and release time for colleagues to focus on other tasks.
It’s important that a human reviews anything that AI produces.
Generating business plans and strategies
AI can help turn personalised action items or the recorded content of a business planning or strategy meeting into plans or draft strategies for your organisation. It’s important to keep control of your data so that your hard work and original ideas stay private, if you do not want to share them.
If you’re using an open AI tool to generate business plans and strategies you can protect your organisation by:
- not inputting any confidential information
- hiding your organisation’s name
This will help prevent any misuse or copying of your work.
HR functions
You can use AI to support the recruitment and onboarding of new staff. AI can increase the efficiency of automated responses, vacancy administration and onboarding scheduling. This will free up time for staff to review and respond on a one-to-one basis where required.
More applicants are now using AI to generate their CVs or job applications. It’s a good idea to decide if your organisation is happy to receive AI-generated CVs and applications. If not, we recommend that you make that clear in your job adverts.
Auditing tools
Some care services are using AI to help with monitoring audits over multiple sites. When a member of staff completes an audit checklist, the AI automatically creates a summary of completed activities and flags if there is anything else that needs to be done.
Some care providers say that this is making their organisations more operationally effective as well as saving staff time.
Best practice guidance
AI’s impact is increasingly relevant to adult social care. The reduction in staff hours and cost efficiencies achieved in other industries highlight the considerable potential for AI. However, AI may not always be the appropriate solution in adult social care - read this best practice guidance to help you decide.
Input high quality data
The success and reliability of AI systems depends on the quality of data you provide. It’s important to make sure that all the data being used is correct and contains all the relevant information needed. The data should also be well structured and organised.
Consider data protection laws
You’ll need to make sure that you are complying with UK General Data Protection Regulation (GDPR) when using AI tools. In particular, you’ll need to consider:
- where the data is being processed and if it’s in the European Economic Area - you can normally find this out from the technology’s privacy policy
- how you’ll tell people about how their data is being used
If in doubt, speak to your software supplier.
If you’re using a free or online tool, you should not use personally identifiable information because you would be providing confidential information to a third party. As you would not have a contract with the technology supplier, you will have no way of guaranteeing the safety of that information or how the data will be used.
Under UK law, people have rights about how their data is used. You must tell people how you’re processing their data in the course of your activities. Digital Care Hub’s free Better Security Better Care programme can provide support on fulfilling your data protection obligations.
Maintaining ethics
You should consider how your organisation can use AI ethically. The Oxford Project on the responsible use of generative AI in social care has developed a principles framework and guidance on how to use this in practice (linked to previously). They’ve identified the following core principles for the ethical use of AI:
- truth
- transparency
- equity
- trust
- accessibility
- humanity
- responsiveness
Be aware of and mitigate bias
AI can show biases based on the data it’s trained on and this can affect its outputs.
Bias in AI means unfair favouritism in the algorithms and data. Biases can come from historical and social inequalities in the training data (the data that is fed into the AI model), algorithm design, or human involvement in data curation and labelling.
Bias in AI can:
- reinforce stereotypes
- cause discrimination
- affect decisions based on biased outputs
Equity is an important ethical principle that underpins the responsible use of AI as algorithms can unintentionally reinforce existing inequalities. Read Digital Care Hub case study: ensuring fairness for all.
Upskill your workforce
As with any new technology, it’s essential to have the training and development in place to make sure staff are skilled and confident in using AI. The success of AI will depend on the data it’s given and how people feel about using it.
Consider identifying digital champions within your staff teams who can act as the internal experts on your AI systems. They can help:
- other users with their questions and issues
- train other users, making system implementations and upgrades smoother
Read guidance on introducing digital champions in social care organisations.
Always have a human review
We recommend that you always include a human review of any AI-generated outputs to:
- ensure accuracy and fairness
- make sure they meets your organisational standards and policies
You may need to set up review guidelines or quality controls to make sure that human processes continue to sit alongside any AI developments.
It’s best to define the human role within any use of AI and to produce an AI policy that answers questions like:
- who will be responsible for the decisions and tasks of the AI?
- how does your organisation oversee your use of AI?
- who has accountability for this role?
- how will you approach AI adoption?
- do you use a particular framework or decision tool to assess AI’s appropriateness?
Outline the process for choosing AI tools
This is an important step in determining what you need any new AI tool to do across the organisation and analysing if a specific AI technology can cover that.
It’s best practice to define what you hope to achieve before choosing any technology. You may wish to follow this checklist:
- Create a specification by listing what you hope to achieve with the technology .
- Speak to the people you support and staff to get their feedback.
- Define the potential benefits and risks of using this type of technology and compare in a table.
- Identify measurable outcomes you can use to assess success,
Evaluate the financial cost
Adopting any new AI technology will involve a cost. Follow these steps to guide you through the financial process:
- Use your table that compares the benefits and risks of the AI technology.
- Compare this against the cost of the AI tool and consider if it is value for money. Look at things like hardware and software costs, as well as more indirect costs such as staff training and system changes .
- Input this data into a financial plan to track your spending and income. Always be aware of hidden costs and be ready to adjust your plan as needed,
Introduce an AI policy
All organisations should consider having an AI policy, even if your policy is that staff cannot use AI for work purposes. This way staff and stakeholders are aware of your organisation’s stance on AI adoption and how you plan to use it in your organisation. This is important as there’s still mistrust and concerns around the use of AI.
Your AI policy could include:
- how different roles will be required to interact with AI - this can differ between senior leadership and front line care delivery staff
- a review checklist to help plan the best time for the continual human review
You should disseminate your AI policy among your staff to ensure that everyone is included and consulted in the AI journey.
Continuously improve
You should continuously improve your use of AI systems by seeking feedback from both human reviewers and the AI system itself (if possible). Use this feedback to identify areas for improvement and make necessary adjustments to the human review process.
This can be part of your AI policy, or you can write it in as a stage in your organisation’s AI process or journey. As the AI evolves and your organisation’s needs change, remember to adapt the review process accordingly.