Overview
A range of AI solutions are already being used to support the direct delivery of care and support. They include:
- sensor-based technologies, including acoustic monitoring,
- chat bots,
- facial recognition technology, and
- data collection and analytics technologies.
These types of solutions can deliver improvements in the hands-on, immediate care to individuals in accommodation-based settings and 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 on the time spent doing administrative tasks, allowing for care staff to give more time for those in receipt of care and support and leading to better outcomes.
Be aware
There is currently limited evidence that generative AI can create truly personalised care plans. If AI is used in care planning, the plan must be reviewed by a member of care staff to make sure it is accurate. See Tip 5 - Always Have a Human Review.
Care organisations must ensure that any use of AI does not breach data protection legislation. See Tip 2 - Consider Data Protection Laws and Legislation.
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 analyses patterns over a period to intelligently predict when a potentially critical situation will arise. Much like a human, the AI system has the capability to independently think and alert care givers, allowing for a timely response and for appropriate interventions or changes in care and support to be activated immediately.
Acoustic monitoring, a subset of sensor-based technologies, is typically used for falls monitoring and to enable maximum independence. Acoustic monitoring systems rely on sensors which pick up sounds in an environment and some of them now incorporate AI. These systems are especially useful at night in care settings, as they can listen for disturbances and alert caregivers, reducing the need for frequent intrusive (nightly checks that might disrupt residents' sleep.
- Case study: WCS Care on the benefits of using a night-time acoustic monitoring system.
- Case study: Lancashire and South Cumbria ICS 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 Supporting 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, picking out and recording facial muscle movements which are indicative of 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 pain is vocalised by the person. Finally, the AI technology calculates an overall pain score, and the caregiver can decide on how to respond appropriately to the person.
Data Collection and Analytics Technologies
AI-backed data collection and analytics technologies are being used to highlight patterns in behaviour or interactions which impact 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 through the window, impairing vision and leading to unsteadiness.
Using the AI outputs, staff were then able to take proactive and preventative action to adjust the physical environment by installing blinds. This led to a decrease in 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. It can be delivered 24-hours a day, seven days a week and provide that immediate conversational support function.