AI
near-misses or care plans that are not up to scratch. For example, it might notice that a carer is writing fewer notes than they did last week or the week before. The quality of notes inputted into a system that charts the interactions a carer has had with residents gives you an insight into how they do their job. For example, there might be a time when they write fewer notes than they have done previously. This could indicate that the carer is having problems at home, is unwell, or needs additional support. It provides an alarm system that allows care managers to step in and nip potential problems in the bud. The ability to predict events before they happen is a huge bonus to care managers. If you are a provider across a group of care homes, you are constantly scanning your homes, wondering which are doing things better, what best practice looks like, and how you can build that from one location into another. AI can look at all those people supported, all the care times and interactions, and revert it backwards. So, it starts from the good outcomes and works back to find out what factors were in place to ensure the best result. It is always good to start with outcomes and find out what care practices have contributed to them. AI enables us to find those care patterns. For example, our AI data has shown that a certain group of individuals exhibit better wound healing than others. Now we can see this good outcome, we are tracing backwards to try and find out what has contributed to this so that it can inform how carers treat wounds going forward.
Onboarding new residents with AI assistance If you are onboarding a new resident into a care home and their family comes in and has a meeting with you, AI can listen in on that conversation and summarise it quickly. Then you have a document listing key points about the needs of that individual from the family. It is a much more person-centred way of onboarding somebody into a care home as it gives you the family’s voice in addition to the supported person’s voice. That can then help you build an exemplary care plan.
At the moment, a lot of onboarding is done badly. A care home might use documentation from the local authority and the hospital discharge team, but that might lack key personal insights. What AI can do is learn to zone in on elements that are of particular importance to a resident. It can also enable carers to access free text information during onboarding that captures their needs to build a care delivery plan for the resident.
The onboarding process is important, as it is the foundation of a care plan and serves as a road map for an individual’s care. The more personal information it contains, the better, so in this instance, AI is again creating efficiencies that improve person- centred care.
AI, best practices, and mitigating risk We can combine the data we receive from our clients with research that outlines things like best practices and that is useful to those who are delivering care. Think about a carer who has got 10 people they
need to look after every day with 10 things on every resident’s to-do list. They have a lot to process. AI can do a lot of work and help them find the most important information. It can say: ‘Based on research and the data you have entered for this type of resident, here are the three most important actions required’.
This can be a risky strategy. Part of our job is to take that seriously, and part of our AI strategy is to make sure that any information we give to our customers has been tested and validated technically, and via our experts. It has to go through a rigorous process before we deliver it. We cannot give caregivers any bits of information that have been dredged up from the internet. In the early days, Google’s AI told people how to make pasta from glue! While we want to embrace innovation, we cannot be reckless. When we talk about AI and social care, we must talk about risk. It cannot be something we shy away from. Managing the risk and governing how we use AI is something we factored in from day one of our design activity. We have built a system that knows where AI fails and where it excels, and then designs the software that enables it to support caregivers successfully and safely. We are also making sure we adhere to
data privacy and data security policies. All our partners undergo rigorous scrutiny because we have to safeguard our clients’ data. We anonymise data where we should and then, in any analysis we present, it is done in aggregate levels as we have to protect the privacy of those we support.
We are building a future where AI is an integral part of delivering exceptional care
May 2025
www.thecarehomeenvironment.com
Personalised care plans A care plan is a personalised roadmap, guiding caregivers on how to provide the best possible support for each resident. AI helps to improve them by analysing existing care plans, comparing them to best-case examples, learning what elements contribute to positive outcomes, and adapting to each resident’s evolving needs. We are not simply following a standard template; we are creating a unique care journey tailored to each person’s specific requirements and preferences. For instance, AI might suggest activities perfectly matched to a resident’s interests, alert the care team to the need for additional social interaction, or highlight potential dietary adjustments based on observed eating patterns.
It means that those receiving care get the support and care they require with a level of
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