Insufficient funding and a lack of community care provision is having a detrimental impact on the wellbeing, health and happiness of people living with autism and learning disabilities in the UK.
The House of Commons Health and Social Care Committee inquiry into the treatment of people with autism and learning disabilities published its report in July. The report stated that “people with autism and learning disabilities are being denied their right to live independent, free and fulfilled lives” in the community.
MPs heard that more than 2,000 people with a learning disability or autism are stuck in inpatient care settings and the average length of stay in an Assessment and Treatment Unit (ATU) is now six years, largely because there is no suitable community care to move on to.
While the UK government’s new National Disability Strategy promises renewed investment in housing and accessibility, however no immediate answer to the financial difficulties is likely in the wake of the COVID-19 pandemic.
At Lilli we believe that by embracing advances in technology and a new way of thinking about care, we can empower individuals to not only regain the independence they deserve, but also thrive within their own setting.
During the pandemic we have been really encouraged to see that in Southwest England the NHS has been using remote monitoring and technology-based solutions that improve outcomes without using extra resources.
They supported the use of remote monitoring to help people living with a range of learning disabilities and other long-term medical conditions such as diabetes, arthritis, and heart conditions.
They also used the technology to increase the uptake of regular health checks and improve the quality of resulting health action plans.
What makes ML-based solutions such as Lilli uniquely pertinent is its ability to learn from masses of service-user data, spot patterns and flag up when an individual might need help to prevent more serious deterioration in a condition.
In a home or residential care setting we believe that this has huge potential.
How technology can improve lives
Lilli cleverly uses data from sensors in a service users home that can monitor ar range of behaviours, such as movement, activity and energy use from domestic appliances to establish patterns of behaviour, this means that Lilli can spot when an individual’s behaviour changes from what is normally expected.
The data collected alerts care providers so that they can intervene early, before a potential problem develops into something that requires a more complex treatment.That could initially be a phone call or visit to check that the individual is ok.
The accuracy of the data and the knowledge obtained means that caregivers can set thresholds appropriate to a client’s condition and create a bespoke ‘flightpath’ of what is normal for that individual; alerting care providers if their behaviour changes. For example, this may be more frequent visits to the toilet in the night, or less drinks throughout the day.
What makes Lilli unique is its ability to learn from the wealth of service user data collected. As this data is tailored to the individual, it provides caregivers and clinicians with firm evidence that they may struggle to obtain otherwise; especially if the service user isn’t able to discuss symptoms of a new problem or issue.
Sharing data for good
There is a clear opportunity to build knowledge and skills of front-line workers to produce long lasting and impactful results for vulnerable individual receiving care.
The days when data was hard to process and understand have gone. Today’s behavioural ML technology is not only capable of analysing huge amounts of data, but its insights are immediately clear to providers and caregivers, making it simple to understand and then put into action.
The accuracy of the data and the insights extracted reduces unnecessary call-outs and care visits, while providing firm evidence for decisions to be made about care and resource allocation. The easy accessibility of rich data means that where service-users may not be unable to discuss symptoms of a new problem, the insights from the data provide care-givers and clinicians with firm evidence they could never obtain otherwise.
The data can be easily formatted so different organisations in shared care pathways and networks can also access it. By working together Lilli believes that ML technology can have a huge impact by improving lives and quality of life for those living with disabilities.
The future of care
The tides are certainly changing on an age-old prevention model of care.
If we are to rise to the challenge of providing high quality and create a sustainable proactive solution, Lilli believes that we must all support a new way of thinking.
With low costs of implementation, ML-driven behavioural analytics systems have major potential to help solve the significant problems care-providers face when trying to give people with learning disabilities a better quality of life. A recent trial of the Lilli solution in Dorset explored in this BBC article, for example, is saving nearly £4,000 per person annually through reduced visiting of elderly people and those with long-term conditions. These advances in technology can enable people with learning disabilities to live with greater independence and dignity, which is what any society should be striving for.