Nick Weston, Chief Commercial Officer, Lilli
In the next 25 years, the number of people older than 85 will double to 2.6 million in England. A rapidly aging population alongside a drastically underfunded NHS is now placing unprecedented levels of pressure on care services, and it’s a growing issue that the UK Government is taking steps to counteract. To plug the growing financial gap, the introduction of the Health and Social Care Levy in 2022 will provide some much needed funding, while £150 million has also been set aside to drive greater adoption of technology and achieve widespread digitisation as part of a wider ten-year plan.
Increased funding will however only go so far in making a difference. To truly transform the care industry, effective use of the most appropriate technology is going to be vital to help care for people in their homes. The methodology behind this approach is one of proactivity.
By taking a proactive approach, organisations can evolve the way they care for older and vulnerable people, solving one of society’s most pressing problems at a time of stretched resources. This can be achieved by combining machine learning (ML), behavioural data analytics and sensor technology in a cloud-based solution. ML in particular has huge potential in a home care setting due to its ability to harness masses of service-user and patient data to learn and identify deviations.
It works by creating a baseline of each individual service-user’s normal pattern of behaviour in their home by monitoring everyday activities such as movement, temperature, night-time activity and eating and drinking habits. When a person’s behaviour deviates from that baseline, such as a decrease in movement or fewer drinking occurrences, it may be an indication of a possible deterioration in health or wellbeing.
With the deviation flagged, alerts are then sent to care teams along with access to detailed reports of behaviour, enabling follow-up interventions to be made quickly by care providers, GPs, district nurses or community rehabilitation teams. This highly personalised approach means that teams can then devise a solution uniquely appropropriate to their individual needs that enables prolonged independence at home for service users.
Protecting patient privacy
Service-users will likely have initial concerns about how potentially invasive proactive technology methods are, and about sharing their data in this way. However, the way that ML can achieve these results is truly discreet in nature. Unobtrusive devices such as sensors and smart plugs remove the need for large, unpopular medical hardware or other space-taking solutions.
Rigorous security protocols enable patient data to remain protected via policy layers and encryption principles, and consent is at the heart of data collection, ensuring that it isn’t shared with third-party organisations or applications. The result is a preventive and sensitive approach that respects service-user privacy, all for as little as £1.50 per user per day.
Futureproofing care services
Alongside the benefits to service-users, technology-driven proactive care methods also make a positive difference to the care organisations that utilise it. The data generated is key to supporting front-line care resources, allowing them to care and manage those that need care much more effectively and safely. Firm evidence allows care organisations to allocate their resources effectively, which ultimately leads to an increase in the number of people that can be cared for without reducing the quality-of-care provision in any way.
Alongside decreased incidences of unnecessary and costly callouts, proactive technology also reduces the likelihood of more complex and costly treatment or admission to hospital. The result is that in conjunction with improved care, there’s a reduction in the strain being placed on the wider health and social care services outside the home, enabling better clinical pathways.
Data as the driver
A proactive approach, underpinned by supporting technology, allows care organisations to weather the storm of underfunding and consequent strain on resources as the number of older people in the UK continues to rise. At the core of this is the effective, secure and ethical use of service-user data. Data has been identified as the key to reshaping health and social care moving forward by the UK Government, following its success in saving lives during the Covid-19 pandemic. It empowers care organisations to revolutionise how care is provided, enabling both better allocation of resources and ultimately allowing people to live more independent and fulfilled lives, in their own homes for longer.