Helen Dempster, chief visionary officer, Karantis360, outlines the role IoT sensors are set to play in delivering highly effective, intelligence led 24x7 care during the winter months.
With the NHS’ admitted concerns about available resources and endemic bed blocking by the elderly who cannot safely return home, the arrival of winter is ramping up the pressure. And with just 57% of trusts confident they will be able to deliver safe, high-quality care this winter – and a 10% openly not confident, a much higher level than those overwhelmed by demand last winter, the picture is not looking good.
In one week alone last winter (2nd – 8th January 2017), the NHS had over 31,000 escalation beds open to cope with demand, the equivalent of opening an additional eight hospitals. Yet many of the emergency admissions of the elderly due to falls, pneumonia, even dehydration, are avoidable – if there was a way to better identify and proactively address emerging problems. But with carers spending no more than an hour or two with each client every day, how can the care sector achieve the timely interventions required to minimise emergency visits and ensure the elderly and vulnerable are safe at home whatever the weather?
Cold Care
Enabling the elderly and vulnerable to stay in their homes for as long as possible is the underpinning objective of our care model. Yet when carers have limited time with each client every day – and many individuals receive care from multiple individuals over a month, there are huge swathes of time when individuals are unchecked and limited opportunity for emerging problems to be identified.
Falls are an obvious concern; but during the winter there is an array of other problems that lead to huge demand on the NHS. Many elderly people are incredibly concerned about fuel costs, and as a result often fail to turn up the heating. Who knows whether an individual is eating enough to keep warm? Or boiling the kettle to make that essential hot drink? What happens when someone leaves the one warm room to venture to the bathroom, for example?
A fall in an unheated area of the home could be devastating – and require not only a trip to A&E but admission to hospital. Add in the inevitable flu epidemics and the fear of falling on ice that will result in many elderly not going outside, failing to get to the shops, and the winter can be both dangerous and lonely.
Vulnerable and Unchecked
Clearly the big gap in care is the 22 or 23 hours each day when an individual is not being visited or assessed by a carer. Of course, family members and neighbours may well pop by, but many elderly spend vast amounts of time alone – and it is during these times that problems can occur that then demand an emergency response and possible long term hospital admission.
And while both carers and cared alike are somewhat resistant to the idea of CCTV or biometric scanners due to the perceived intrusion, in contrast the use of IoT sensors is widely welcomed. Installing movement, humidity and temperature sensors across a home enables a care organisation to rapidly gain a picture of each individual’s day to day routine – information that is then key to flagging changes which could reveal a problem.
In addition to continually checking a home is at the correct temperature, there are a number of behaviours that can be an indicator of a person’s well-being. Has the client got up each morning; put the kettle on; opened the fridge; even followed their usual morning routine of opening the back door to feed the birds?
Intelligence Led Care
If something occurs – or doesn’t occur – that is out of that pattern, the care agency is alerted and can immediately respond, either by making a phone call to check whether the individual is okay, sending a carer to pop in, or, if appropriate, contacting a nearby family member. Indeed, with many care services only provided 7am to 10pm the ability to share this information with the near family via smart phone, ensures an individual is being monitored – in a low-key fashion – 24x7.
It is the speed with which behaviour changes can be identified that is key to achieving essential early intervention, intervention which works. Take for example, a patient with early stage dementia who had recently had a catheter fitted. The IoT sensors revealed the man was getting up to use the bathroom, even flushing the toilet, clearly revealing an unexpected level of confusion.
Combining AI with the IoT sensors, the care providers were alerted to the potential problem with a recommendation to call the GP, who immediately diagnosed a Urinary Tract Infection (UTI) caused by the catheter. Antibiotics were prescribed, the catheter changed, and the individual’s confusion reduced. Without that early intervention it is very likely the UTI would have had a detrimental impact on the individual’s mental and physical health, leading to hospital admission and potentially even resulting in the need for palliative care.
Effective Response
Care providers have to make incredibly tough decisions during the winter months, decisions that could affect an individual’s ability to remain at home in both the short and long term. Add in the challenges created by snow storms that affect a carer’s ability to travel or flu epidemics affecting both carers and clients, and the situation can rapidly become dire. How does a care agency prioritise visits? Or ensure resources are most effectively deployed?
By using IoT sensors to better understand each individual’s pattern of behaviour, it is possible to leverage intelligent algorithms to tailor the response to truly match demand. When a crisis arises, a care agency can continue to provide a high level quality of care with confidence in the quality and depth of client information provided by the sensors. With visibility of which client requires urgent care and which one is happy and comfortable at home, the agency can allocate scarce resources where required and only intervene when needed. Additionally, with every carer in the agency able to see this real-time information, they can work together to determine who is in the safest position to reach the client in need – the carer closest or the carer who can avoid the tricky roads. And with every carer having access to a client’s recent behaviour and activity, the same level of consistent care can be delivered, irrespective of which carer is able to reach the individual.
Conclusion
With continued rising demand and extraordinary pressure on resources, especially during the winter months, the care model has to change. The ability to leverage IoT to embrace intelligence led caring can be transformational – not only enabling the early intervention required to minimise problems, including A&E visits, but also ensure carers reach priority clients as quickly and efficiently as possible. Critically, individuals are no longer alone for 23 hours a day – their well-being is being continually, yet discretely, monitored to provide families with reassurance and enable a far more effective and tailored care response, whatever the challenges created this winter.
