Spotlight on Falls – Harnessing technology and AI for a safer future at Peverel court care

 


Falls are one of the most feared health emergencies for older people and their families. In our three-part series, we are shining a spotlight on falls, the changes we aspire to make and the impact these will have in reducing falls. We finish this series by looking at the possibilities for future falls detection and prevention.

We know that falls are something our residents and their families dread, as we explored in our first blog that looked at the impact and implications when a person has a fall and our second blog where we heard from our residents, relatives and staff

How we support our residents to reduce their risk of falls and ensure that any falls that do occur are detected very quickly is extremely important to us. We are supported in this mission by the numerous healthcare professionals who visit us to support our residents, including Gemma from The Caring Physio, whose work we featured in our blog ‘Personalised, at-home physiotherapy for our residents’.

Specifically thinking about the role of technology in falls prevention, Gemma told us:

I believe that there is so much scope for digital technology improving and reducing falls, both in a preventative element and an analytical element. The biggest way to reduce falls is by getting close to really understanding why people fall, how they fall and how we can reduce it, so if technology can do this I think it would be really good.

 

Technology we are considering at Peverel Court Care

We are in discussions with various supplies, including Sensio and Ally Cares, two companies who specialise in cutting-edge falls detection and prevention technology.

To share more about their work, we spoke to Sven Seljom, UK Country Manager for Sensio who produce a product called RoomMate, and Thomas Tredinnick, Co-founder and CEO of Ally Cares who produce an acoustic monitoring system, to share more about these breakthrough technologies.

 

Sensio’s Roommate

RoomMate is a prevention, detection and digital monitoring device. We asked Sven what the benefits are to implementing this type of technology for our residents: 

The obvious benefit is that we are able to detect movements and incidents in the room. We can detect falls, even low impact falls, very reliably thanks to our 3D vision sensor without needing the resident to remember to wear anything. 

When it comes to falls prevention, there are so many things that actually lead up to a fall that we can help with. For example, the sensor can pick up if a resident sits up in bed during the night. Staff can be warned about that on their handheld devices, and then act on it before the resident potentially ends up falling because they are tired or the room doesn’t have enough light. 

The system also enables staff to look into the resident without actually going into the room. They can do this through an anonymised view of the room, which means that they can see a figure in the room that represents the resident and they can check if they’re ok. If there has been an alert, they can also assess whether it’s a false alert or not. The purpose of this is to try and keep staff out of the room unless they are needed. This improves the privacy of the residents, and also increases their sleep quality. If residents sleep better, they are more rested and have fewer falls during the day. Night staff are also more relaxed; they can concentrate on the residents who need attention and leave residents who are happily asleep to enjoy that rest.

 

Ally Cares Acoustic Monitoring System

Ally Cares produce a resident monitoring system that uses sound and inferred motion to understand when a resident is alone in their room and may need assistance. It alerts staff to enable them to provide assistance if it’s needed. If it isn’t, they can hear why the alert was generated and leave the resident to enjoy privacy to continue with their activities, safe in the knowledge that that staff will be alerted if assistance is needed.

Thomas explains more about the benefits of what he and his co-founder, Zach, have set out to achieve with their technology after having personal experiences of the challenges their ageing relatives faced:

The main benefit to our technology is to being able to absolutely know when a resident needs assistance, and more broadly to gain insights into their health and wellbeing by being able to see trends and changes that you originally would not have been able to observe.

By connecting with care record systems, we can support residents to have better sleep which should reduce falls’ risk. Better sleep means a person may be able to do more for themselves safely, enabling staff teams to provide targeted, insightful care for residents who need it the most. 

One of the managers we worked with early on when we were developing the system put it really well. She said she wasn’t really anticipating the level of insight you get from the products when you’re using sounds. She also wasn’t anticipating seeing how much more connected her night team felt to her day team. How much more knowledgeable they were and the conversations that flowed because of this. That was a benefit that we hadn’t anticipated because we were so focused on how to deliver the safest possible care for residents.

 

Integrating falls detection and prevention technology into our digital care records

Across Peverel Court Care homes we moved to digital care records in 2020, with Nourish as our chosen supplier. We spoke to Steve Lawrence, Head of Product at Nourish, to find out his view on how Nourish see sensor based technology linking to what they offer:

The fact that you don’t have to wear a device or press any button to interact with acoustic systems is one of the key positives around this technology. With wearables, sometimes the person isn’t wearing the device, or the person isn’t able to raise a warning using it. Or the person is wearing it but they don’t want to make a fuss; they sit there suffering rather than actually getting the response that they need.

To know that the system is monitoring all the time, mostly generating non-urgent alerts which give passive information, means you have rich data that you wouldn’t have otherwise. For example, with night-time behavioural monitoring with acoustics. This works really well because as humans we are generally creatures of habit, so if we’re going to get up to use the bathroom we’ll do that consistently most nights. When there is something wrong, that’s when that pattern changes, and we can start to monitor that activity and use algorithms to determine changes to behaviour that can link to changes to someone’s condition. This could be due to a number of different factors, including an underlying condition that perhaps the person hasn’t been able to verbalise themselves. 

Through machine learning, we’re able to determine that these things are beginning to occur and to enable staff to have that early insight and take action sooner. We’ve seen that in practice, to a level where you can analyse that data and use it in predictive and preventative ways.

 

The current and future for falls detection and prevention – Ally Care’s view

We asked Thomas about how Ally Care will look to develop their acoustic monitoring technology further, particularly by supporting staff knowledge and decision making:

At the moment we have an insight tool using a machine learning algorithm to say whether or not a resident needs assistance. We use a different machine learning algorithm to chart how much rest a resident has had, how much care they might need, and picking up on things like whether they’ve been coughing more than usual.

We deliver that in a little handover tool and an insights tool that lets the night team very quickly and succinctly handover information to the day team about residents that they really need to handover. This means you go from the night team not really feeling like they can understand what’s happened for that resident (because multiple people have been going in and providing care as part of the regular safety checks), to us giving you a simple prompt that this resident has been awake more than usual, received more care than usual or been coughing more than usual. We measure this both on individual nights and also a trend over multiple nights. 

This means that the day team can be more cognizant of the care that they need to provide during their shift. If a resident has, over the last three nights, been much more restless you can start to join the dots. If this same resident is a high risk for a UTI, is this perhaps the precursor to them developing a UTI and we can do a dipstick test. 

For another resident you might see that over the last month on every Wednesday they are much more restless during the night. What is that to do with? Is it the fact that they’ve started a new activity on that day? Is there a regular visitor that day? Do they take a new weekly medication on that day?

These insights are then like an assessment tool that prompts staff. Is what they are seeing a generic trend over the month or something that’s just happened over the last few nights? This prompts the day team and the managers to review what they’re doing and be more dynamic in their support.

We want to develop this to make it more insightful for staff, so that they are prompted with what they need to look at or do and how they need to do it. In an ideal world you’d want to see the top three or four reasons as to what might be happening for the resident, and I think that’s probably the area we want to develop to create more holistic data sharing.

 

The future for falls detection and prevention – Sensio’s view

We asked Sven about how Sensio will look to develop their RoomMate technology further, particularly by utilising data that’s been collected as a result of their technology. This could be used to support clinicians to reduce an individual’s risk of falls by, for example, linking Sensio’s data to multifactorial patterns like a person’s medical needs, nutritional and hydration input:

We could analyse many aspects from our data and produce useful outputs, for example measuring gait speed and how people move around their room. Are they confused? Are they going straight to the bathroom or are they going out in the hallway and then trying to find the bathroom? With UTI’s, how many times does the person visit the toilet? How is a person moving in bed? Compare that data with their medication regime – What types of medication are they having and how does that affect how they sleep? How much time do they spend in bed? How much time do you spend in a chair?

There are so many things we would like to do to improve our systems. It’s just a question of resources to do this work, always keeping the privacy of people using RoomMate in mind.

 

The future for falls detection and prevention – Nourish’s view

We asked Steve how Nourish foresees using data in the future:

There are good practice examples out there that can be utilised to be able to support staff to do the right things at the right time. It’s not just about research-based ways of doing things, there are common practice examples within our Nourish community where we are learning from providers like Peverel Court Care. We see it as our role to help to share information to support care teams to be able to do things in a more prompted way, to ensure that important aspects aren’t missed and that good care is provided by having the right sort of processes in place. 

There’s a big element around the protocols and workflows. I think there’s a lot around the predictive analysis too, the cause and effect of certain events that take place, and using that information intelligently. You know, we have a lot of insights in our system and we have the ability to start looking at things that happen perhaps before an event to know if there was a fall.

 

What’s next? 

At Peverel Court Care we will continue to work with our partners in falls prevention and monitor the latest news and developments, like the use of artificial intelligence (AI) to prevent falls. We want to be – and remain – at the cutting edge of reducing falls for our residents. 

To conclude with Gemma’s thoughts:

I’m really pleased that you’re looking into this because I think it’s a sadly under-researched area. With the digital evolution that’s going on at the moment, if we can take some of that genius and apply it to something as important as falls – which have such a huge effect on this population’s life – that’s brilliant. 

No pressure, but I think you’ll make big waves if you can break through and make some sort of improvement. Older people deserve this, they deserve to have some tech to help them.

 

Further reading

Peverel Court Care’s Associate Director, Preet Shergill’s Topol Fellowship (that focuses on falls) continues. Preet’s Topol Fellowship includes close working with the NHS, and he wrote about this in his blog for the Department for Health and Social Care

 

About Peverel Court Care

Peverel Court Care is a group of one residential and two nursing homes, located in Buckinghamshire and Oxfordshire. Bartlett’s Residential Care Home and Stone House Nursing Home in Aylesbury, and Merryfield House Nursing Home in Witney. We are a long-standing family business. Providing exceptional, personalised care, delivered by talented and compassionate people, in exclusive and idyllic settings.

With happiness at the heart of our homes, we recognise and respect the contribution made by our residents to society during their lifetimes. Valued by residents and their families; our reputation, investment in each property, and approach to appointing and developing our staff makes each home unique and the benchmark in premium care.

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