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Lilli: Using remote monitoring technology to prevent falls at home

By Nick Weston, CCO at Lilli




Falls are one of the leading causes of emergency admissions to hospital for those aged 65 and over, with statistics showing that 30 per cent of 65s and over will fall at least once a year, while for those aged 80 and over it rises to 50 per cent.

Of these falls, a large proportion occur in the home, often as a result of a declining state of health, such as dehydration or reduced movement affecting balance.

The impact and subsequent treatment required from such falls at home places increased pressure on an already underfunded NHS, but the human cost of these falls cannot be underestimated either.

A review of long-term disability found that around 20 per cent of hip fracture patients entered long-term care in the first year after fracture, highlighting that incidents such as falls can be the start of a loss of independence for many.

However, this need not be the case.

Thanks to new innovative technology, there is a way to stop falls from having such a devastating impact, by preventing them from happening in the first place.

With the number of people aged over 85 in England expected to double to 2.6 million in the next 25 years, urgent change is required to shift from a reactive to a proactive mindset when it comes to care in the home.

It will no longer be enough to simply react to incidents as they happen.

Care professionals must be better served with data that only technology can provide, in order to properly understand how individuals are coping at home, so they can in turn create better care plans that address any declines in health as soon as symptoms are flagged.

This is particularly important as falls can be an indicator of a person’s wellbeing worsening, so catching this pattern of behaviour early on can have a real impact on the way a person lives the rest of their life and reduce the risk of hospital admission due to a fall.

ML-based technology provides indicators of falls early

But how can this be achieved?

It’s no secret that the care sector is in crisis, with vacancy rates back at their pre-pandemic levels, and a particular increase in domiciliary care jobs (around 7.4 per cent).

With the ongoing cost of living squeeze rumbling away in the background, this is likely to have a further impact on staffing levels as those in the care sector eye up more financially appealing employment in the retail and hospitality sectors.

And while the Health and Social Care Levy, which is currently under review with our new government now in place, will alleviate some of these issues and help plug the growing financial gap, this increase in funding will only go so far.

So, at a time of stretched resources, how can care providers adopt a more proactive approach to care?

Remote monitoring technology could be one part of the solution. By monitoring key indicators of those requiring care at home, it’s possible to flag potential symptoms of deterioration that might lead to a fall.

Lilli’s remote caring solution combines machine learning (ML), behavioural data analytics and sensor technology in a cloud-based solution.

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 less movement, increased toilet use 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, 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 that enables prolonged independence and a more fulfilling life.

In terms of fall prevention, this kind of insight could be, quite literally, life changing.

If care providers have the data to suggest that a service user is drinking less, for example, this could enable them to step in before dehydration poses a serious issue.

Likewise, if sensor data suggests that an individual’s movement levels have decreased, this can empower care professionals to ask the right questions at the right time to understand why. It could perhaps be that moving around the home has become difficult.

This information would allow care providers to react before a potential fall has even occurred and put safeguards in place to prevent incidents, such as installing extra handrails , introducing additional walking aids, or even ensuring more frequent home help visits.

Similarly, should a service-user have a fall, the data captured in the lead up could indicate what contributed to it, for instance, it may highlight that the individual hadn’t eaten or drank anything for a given period.

This data could also indicate if a person’s condition is worsening, with remote monitoring technology allowing care providers to intervene earlier thanks to this intelligence and provide the care that service users need, faster.

These insights can then be used to prevent it happening again and reduce the number of service-users being admitted to hospital due to falls in the home.

Using data to improve home care

The potential impact is huge – both in aiding an overstretched health and social care sector, but also on human level.

For example, a recent pilot project with Dorset Council saw Lilli’s discreet home-based sensors being implemented to monitor potential signs of deterioration in patients recently discharged from hospital.

The resulting data enabled teams to promptly intervene when changes in patterns of behaviour were flagged, such as getting up more frequently in the night or using the kettle less.

Results that last

With falls among the elderly and vulnerable a major cause for hospitalisation, the most common cause of injury related deaths in people over the age of 75, finding ways to reduce such incidents is essential, equally to both protect individuals and reduce the pressure on health and social care providers.

Shifting to a proactive care model by adopting remote monitoring technologies will allow health and social care leaders to make a material difference to staff and service-users alike by more efficiently managing resources while at the same time improving care outcomes.

It will also provide them the opportunity not only to reduce the risk of falls in the home, but also to allow care providers to uncover signs of deterioration before it is too late.

For service-users, this will mean they are able to live safely and independently at home for longer, and grant their loved ones and carers peace of mind.

Amid concerns around the aging population, adopting these long-term, sustainable solutions will ensure care providers are able to cope not only with the demands and pressures of today, but are also in the best possible position to handle what is to come in the future.

Learn more at intelligentlilli.com

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