Published on: October 10, 2022

Using technology to monitor care home residents’ health remotely


October 10th 2022: The Care Home Environment   Click to view

By Faramarz Farhoodi, CEO of AI Nexus Healthcare


Remote monitoring within the social care setting has cemented its worth following the unprecedented care climate thrust upon us by the pandemic. Technology was a pivotal solution in limiting face-to-face contact and many care providers across the UK employed traditional hardware devices that could monitor the vital signs of residents —which prompted some impressive developments within remote monitoring technology. As many fundamental care techniques have returned, there has been a residual appreciation for telemedicine and its ability to alleviate basic tasks from care workers.


What’s more, telemedicine is starting to increasingly interact with Artificial Intelligence (AI), which provides scope for technology providers to emulate clinical expertise through complex and functional solutions. Not only can this serve to limit the number of chronic diseases in care homes, but also support the social care sector in the UK, which is already operating beyond capacity.


But the question remains, how close are we to creating a technology platform that can provide functional and accurate advice in line with the thought process of a clinician — or are we already there?


Why is remote monitoring so important?


Remote monitoring is a great way of fostering strong relationships between carers and residents, especially within the domiciliary care sector. This being said, it also has an abundance of applications within traditional care home environments and can provide another layer of comfort for residents and their families to know that health checks are being carried out more regularly and that an overall picture of their wellbeing is being monitored and updated consistently.


As touched upon this was especially useful during the pandemic, where technology allowed care providers to keep a watchful eye over their residents from a safe distance. However, despite the reactive developments in health technology, there is something missing in the process. I’m talking about the ability to translate medical data into tangible, accurate and in some cases, life-saving advice. This is where AI comes in. Many leading minds in the UK and overseas have spent years developing complex neural networks that offer processed and accurate pattern analysis within datasets, which are packaged neatly under the somewhat daunting umbrella of AI. But this fails to address one key point: the ability to combine cognition with recognition, which is essentially AI that can reason and think beyond basic patterns in data, the same way any clinician would. This is a term we refer to as hybrid AI and is the bridge between providing supplementary tech that helps carers do their job and tech that can actually save lives through functional advice.


So how can this technology be applied within the care setting?


The capabilities of AI reach beyond simply tracking biometric and health data, which many health apps widely used by consumers can do. If an app is tracking your step count, deep sleep time and heart rate, then despite this data being useful and a great way to gain an insight into your own body — does it really consider the bigger picture and what this data might actually mean? 


This technology focuses on collecting and displaying data for means often unbeknown to the consumer and the technology provider. Many people in the UK now have health accessories such as watches or other monitoring devices, yet they all fail to provide actionable advice on the data they collect. These devices are also trained to recognise patterns in vast amounts of data as a substitute for medical expertise — something commonly referred to as machine learning. However, to put this into the context of a care home resident, if an individual is experiencing significant disturbances in their sleep, most monitoring systems will be able to identify this through peaks and troughs in their heart rate. However, the process tends to stop here. Hybrid AI has the ability to translate this data into actionable advice, with the key message here being that pattern recognition is not cognition. 


Cognition by its very definition is the “action or process of acquiring knowledge and understanding through thought”. At AI Nexus Healthcare, we have decided to focus on “understanding”. We are using advanced AI to convert masses of data into genuine advice — a tool that is actually of use to social care professionals.


Given the complexity of such technology, it is vital that its application is simple. If a product or software is user-friendly and easy to navigate, then its uptake will be much more significant within the care setting. Years ago, the thought of obtaining vital signs and behavioural data straight from a smartphone camera or from more than 100 other external collection points would have been deemed impossible. However, thanks to years of expert development and the endorsement of some of the world’s leading medical professionals, these capabilities can be centralised into one simple platform. Care workers are able to gain a full insight into a resident’s health in a matter of minutes, which would then make informed recommendations on whether the individual is dehydrated, low in glucose, or in need of a medical professional.


Spotting the signs early


Within the elderly population, detecting issues at much earlier stages of the disease cycle can significantly increase the scope for recovery and treatment. AI provides the opportunity to allow care providers to become more aware of their resident’s overall health and take action as soon as anomalies in data occur. Given that 80% of chronic diseases are preventable, the ability to do this is invaluable and could massively impact avoidable mortality. Any indications of disease can be identified before they are at a later stage of the disease cycle and thus reduce the impact on carers and level of support needed for that individual.


The data collected can not only inform care providers when to outsource their treatment to more advanced medical professionals but the information gathered can also be used to assist a doctor to make an informed decision — similar to paramedics debriefing when a patient enters A&E.  This hybrid AI approach pairs deep learning with reasoning mechanisms, which essentially allows you to build applications that benefit individuals and carers who may not be highly qualified medically, to have a better understanding of actions they can take — before it’s too late.


Taking remote monitoring to the next level


Remote monitoring using hybrid AI has endless potential within social care. One key ability is to track the likelihood of falls — something that is a real issue with elderly people. It allows for the identification of people’s fall risk through tracking data such as heart block, sleep quality, walking gait and other biometrics. This data is then processed, rationalised and presented as functional advice for carers to act upon.


Of course, its capabilities go beyond just fall prevention, with the capacity to identify other medical conditions through diagnostic information, such as arrhythmia, strokes, Bell’s Palsy and diabetes. All of this can be detected by simply scanning a resident’s face or finger. This simplicity of use and localisation of complex technology is something we like to describe as ‘smart care’.


Why is now the time for a shift to ‘smart care’


Social care providers across the globe are suffering at the hands of an ageing population. Advancements in medicine, although welcome, are allowing individuals to live longer lives, which in turn, means that more people are calling upon the services of the care sector. Exacerbated by the hardships of the pandemic, the care sector is operating well beyond its capacity and many clinicians are also vastly overworked and unable to deal with the excess demand. A contributing factor to this is the number of unnecessary appointments in hospitals and general practices. As a default, humans are wired to action any sense of discomfort or abnormality with a trip to the doctor. However, what AI can offer is a middle man that can evaluate whether this trip is necessary by remotely monitoring an individual’s biometrics. This in itself could massively ease the strain on medical professionals, however, its potential application does not stop there. 


Many care homes across the UK are short-staffed and carry out the bare minimum amount of care to ensure every resident receives a benchmark level of attention. AI can help carry out typical daily tasks such as the monitoring of vital signs and do so multiple times during the day — without the need for a present carer. In turn, not only will staff be able to focus their efforts on formulating inclusive and person-centric care cultures, they are also provided with reliable and actionable advice for each resident, who may be in need of more advanced treatment or, indeed, no treatment at all. Similarly, for domiciliary carers, their job is made both easier and more efficient by having that remote monitoring capability. They can keep a remote eye on their care recipients, helping to provide more holistic, all round care without physically having to be there.


An additional benefit is the opportunity to share key information with care recipients’ families, helping to provide peace of mind that their loved ones are being monitored, even without a carer being physically present – which, from a commercial standpoint, also helps to reinforce the value of employing professional carers.


One of the most difficult things for carers is logging and recognising that each individual has their own set of needs and requirements, however smart care through continual learning, can understand and adapt to every individual’s unique wellness challenges. This can help create a regulated and thorough map of each resident’s progress and supplement traditional logging techniques.


Accessibility and affordability


Despite its complexity, this form of remote monitoring is extremely accessible and affordable to all and unlike many care techniques, is appropriate for everyone. This unlocks vast potential for the industry-wide uptake of such technology and is the main reason that hybrid AI is the key to achieving a ‘smart care sector’. Using this technology can also help you gain a competitive advantage by creating a care culture that consistently addresses the question “are my residents ok?” Not only can this boost your reputation and occupancy rates, but it can also improve your overall quality of care and allow staff to focus on generating meaningful connections with residents — as opposed to working round the clock to complete the basic requirements.


How AI is addressing the challenges of remote monitoring


One of the key challenges with remote monitoring is its implementation and the training of staff. Most traditional remote monitoring systems require staff to manage repetitive tasks, which is not only a misallocation of resources but can also take a lot of time to ensure they have received adequate training on all components. Many of these systems also lack automation and therefore their ability to streamline the monitoring process is somewhat hindered by the continued demand for human intervention. Hybrid AI solutions like our signature platform, mia care, can eliminate the need for excessive training and can function autonomously each time it is used. Its seamless integration within a care environment means that efficiency can be achieved almost instantly and staff can focus on other aspects of their job role. 


Another issue is apprehension from residents or a lack of technological aptitude. Data collection methods are key to addressing this issue, so by simply scanning an individual’s face or finger, there is no need for the input of data and they can easily be assisted by a carer. Many remote monitoring systems have external hardware, such as an oximeter, that actually collects the data, which is then fed back into the processing system. However, by localising this into one simple camera lens, technological mishaps are significantly limited and a truly user-friendly system is created. 


Of course, any changes to a care agenda will take time to integrate, however, the design of mia care was underpinned by an innate understanding of the overstretched care sector. With this in mind, seamless integration is a key feature of hybrid AI systems, and staff are left to simply observe the functional advice provided and act accordingly. Once this is in place, staff can spend less time on tedious tasks and more time on actually treating residents, while also enabling early action and the confidence to make decisions.


At AI Nexus Healthcare, we believe that telehealth requires AI to help embody the art and science of medicine and to find clarity within vast bodies of biometric data. Simplicity needs to be achieved through complexity and with a simple, functional and useful platform that monitors residents, care providers can not only limit the number of chronic diseases within residents but also enhance their daily health and wellbeing — the gold standard for any care operation. 


We champion the concept of prevention over cure and by creating a ‘check engine light’ for the human body we are demonstrating the power of AI to supplement traditional care. The healthcare system remains under immense pressure and with elderly populations increasing exponentially, now is the time to embrace a shift towards ‘smart care’ and take remote monitoring to the next level. 


Faramarz Farhoodi, founder of AI Nexus Healthcare, has more than three decades of experience in the field of AI, having led more than 1,000 person-years of AI application development across the defence, healthcare, manufacturing and finance industries – with his experience as diverse as helping to build NATO command and control systems to overseeing’s largest commercial account.


With 80% of chronic disease preventable and a global shortage of healthcare professionals, Faramarz and AI Nexus Healthcare are using a specialised AI skillset to transform healthcare systems, focusing on intervention and prevention.