Digital technologies: Enhancers or disruptors of good social care?
The current digital shift in social care services is bringing about rapid and far-reaching change. To consider this from a range of perspectives, this panel was organised by the Green Templeton Care Initiative in collaboration with Digitally Enabled Care in Diverse Environments (DECIDE), an NIHR-funded centre for rapid evaluation of technology-enabled remote monitoring in health and care settings based in the Nuffield Department of Primary Care Health Sciences. The conversation brought together Professor Caroline Potter (Senior Researcher in Community Health and Social Care, Nuffield Department of Primary Care Health Sciences), DeeDee Wallace (Health and Care Innovation Team Leader, Innovate Oxfordshire, Oxfordshire County Council) and Tommy Wise (Policy Lead for Care Technology, Department of Health and Social Care).
Tommy Wise presentation slides
DeeDee Wallace presentation slides
Caroline Potter presentation slides
Tommy Wise began by giving a view from national civil service policy making – which has the challenge of balancing many interests, including the changing aims and priorities of the elected government, against a background of wider demographic pressures. He mainly focused on digital care records as a case study of digital technologies, outlining the process by which digital care records were introduced and promoted nationally through their inclusion in Care Quality Commission criteria for registered care providers. The result is that 75% of registered care providers (and around 85% of people in receipt of care) now have a digital social care record (DSCR), an increase from 41% of providers in 2021. He sketched the advantages of DSCR: they can store a lot more information, including personal preferences, and records in different formats (such as pictures); and they enable care workers to spend less time writing notes (an estimated twenty minutes to an hour per worker per shift), allowing more time for care and social interaction. He also acknowledged more negative effects. Users can become over-focused on the digital and the appearance that their care worker is typing on their phone may alienate some care users; the overuse of emojis and icons can also be, or be perceived as, reductive – for example, by auditors. There are also significant concerns about data privacy and cybersecurity.
Mr Wise emphasised that the implementation of DSCRs was carried out not by the civil service but by people involved in social care: care workers, providers, care users, unpaid carers, and families. He pointed out that there is a lot of variation in care workers’ readiness to learn to use new technologies and systems, and that culture change as well as training is essential. He gave the example of ‘Jane’, a highly experienced care worker with autism and dyslexia, who described the impact of using a voice-to-text feature to write DSCRs: she “feel[s] like an actual human now.” While she “used to get so worried and nervous and embarrassed about showing any of my paperwork because it was so bad”, the digital shift has given her more time to spend with residents. On the other hand, Jane’s testimony suggested that the change had taken, and continued to take, some time and effort to master. “The longer I spend on the system”, she explained, “the better I get at it. So, I think it will keep getting better.” Mr Wise closed by outlining further steps which have been announced by the government: the introduction of new national standards and trusted guidance on care technology, and the development of more effective and joined-up data sharing.
DeeDee Wallace’s presentation focused on a sensor-based falls prevention project in Buckinghamshire and Oxfordshire, funded by NHS England’s Digitizing Social Care Fund. She contextualised the project by explaining that falls are a leading cause of non-elective hospital admissions and cost NHS £2.3 billion annually, and that care home residents are three times more likely to fall, and ten times more likely to sustain significant injuries, than older people living independently at home – although this is likely a reflection of their more complex care needs. Falls prevention initiatives are thus vital for many reasons including protecting individuals’ independence, but need to avoid ‘helicopter caring’, which may erode their privacy and dignity.
Ms Wallace presented sensor-based falls technology (SBFT) as part of a move from reactive to preventative approaches to care. Across five care homes, passive sensors have been supplied and installed by Vayyar to monitor 350 residents in their bedrooms and bathrooms. These alert staff when people fall or may be in immediate danger of falling, but also gather data which can be used for fall prevention in the future. The biggest risk indicator for falls, Ms Wallace underlined, is a previous fall, but current data is incomplete or misleading: SBFT collects not only reliable, consistent information about falls and resulting injuries, but also other risk indicators such as increased toilet use (which might indicate a urinary tract infection). While Ms Wallace does not advocate for SBFT being used to reduce in-person interactions such as night checks, she acknowledged that this might be an occasional effect, as users test the limits of the technology.
Ms Wallace’s team is supporting the local care homes with installation, training, and cultural and process change, and will carry out qualitative and quantitative evaluation, producing an impact analysis and, if the technology is seen to deliver benefits, a scale-up strategy. She expects the benefits to include: a drop in non-elected admissions to hospital, improved night monitoring, faster incident response, and improvements to independence, workforce capacity and most importantly quality of care.
The third speaker, Dr Caroline Potter, shared some findings from one of the streams of a DECIDE project. This assessed the use of a package of multiple sensors in the homes of people identified by social care services as possibly benefiting from monitoring to allow them to stay in their own homes for longer and receive better support from care workers and family networks. Rather than only recording general motion or discrete events to identify risk indicators, these sensors scan all the time, collecting day-to-day data about the use of doors, kitchen appliances, beds, bathroom equipment and so on. The system uses machine learning to identify patterns of behaviour which are ‘normal’ for an individual household, as well as knowledge of what kind and degree of changed behaviour should trigger an alert.
There is consensus in the research literature of the potential benefits of this: if care providers understand people’s ‘normal patterns’ and can spot differences early, they might be able to intervene and stop an escalation of care needs or health crisis. There have therefore been plenty of pilot projects, but there is little evaluation evidence or information about the process of moving beyond the pilot level to making such a package a standard, ‘business-as-usual’ offer in a local authority’s adult social care service.
To fill in this gap, DECIDE worked with three local authorities at different implementation stages to track impacts on different users and stakeholders – some of which were unexpected – and learn more about effective practices in this long and complex process. Caroline gave two case studies of users: one on a short-term basis, to support a return to home living after an injury, and one for long-term care alongside ongoing visits from paid carers. While there was evidence that the sensors could provide a real sense of reassurance for care users and their family members, as well as evidence to inform care provision, there were also conflicts as multiple stakeholders engaged with data that could be interpreted in different ways. They could also require extra, hidden work from family members and care workers to manage problems and anomalies.
Questions from the audience raised the matter of whether people needed protection in the face of the silent but quite intrusive interventions. A massive volume of information was being collected. Questions were also raised about the use of digital technologies in a context of dementia or reduced capacity and the ethical implications. Another matter discussed was the degree of ‘disruption’ that is tolerable or should be allowed and the scale of an acceptable trade-off between enhancement and disruption.
The opinion of the panel was that digital technologies will both enhance and disrupt good social care. Tommy Wise argued that while technology with a clear, specific functionality (he gave the example of an AI pain check app which can be used with nonverbal people) can be minimally disruptive and enhancing for all parties, larger and more general changes will likely be more unsettling, because they require care pathways and models to be rebuilt around them. While this may be worthwhile, it requires work not just to implement the change well but to test and quantify the benefits and make a case that they justify the disruption. Similarly, DeeDee Wallace stressed the potential of data analytics to enhance risk management, but also acknowledged that significant support is needed to manage disruption to the workforce. This generally positive view was, though, challenged by some audience members, who highlighted risks including over-surveillance and data exploitation; the loss of human contact in a social care system which may use technology as an excuse to cut staff costs; and the monopolistic power such projects may hand to private tech companies. As Professor Mary Daly commented, questions about the impact of this digital shift are clearly urgent, but they are also highly complex, depending on an often-elusive shared definition of ‘good’ social care.
