Home sensor technology in social care reform: Moving from potential to practice at scale in tech-enabled care

Why this matters now

Adult social care is under intense pressure due to the rising complexity
of needs, workforce shortages, financial constraints and public
expectations for better-integrated preventative care. Government efforts to
reform social care are placing renewed focus on the potential of
tech-enabled care (e.g. the Adult Social Care Technology Fund [ASCTF] and
the Casey Commission on Adult Social Care).

There is growing interest in the use of home sensor technologies for
proactive care (prevention or early intervention in health or care needs).
These technologies have the potential to support independent living and
improved quality of life. They could also help prevent avoidable hospital
admissions and unnecessary demand on health services through early
detection of deterioration, as well as potentially supporting social care
productivity and efficiency. However, evidence about how home
sensor-enabled social care pathways work on the ground, their impacts on
people and services and their success criteria, is scarce. Without
understanding the determinants of successful design, implementation,
sustainability and scale, it is difficult to establish effective policies
and programmes.

There is an urgent need to improve the evidence base relating to how
technology such as home sensors and their associated data infrastructure
can help improve adult social care, enhance integrated health and social
care, and support independent living, prevention and community-based
care.

The National Institute for Health and Care Research (NIHR)-commissioned
rapid evaluation of home sensor–enabled proactive care pathways, delivered
by the DECIDE centre (a partnership between the University of Oxford and
RAND Europe), provides uniquely in-depth and robust evidence and analysis
of the realities of home sensor-enabled social care pathways, looking at
how tech can help, how pathways operate, and their impacts and influences
on effective implementation and adoption at scale.

What the evidence shows

Drawing on an evidence review, deep dives in three local authorities,
over 70 interviews, workshops, and an economic feasibility analysis, we
found:

• Home sensor pathways have real but uneven benefits, with
  privacy concerns discouraging some people. Home sensors can help
  identify early signs of health deterioration (e.g. night-time waking,
  reduced movement, hydration/ nutritional changes). They can also enable
  more objective and holistic care assessments, support care planning and
  help reduce unnecessary domiciliary visits, help prevent prolonged ‘long
  lies’ after falls and provide reassurance to families. Sensor-enabled
  remote monitoring pathways in social care can also aid communication
  between social workers and families when agreeing on care plans. However,
  some participants in the evaluation voiced concerns about privacy and
  shared examples of the sensors exacerbating anxiety and paranoia in people
  with diagnosed mental health conditions. Sensors can also have limited
  effectiveness for people without supportive networks around them to respond
  to alerts. Thus, home sensor-enabled remote monitoring pathways are not
  suitable for everyone.




• Sustained adoption at scale is
  hindered by challenges related to funding, workforce capabilities and
  capacity, demands on informal carers, silos between health and social care,
  and digital connectivity and equipment maintenance demands. Home
  sensor-enabled social care pathways reshape, rather than replace, the work
  done by social care professionals. To achieve intended benefits, frontline
  social care practitioners need to have the skills and confidence to
  interpret sensor data for decision making. Informal carers also play a key
  role in acting on sensor data, requiring their engagement and time.
  Challenges to the timeliness of sensor pathway initiation for reablement
  purposes after discharge from hospital persist, largely related to
  insufficient staff working at the intersection of NHS healthcare and local
  authority social care. Home sensors also require digital connectivity and
  ongoing maintenance, with implications for service resourcing, digital
  infrastructure and planning. Senior-level buy-in, clear distribution of
  roles and responsibilities for monitoring and acting on alerts, dedicated
  tech-enabled care (TEC) leads in local authorities and
  installation/maintenance teams, social care practitioners embedded into NHS
  discharge services, and close working relationships between tech suppliers
  and local authorities are also key to success.




• There is currently insufficient system-level data to evidence
  cost effectiveness, which is needed for long-term investment. Data
  fragmentation (e.g. between health and social care or between local
  authorities), inconsistent data governance requirements (e.g. data-sharing
  agreements) and data infrastructure limitations all block meaningful
  economic evaluation of cost effectiveness. The quantitative data currently
  available are limited, which constrains the ability to assess impacts on
  the prevention of deterioration and hospital admissions, care packages, and
  delays in admissions to residential care. Local authorities often lack
  capacity and capabilities for effective evaluations and cannot demonstrate
  full value without integrated health and social care datasets. Improving
  data access, sharing and use infrastructure is fundamental in enabling
  better-informed decision making about funding these pathways sustainably
  and at scale.

What this means for national policy and action

This evidence has clear implications for the Department of Health and
Social Care and for wider government reforms. While our primary focus was
on the use of home sensors in social care, reflections from study
participants suggest that many of our recommended actions are applicable to
broader decision making regarding the use of assistive technology in social
care.