eHealth
EFRAIL: USING DATA TO
ASSIST IN-HOME CARE
Our researchers are seeking
to apply the latest Big Data techniques
to a specific health problem
for the elderly – frailty
T
he UK has a problem. It’s getting
older as Baby Boomers age. This
demographic bubble will put
a significant strain on the NHS and
other support services. Healthcare
providers are preparing for the crunch.
Can data help solve the problem?
The School of Computing’s
Adrian Smales thinks it can and
is demonstrating this through
his eFrail project, funded by the
Digital Health Institute.
Care in the home
Frailty is a common multidimensional
health and social care challenge
associated with an increased risk
DELAYED
HOSPITAL
DISCHARGES
£900M
COST TO
NHS PER
YEAR
of physical, cognitive and functional
decline. This often results in health
problems among the ageing population.
Mitigating the problems associated
with frailty is an important objective.
Delayed hospital discharges are
a major health and social care issue
costing the NHS up to £900m a year.
Part of the solution is to keep people
out of hospital altogether and that
means preventative care. A recent
Audit Scotland report on ‘Social
work in Scotland’ highlighted that
prevention must be an integral part
of Councils’ long-term strategies.
That’s not controversial because
most people prefer to stay in their
own home in retirement. The problem
is how to ensure that people stay
healthy at home and avoid typical
accidents such as falling, all while
reducing overall healthcare costs.
Tracking health data
As part of the eFrail project, Adrian
is working with CM2000, a care
management company, to help
keep people in their own homes
and at the same time reduce some
8
Adrian Smales
of the healthcare needs traditionally
associated with ageing. There are
many factors associated with frailty
and risk of falling, such as low grip
strength, muscle mass, hydration
levels, low heart rate, and heart rate
variability. These can be monitored
and measured at home using the
latest wearable technologies,
even without the supervision
of medical professionals.
He says: “Through a knowledge
transfer partnership, we are
attempting to identify how
to use the measurement of these
risk factors via wearable tracking
technology to intervene early and
prevent falls from occurring in
the first place. The purpose of the
partnership is to develop and hone
predictive techniques to help identify
those at risk.”