The Journal of mHealth Vol 1 Issue 3 (June 2014) | Page 32

Conference News
Continued from page 29

ance companies, employers and healthcare providers can view a comprehensive
picture of an individual and a population's health – one that is more accurate
and trustworthy than a first-person narrative.
This increase in predictive ability should
be a force for good, but human reactions
may be unpredictable. Prognosis could
provoke change, equally it could provoke
over- or underestimation of the risk, or
– if the prognosis is not positive – to
ignore it altogether. We already know
that humans have a tendency to drift
towards hyperbolic discounting. The
risk of a terrorist attack, which statistics
tell us is highly unlikely, is seen by most
respondents as being far higher than diabetes – which statistics suggest is a much
likelier fate. Moreover, most people have
an inability to imagine how they will age
and how their preferences and personalities will change.
The most effective way for humans
to take on and realise information is
through feedback loops. The first stage
is evidence, the actual data; then comes
the prognosis based on the data; the
relevance of the prognosis has to be
realised in its social and physical context;
the consequences of the prognosis are
understood; and the individual finally
acts according to the previous four steps.
The circle is started again.
These stages can be identified within
the use of fitness armbands that record
physical movement. Evidence (steps)
leads to prognosis (expected gains in fitness); leads to relevance (frequently in a
gaming context, which encourages participation); leads to consequences (feel
better, weight loss); and finally action
(take more steps in a day).
This does not mean there are not questions about predictive technology.
Human happiness is not a universally
defined quantity. Some may feel uncomfortable in the knowledge that our future
is already defined. Moreover, it is difficult to know what to do with prognoses that may not be beneficial; such as
a predisposition to criminal behaviour
or a degenerative condition. Predictions
can be self-fulfilling. As W.I. Thomas
and D.S. Thomas suggested in 1928, “If

30

June 2014

men define their situations as real, they
are real in their consequence.”

Reducing the burden of
chronic disease through
remote monitoring and
management
(Laurence Jacobs,
Senior Research
Scientist, University
of Zurich Medical
School)

The traditional
approach to the
management of
chronic diseases is not optimal from a
medical perspective, and it is extremely
expensive. Moreover, the worldwide
growth in cases of chronic disease continues to increase at a very fast pace.
Reasonable cost estimates place the
total financial burden caused by chronic
disease in the several hundreds of billions of dollars annually. This situation
is untenable in the long run. Left unattended, this problem is such that in the
not too distant future, no society will
be able to afford the cost of caring for
its ailing population. The traditional
approach to this problem simply does
not scale well.
Fortunately, there are alternatives to the
traditional approach. These alternatives,
at present mostly in the development
or testing phases, are not only much
cheaper, but they have the potential of
being better for the patient from a medical perspective.
The current opportunity was born not
only of necessity, though that has played
an important role, but also from the confluence of the general population's interest in health. Companies have developed
small, accurate and inexpensive biosensors. These have led to a growing availability of good quality data that can be
used to derive accurate models that can
generate alerts, or even trigger devices
to react to critical changes in the one or
more parameters being monitored.
Diabetes is a prominent example. As far
as growth, it is estimated that there will
be around 250 million sufferers worldwide by 2030, more than double the
amount estimated in 2005. A key component of the process of managing dia-

betes is to measure the level of glucose
in the blood several times a day. With the
technology of a few years ago, this process is painful , expensive and cumbersome, requiring the extraction of blood
and the use of portable meters. However, current technology already allows
for a reasonably practical way to measure glucose continuously using a sensor
that is implanted subcutaneously. Even
better, several start-ups are announcing
systems to measure glucose continuously without the need to extract any
blood at all. These sensors, several using
light, or estimating the levels of blood
glucose by analysing tears or saliva, will
soon become commercially viable. These
systems will not only be simpler and
cheaper, but they will also lead to better
methods of treatment.
There are currently many clinical trials
underway that aim to test integrated platforms, running smartphones, that measure, analyse, and report on multiple continuous measurements of a potentially
large number of important biometrics
that promise to optimise the treatment
of several chronic diseases. Patients and
their doctors can be informed in real
time on effective treatment change, and
alert on critical risk factors. This would
have been imposs