Big data and the future
of healthcare industry
Vice President and General Manager of
a big data software company.
New Straits Times/Opinion/November 30, 2017
ONE
of the greatest challenges facing governments around the world is how to
provide their citizens with effective and affordable healthcare. This is in
fact a highly complex set of problems with multiple causes and a variety of
actions needed in response. Happily, advances in technology are holding out the
promise of addressing the challenge.
As in developed countries around the
world, Malaysia’s healthcare providers must deal with a rapidly ageing
population, leading to an influx of patients, and increasing pressure on
general practitioners and hospital emergency departments. People are living
longer — which actually reflects one of Malaysia’s success stories —
healthcare. In the 60 years since independence, we have increased our lifespan
by about 20 years.
Improvements in primary public healthcare, such as sanitation, food safety and protection against infectious diseases via vaccination, have all contributed to this increased life expectancy. Unfortunately, however, living longer has not translated to better quality of life.
Improvements in primary public healthcare, such as sanitation, food safety and protection against infectious diseases via vaccination, have all contributed to this increased life expectancy. Unfortunately, however, living longer has not translated to better quality of life.
Of particular concern are the
statistics on obesity and diabetes. The National Health and Morbidity Survey
2015 revealed that obese Malaysians make up 17.7 per cent of the population,
compared with just 4.4 per cent in 1996.
The same survey found that 17.5 per
cent of Malaysians aged 18 and above — around 3.5 million people — have
diabetes. In 2006, this figure was 11.6 per cent.
One thing is clear from these numbers
— more Malaysians are having to live longer in ill health.
Will the country be able to cope with
the increasing number of the elderly and ill? The proposed Aged Healthcare Act
is a start, though its primary aim is better regulation and monitoring of aged
healthcare centres in the country.
The healthcare industry has always
generated large amounts of data for purposes of patient care, compliance and
record-keeping. The advent of the Internet of Things has caused an explosion in
data, from sensors to health-tracking applications and devices that healthcare
providers can tap into to optimise resources, bring greater efficiencies and
develop an integrated healthcare system.
The capture and analysis of this mass
of raw data has the potential to transform healthcare, to enhance the
accessibility, affordability and quality of healthcare to meet the needs of
Malaysians across different stages of their healthcare journey — from diagnosis
and treatment, to post-discharge follow-up.
Big data in healthcare refers to
electronic health data sets that are so large and complex that it would be
difficult to manage and analyse using traditional software and data management
tools and methods. With big data, healthcare organisations have the ability to
let multiple hospitals exchange information, leading to a 360-view of their
patients, so doctors can give a more complete diagnosis.
Healthcare services companies have
gained significant value through the ability to take in data from a variety of
sources, such as lab and patient data, to recognise patterns and supply this
data to doctors to provide recommendations on how patients can improve their
health. Without Big Data, none of this would be possible and healthcare
organisations would be operating without having the complete picture.
When a person’s medical records are
shared among all public health institutions, the patient’s journey is
simplified from primary to tertiary care, in both the public and private
sectors, as any doctor treating the patient would have full access to his or
her medical records
There are many other ways in which
technology is being adopted, putting health data to work in the pursuit of
improved healthcare.
For example, hospitals have begun to
use radio-frequency identification (RFID) to track equipment and medicines as
they move throughout their facilities. RFID scans of an item or device can
capture their contents, location, manufacture date, order numbers and shipping
data. This information can ensure medicines are utilised before their expiry
date or quickly locate an important piece of equipment.
In the longer term, historical data
on the interactions of medicines, equipment and doctors will provide valuable information
for healthcare predictive analytics, as well as helping to plan purchases,
train staff and improve operational efficiency.
In another advance on traditional
practice, wireless sensors are being used to capture and transmit patient
vitals more frequently than staff can make bedside visits. These signals can
provide real-time alerts, so caregivers can respond more promptly to unexpected
changes. Accumulating this data over time enables healthcare predictive
analytics to proactively help predict the likelihood of an emergency, even
before it could be detected with a bedside visit.
One common problem with our existing
healthcare system is re-admission rates. Patients with heart disease, for
example, are closely monitored in the hospital, but may skip their medications
or ignore dietary and self-care instructions when they go home.
Healthcare, especially on a national
level, will continue to be a major challenge for authorities. Demographic and
lifestyle changes in populations, as well as outbreaks of unanticipated
diseases, will constantly demand innovative responses from governments and the
healthcare profession.
Fortunately, advances in healthcare
data analytics are keeping pace with the evolving nature of the challenge.
Patients and healthcare staff alike can be confident that technology is on
their side.
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