Aiding healthcare through data analytics

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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.

Growing challenges in

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 in healthcare.

In the 60 years since Independence, we have managed to increase 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, living longer has not translated to better quality of life.

According to reports, various National Health and Morbidity Surveys carried out in the country have revealed that the number of those afflicted with lifestyle/non-communicable diseases such as diabetes, hypertension, obesity and cancer, has risen, and more worryingly, continues to rise.

Of particular concern are the statistics on obesity and diabetes.

The 2015 National Health and Morbidity Survey revealed that obese Malaysians make up 17.7% of the population, compared to just 4.4% in 1996. The same survey found that 17.5% of Malaysians aged 18 and above – around 3.5 million people – have diabetes. In 2006, this figure was 11.6%.

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.

More needs to be done.

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 about greater efficiencies and develop an integrated healthcare system.

The capture and analysis of this mass of raw data has the potential to transform healthcare and 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 and follow-up.

Understanding the data captured

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.

For example, Vizient, a healthcare services company, is able to take in data from a variety of different sources, such as lab and patient data, to recognise patterns and provide this data to doctors to provide recommendations for how members 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.

Leading the way through data

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 help 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.

However, for example, Geisinger Health System has a platform designed to deliver quick and easy data to caregivers, enabling their staff to search through 200 million patient note records in seconds to find relevant conditions and medications, which helps them analyse the success of treatments, identify areas of improvement, and determine ways to save time and money for both patients and providers.

Data to help in future

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.

Kamal Brar is vice-president and general manager of Asia Pacific at Hortonworks, a Big Data software company based in California, United States.