How big data is transforming medicine

There are endless reasons why future-focused businesses are harnessing their reams of big data sources. These include simple internal process enhancements and streamlined operations that boost bottom line, to granular business intelligence that dictates high-level strategic decisions. Big data drives big business gains. High-volume data analysis is so widely accepted, the term ‘big data’ is almost obsolete.

Behind the scenes, however, big data is also advancing science and medical fields across the world. Data is not only boosting thousands of businesses’ revenues, it’s contributing to solving world problems like deadly disease outbreak.

Here are three ways big data is contributing to the ‘greater good’:

Disease mapping

With a shortage of doctors and nurses around the world, scientific insight on how diseases develop and spread is absolutely invaluable when allocating resources. In the past, public health organizations had to make incredibly tough decisions about where to allocate the treatment and manpower. Now, however, big data — extracted from health records, internet resources and social media is being used to tackle deadly outbreaks more effectively.

Whilst traditional risk maps become outdated almost immediately, digital maps with accurately geo-positioned data allow health organizations to see the full scale of an outbreak, and make more accurate predictions.

With the Ebola crisis which started in 2014, platforms and applications were deployed to collect valuable data to understand and communicate about the outbreak in real time, to allocate medical supplies and resources as quickly and efficiently as possible. Unicef’s data showed a clear correlation between people’s mobility and the spread of Ebola.

unicef ebola mobile data image
Mobility data identifying south ferry line as the most common route of travel from an Ebola-infected area in Kaffu to Freetown area. (Source: Unicef)

UNICEF’s Edutrac, a mobile-based data collection system, meanwhile, aggregated real-time data about teacher and student attendance in Sierra Leone to ensure hygiene equipment had been correctly delivered to schools.

In Europe, Influenzanet uses online data to gather information about symptoms related to influenza, as well as Salmonella, E. Coli, and the Zika virus. Scientists are able to map out risk charts in order to predict future outbreaks, should they start to accumulate.

screenshot map
Amount of influenza-like illness reported around the UK in real-time. Map shows a gradient from no reported (blue) to very high (red). Updated every 3 minutes. (Source: /

Wearable technology data

On top of the explosion of personal tech that monitors heart rate and step counts, there is a whole market of sophisticated wearable tech in development. These wearables aim to contribute towards keeping the public in good health, in turn removing the strain on hospitals and general practices. For example, there’s tech that could act as a skin patch that performs blood tests or measures blood sugar levels, and earbuds that detect abnormal heartbeats.

diabetes patch photo source Hui Won Yun, Seoul National University
Experimental diabetes patch. (Source: Hui Won Yun, Seoul National University)

The most exciting prospect of this personal health technology? The reams of data collected over time will give doctors a far more comprehensive view of patient information, rather than from one-off tests. On top of this, it will provide in-depth information for spotting trends and making accurate predictions for higher-risk patients.

Through the use of wearable tech, patients are reminded to take medication, or to alter their activity levels, perhaps due to an irregular heartbeat or a change in blood-oxygen levels. This data can be integrated automatically with other data streams to help alert doctors and family members, in the event of an emergency.

Uncovering dementia risk

Currently, there are 850,000 people with a form of dementia in the UK. With this number set to rise to over 1 million by 2025, there’s a push to understand what factors are involved in the development of such brain disorders. Worldwide, dementia is the leading cause of disability and dependence in older adults.

Today, scientists are tapping population data sets to detect patterns and risk factors; only by dissecting these vast data lakes do clear patterns start to emerge. The Framingham Heart Study (FHS), for example, has followed three generations of participants since 1948, observing common factors that contribute to cardiovascular diseases.

Using comprehensive data sets, researchers can unearth new combinations of factors that increase the risk of dementia later in life. The findings could help clinicians to spot at-risk people in advance.

While these are just a three examples of how big data is being used to combat serious health crises, it’s clear that data is as critical in the world of medicine as it is in business. Ultimately, data analysis helps us to prepare for any potential issue or to take immediate action when disaster does occur. Read more about how Kognitio is empowering businesses to make ultra-fast insights from their data sets.