Prime Insight
Prime Insight

Big Data in Healthcare

Posting date: 10 December 2019
Matthieu Pirouelle our consultant managing the role

Data Analysts have the Power to Change Life Expectancies

Of all industries around the world, healthcare is the one that collects most data. If you want the definition of BIG in the term ‘big data’, then the billions of health interventions each day is it. And each intervention includes multiple data points itself. 

Consider a simple appointment with a physician. You may divulge information about your general health and lifestyle, have blood samples and temperature taken, your heart rate monitored, and so on. A follow-up appointment will collect data on how you are reacting to treatment.

Connected and wearable devices could pump data in real time that includes all your vital signs every second of the day. This isn’t simply big data, it is huge. How could this data be harnessed most effectively?

How Big is the Data in Healthcare

The data collected in the worldwide health industry is mind-boggling. It comes from a multitude of sources – healthcare providers, physicians, pharma companies and insurers. It includes blood tests, physical exams, biopsies, invasive and non-invasive examinations, research, prescriptions, over-the-counter sales, and so on. It is estimated that around a third of the world’s data production comes from health.

This is a colossal amount of information that, until relatively recently, could not be used to best effect. There just wasn’t the technology around. Until now, all this data has been collected and stored – stored and used mostly for niche research or locally.

The Internet of Things is transforming business, and the healthcare industry has a similar opportunity. New technologies have provided the framework connectivity and capability to finally access this data at scale – and this could transform diagnosis and treatment for billions of people.

Data Analysis - The Holy Grail of Healthcare

The healthcare industry has been collecting data since healthcare was first considered a service. We’ve made enormous advances because of this data. As our ability to collect, collate, crunch and interpret this data has improved, so too has the diagnosis and treatment of illness and health conditions.

The increase in longevity of life owes much to the advances in our capability to analyse ever-increasing amounts of data effectively. You see, we’ve always collected data. As technology has improved, we’ve been able to improve the quantity and quality of that data. Now we have the capability to understand the nature of health conditions on a scale and at a pace that could never have been imagined just a few years ago.

It is this understanding of data that is key to producing the most radical transformation in the healthcare industry the world has ever witnessed. Data analysis in healthcare has the potential to discover causes of illness and disease, improve health provision, and reduce the costs of healthcare. 

The analysis of data in healthcare could lead to an explosion in life expectancy. For centuries, people have been searching for the elixir of life – something that could make people at least semi-immortal. Could big data be it?

Big Data and the Internet of Things Could Explode Life Expectancy

For around 300 years, between 1500 and 1800, longevity remained stuck between 30 and 40 years. Today, longevity in most developed countries is more than 75 years. Partly, this is because infant mortality has collapsed: medical science has largely removed causes of infant death such as cholera, tuberculosis, and smallpox.

More effective analysis of big data should allow faster progress toward tackling diseases that affect people in older age – Alzheimer’s, diabetes, cancer, heart disease, and so on.

Key to this will be advances in technology that are complemented by data analytics at scale. A Bank of America report published in early 2019 predicts that average life expectancy will improve to more than 100 years, as the pace of medical advance accelerates rapidly. It forecasts that medical knowledge will double every 73 days by 2020, compared to doubling every 3.5 years in 2010. It calls the meeting of technology and humanity ‘techmanity’, and a revolution in healthcare. Several drivers enable this pace of knowledge growth, including:

• The adoption of digital tools to enable growth in data collection• Machine learning and AI to make forecasts on available data

• The adoption of cloud infrastructure to allow growth in data processing

• Technology-friendly leadership in healthcare

However, this progress is unlikely to be plain sailing.

Major Challenges to Use of Big Data in Healthcare

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