Data Analysts Have the Power to Change Life Expectancies
Of all industries around the world, healthcare is the one that collects the 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 siloed – 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
Despite the obvious potential to tap into big data and improve healthcare for future generations, the industry faces several challenges to do so. These include the following:
• Fragmentation of technology
Even in the same country, healthcare is administered by different health bodies. These often use disparate technologies that don’t connect. The way in which data is collected and stored in different systems makes it difficult to build insightful databases that include all data. It can be done, but the cost of doing so makes it unviable. Therefore, the fragmentation of healthcare reduces the ability for worldwide data to be collected and analysed to best effect.
• Confidentiality issues
Further, there are confidentiality issues to be overcome. Healthcare providers are traditionally reluctant to release information, especially in accessible formats. Violation of confidentiality is a major concern, and in a world in which cyber security is a major concern the risk of being sued by individuals or a case lawsuit cannot be ignored.
• A lack of trust in big data
There are concerns within the healthcare industry of the quality of data within the industry itself, especially when collected by third parties. A case in point is the failure of Google Flu Trends to perform as well as other models, despite access to far more data. Success of big data in healthcare is dependent upon that data being representative.
These challenges must be overcome, and may require policy change at governmental levels. Entrenched institutional practices must also be overcome, in which decision-making processes involve many medical practitioners who don’t share their findings effectively. This experience shows that if data collection tools don’t fit into exiting frameworks, they are unlikely to be used.
Where Will Data Analytics Take Healthcare?
Data analytics has the potential to transform life. However, to do so, several challenges must be overcome. Organisations must collect data from many sources effectively, and doing so may need a cultural change as well as legal basis to do so from governmental policies.
As a first step, it is likely that wearables will help to enable greater proactivity in selfcare, with physician appointments replaced by real-time monitoring of existing conditions and remote consultation. Decision support software may be implemented using collection and analysis of data on the wider scale, though care will have to be taken not to box patients into ‘average patient groupings’. In time, as availability of and access to healthcare data improves, it is likely that insights will help deliver more effective care and solutions to complex health issues.
In time, it is likely that big data will help to extend average life expectancy to ages that would once have been considered sci-fi longevity.
Data analysts and data scientists can make a real difference in the world. Thanks to their ability with big data, we may all be living to over 100 years old soon. Do you have what it takes to be the difference? Contact Prime Insight today to discover exciting opportunities in data across all industries.