Healthcare is brimming with technology, revolutionizing the overall dynamics of quality care. The big data revolution is already underway. The argument is best expressed in Desiderius Erasmus’s famous aphorism, “Prevention is better than cure”. Data is both omnipresent and omnipotent. With the escalated employment of wearable devices, digitization of healthcare records, patient surveys, generic databases, and many other sources, the sheer volume of data being collected is overwhelming. Here enters the protagonist: Big data, shifting the dynamic from predictive to preventive medicine.
Big data versus traditional computing
But what is big data, and how big is it? In simple terms, big data refers to the enormous volume of data produced and collected from a vast variety of digitalized sources. These data sets are too complex to be processed by traditional computing applications, hence, special algorithms are required to get the most out of them. The enormity of big data is overwhelming. By the end of 2022, it is estimated that 94 zettabytes (ZB) of data would be present in the digital world, which is twice the amount present in 2020-up to 44 ZB. If you’re wondering how many bytes is 1 ZB, it’s 1 with 21 zeros. That’s massive. To grasp this enormity, a single zettabyte is equal to a trillion GB or 250 million DVDs. Let that sink in for a while.
Big data has taken over every major industry
Almost every industry is benefitting from big data analytics-detecting patterns, gaining meaningful insights, and solving complex problems, all to provide an ultimate consumer experience and expand their businesses. Big data in healthcare is no different. Healthcare-related data is being collected from a variety of sources such as electronic health records, genomic data, patient portals, smartphones, wearable devices, patient surveys, and so on. Careful analysis of these gigabytes of information can reveal trends that generate new ideas and approaches to improve patient care.
How health risks are reveal by analyzed data
Personalized medicine is the current hot topic. Risk factors for each one of us are different, but wouldn’t it be great if we can get our own personalized list? This is just the tip of the iceberg. The analyzed data can reveal health risks, environmental hazards, lifestyle, and genetic factors which will, on the first hand, prevent illness, furthermore, deliver hyper-personalized treatment options. The scanned data can be utilized to flag medication errors to avoid any adverse events. Data-driven research in medical and pharmacological fields can unleash some great discoveries in disease prediction and prevention. In addition, knowledge derived from big data analysis allows physicians to make sound clinical decisions that cut huge costs of hospitalizations by preventing frequent hospital admissions. Curating treatment options for cancer, reducing prescription errors, staffing management at hospitals, mass health assessment, improving telehealth, and so on; the list of applications of big data in healthcare is lengthy.
Going forward, the true potential of big data analytics will only be realized when the trends and patterns are converted into actionable knowledge for healthcare personnel to use. For this, necessary training programs should be included to ensure the necessary skill set for data handling and interpretation.
Though big data face certain legal and ethical issues, it holds a promising future for taking personalized medicine to a global level. It is destined to revolutionize healthcare.
The author is based in Toronto, Canada, and has more than a decade of experience in Technology design and implementation in diverse industries such as retail, health, logistics, energy, and consulting. Currently, the author is the strategic advisor to the CIO at Canadian Nuclear Laboratories Ltd and a technology solution partner for the University of Toronto for the Cannabis & Vaping research and development campaign.