The world’s computers contain massive amounts of health data. Three out of every ten data storage systems are within healthcare. One patient creates nearly 80 megabytes of electronic protected health information (ePHI), including electronic medical records (EMRs), images, and other confidential data. In other words, this industry is the realm of big data – huge quantities of data, both structured and unstructured, that can be mined by organizations and studied to their benefit, but that is so voluminous that it is challenging to process it through traditional program and database methods.
Simply from a standpoint of how to handle and understand it, this data can be the source of many headaches.
Regardless of whether big data can be overwhelming, understanding and using it is a huge point of focus for those within the healthcare information technology (HIT) field – as it should be. The data has clear values to healthcare firms from numerous perspectives, not just in lowering costs but also as clinical information and as fodder to improve operations. Just to look at the first of those, McKinsey estimated the total worth of healthcare big data (in terms of the insights it could provide, its “data-related value”) at greater than $300 billion.