Digital transformation was already underway, but Covid-19 accelerated its adoption.
Can a massive dose of data actually make you better? It is a question that more and more healthcare providers are answering in the affirmative, although sometimes cautiously. Today, more than half the nation’s healthcare providers are using Big Data in one form or another, and even more are expected to follow.
But for anyone raised to understand the importance of accuracy and precision in so many areas of human activity, there is something about the concept of Big Data that seems deeply unsatisfactory. After all, how is Big Data really any different than noise? The influx of data doesn’t always translate to relevant or useful information.
The adoption of interconnected systems is causing the size of Big Data to constantly grow. Big Data in healthcare includes information from all types of sources including clinical health records, medical imaging, claims data, patient generated health data, public health data, data generated from academic studies, pharmaceutical data, and more. This makes it challenging to segregate and filter Big Data in forms where it can be digestible.
An estimated 80 percent of patient information remains unstructured making it more challenging to mine data. Taken in aggregate, that glut of information is both too large and too complex to be processed using traditional software applications. To combat this, innovative new forms of data processing, including some using artificial intelligence and machine learning, are being devised to make sense of it.
Yet there is more than enough already available in digital form to allow healthcare Big Data to be converted into clinically actionable information and, over time, to transform the entire industry. Until this year, the transformation of healthcare into a digital enterprise had been gradual and underway for the better part of a decade. Then, as COVID-19 peaked across the US, the need for remote and digital care delivery became a core tenant of healthcare.