The Rise of Integrated Data in Medical Devices

The generation and analysis of massive amounts of data have completely transformed several industries, and this trend will likely continue, revolutionizing almost every facet of the economy. Indeed, a recent analysis concluded that roughly 50% of the S&P 500 will be replaced over the next 10 years, which are “shaping up to be the most potentially turbulent in modern history” (Anthony, 2016). This analysis also showed that over the past 6 years, at least several companies that are heavily reliant on big data analytics entered the S&P 500 (e.g. Facebook, Netflix, and Trip Advisor) (Anthony, 2016). This revolution has largely been driven by ever-increasing computing power at less cost (as per Moore’s Law), coupled with precipitous drops in data storage costs. Additionally, there has been a dramatic uptick in consumer-generated data, and the rise of the platform economy which is broadly characterized by services that act as an intermediary to bring together groups of users to facilitate economic or
social exchange (Simon, 2013; Evans, 2016).

The prevalence of large datasets (i.e. big data) is providing a resurgence for the field of statistics. While much of the analyses being used today were discovered in the beginning to the middle of the 20th century, over the last decade, innovative artificial intelligence processes have emerged that are superior to the traditional statistical approaches. These advanced techniques are increasingly being used for data integration purposes, whereby heterogeneous data can be acquired, combined and incorporated into a structure that allows different data types. For instance, in the clinical trial industry, this approach can allow for traditional clinical trial data, electronic health records, imaging data, sensor data, and patient-provided data to be merged and utilized for a variety of purposes. We have only scratched the surface in terms of the impact that integrated data analyses will have for commercial purposes.

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