Driven by increasing costs and an aging population, the global healthcare industry is transforming from a pay-per-service model to a more accountable, value-based system in which risk has shifted from payers to providers.
This shift requires providers to significantly change the way they operate. They must focus on the delivery of personalized medicine that is tailored for each patient, while also deepening their understanding of patterns within broader population health.
Advanced analytics allows healthcare providers to quickly and accurately analyze huge quantities of data to make predictions on, and even suggestions for dealing with, future risk scenarios.
Thanks to the digitization of healthcare, most organizations now have access to vast pools of digitized data. It is not uncommon for hospitals to gather more than 100 data points per patient per day1, and in the US over 85 percent of healthcare organizations have now adopted an electronic medical record (EMR) system.2 As a result, their data is not only growing in volume, but also in complexity, as the types of data and sources from which it comes are multiplying quickly.
At Intel, we work with many healthcare organizations that are innovating ways of applying advanced analytics to their data to identify and mitigate patient risk. Let’s explore three examples of providers whose efforts have already produced tangible results: