Marketing, musings, and the future
Big data and personalized medicine have been industry buzz terms for quite some time, but while it’s widely known there are correlations between the two, many are still struggling with how to effectively leverage mass amounts of data in order to improve efficiencies, reduce costs, and advance patient-centric treatments.
With healthcare costs in the U.S. increasing steadily over the last 20 years to 17% of GDP, healthcare experts are looking for every path possible for efficiency and reform. Many believe that a long-term source of savings could be the use of big data in healthcare; in fact, the McKinsey Global Institute estimates that applying big data strategies to better inform decision making in U.S. healthcare could generate up to $100 billion in value annually.
The creation of this value lies in collecting, combining, and analyzing clinical data, claims data, and pharmaceutical R&D data to be able to assess and predict the most efficacious treatment for an individual patient. Many have envisioned this as a physician’s portal, which would enable clinicians to query similar patients and see what treatments worked for others, and thereby more effectively choose the best treatment option. Before the true realization of big data integration in healthcare, however, three key areas will need to be addressed that will both enable this vision and create value from big data strategies.
Check out the rest of my article as published in GEN here.