Physicians often review 10 to 15 variables to diagnose a single patient – a physical exam, lab values, and patient history, to name a few. Precision medicine has enormous potential for eliminating the costly trial-and-error that is intrinsic to medical practice. Plans must be prepared to offer the right test, at the right time and in the right location – all within coverage policies and based on data and evidence. As advanced diagnostics and targeted treatments evolve over the next few years, a physician soon may be faced with more than 1,000 diagnosis variables.
This stream of complex data will include genetic-level mutations as well as other characteristics that, in innumerable and unique combinations, drive how a specific patient will respond to a specific treatment. While the volume of data physicians need to synthesize today can be overwhelming, the future will bring astronomical growth in that data as we move forward in the age of precision medicine.
With the tremendous growth in advanced diagnostics, health plans need to enable an automated approach to evidence-based decision support at the point of care, so as to optimize the use of precision medicine as a catalyst to improve care and reduce cost. The challenge is to do so while not promoting overutilization of advanced diagnostics themselves.
The term "precision medicine," popularized by business strategist Clayton Christensen, describes a step forward in the art of medicine. The ability to test for genetic predisposition to a disease (or its recurrence) is the aspect that garners the most public attention. But more important for health plans is the much larger category of pharmacogenomic tests. These tests pinpoint a patient's diagnosis and determine which drug is the best option, which has a far more immediate impact on costs and care.