You visit your doctor for help with an ongoing health problem and walk out of the office with the new prescription you hope does the trick. A few days after starting the prescription, you notice you are having an unpleasant reaction to it. Now you need to go back to the doctor for either a prescription adjustment or a new prescription altogether. Sounds pretty routine, right? But what if healthcare could eliminate these kinds of experiences?
That is the goal of a certain segment of the healthcare sector obsessed with something known as ‘pharmacovigilance’. If you are not familiar with the term, don’t worry. It’s a pretty big word most of us have never heard of. The World Health Organization defines pharmacovigilance as “the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem.”
A simpler way to define it is to say that pharmacovigilance is the science of studying and understanding adverse drug events (ADEs) so as to mitigate such events in the future. Rock West Solutions, a California company that specializes in advanced signal detection and big data, says that the future of pharmacovigilance rests squarely on the shoulders of developing new ways to use big data.
Big Data and the Current System
The U.S. is generally accepted as having the most advanced healthcare delivery in the world. Our health insurance system may not be all that great, but no other country boasts the R&D, technology, and delivery system we have here. So why do we continue to have so many problems relating to pharmaceuticals? Why are ADEs an ongoing problem for so many patients?
Our system has an inherent weakness: our state-of-the-art technologies are still inadequate in terms of applying big data in useful ways. Healthcare facilities and researchers now have virtually unlimited capabilities for gathering and storing as much data as they want. Yet they do not have the capability to effectively extrapolate from big data in order to make actionable decisions.
As such, the real challenge for American healthcare is not one of developing new drugs or treatment modalities. We are doing fine in that area. The big challenge is to find a way to use the endless reams of data we collect to improve how we deliver healthcare. It is one of developing signal processing that separates actionable data from noise. Tackle that giant and you change healthcare delivery dramatically.
Pharmacovigilance Relies on Data
Tying all of this into the science of pharmacovigilance, it must be understood that pharmacovigilance relies heavily on data. It’s one thing to understand that a certain drug is linked to a certain group of ADEs, but it’s an entirely different matter to understand those ADEs in the context of a larger data set involving other drugs and ADEs. Context is everything when trying to figure out ADEs.
Another thing to remember is that time is the friend of pharmacovigilance. Small data sets over limited amounts of time provide little benefit for improving drugs or reducing adverse effects. On the other hand, large data sets compiled over many years are often the key to finding out what’s causing ADEs for a particular drug.
Everyone from scientists to pharmaceutical companies to government regulators is interested in using pharmacovigilance to make the drugs we use safer. They also want to make the drugs more effective at the same time. In order for that to happen, pharmacovigilance and big data have to work better together. The good news is that the powers that be are working on making it happen.