“The EHR market has commoditized now and the healthcare domain is coming into an era where most other domains, like the financial domain, have been for a long time – understanding risk, identifying and mitigating risk, and finding tools to do so,” said Fred Rahmanian, chief technology officer at Geneia, a vendor of population health, remote patient monitoring and analytics systems. “One reason people will see a lot of activity here is because of the ability to ingest a lot of data and extract insights from that data. Healthcare analytics is front and center now.”
Healthcare organizations must understand the massive troves of data they’re sitting on to best function in the burgeoning value-based care market.
“In this political climate, value-based care and risk-sharing models are going to be front and center in the next few months; they are backed by both sides of the aisle,” he said. “This includes emphasizing identifying and mitigating risk at a high level and, more important, reducing the reporting burden on healthcare organizations because as they move into risk-sharing models the reporting requirements become much more strenuous.”
Rahmanian stressed that when it comes to healthcare organizations and value-based care, the early bird gets the worm.
“Know your risks and identify them as early as you can, because when you go into this value-based care and shared-risk environment, that is the most important thing you need to know about your patient population,” he said. “The No. 1 rule of risk management is truly knowing your risk. Healthcare organizations need to understand their populations and have proper tools that allow them to stratify their populations the right way.”
Rahmanian said there are some standard ways to do this, but that as the amount of data increases and the technology evolves, so, too, do the ways healthcare organizations can identify risk.
“As we get more and more data, we can look for new risks in ways that we could not before. Something that used to be fairly remote to us was identifying patients at risk for opioid dependency, but now with the amount of data we have, maybe a collection of medical and prescription claims can help us identify for this dependency; there are markers we can find in this historical data to help us identify new patients,” Rahmanian said. “There are ways to identify new risks and that’s where things become very interesting.”