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How Analytics Are Helping to Mitigate and Share Risk in Healthcare
By Per Bauer
With the ACA in limbo, as well as the incentives it created for EHR implementation, experts are still looking to big data to drive the future of American health insurance.
Electronic health records (EHRs) have been standardized across healthcare since the federal government started EHR Incentive Programs in 2011. 87% of office-based physicians had adopted EHRs as of 2015, according to HealthIT.gov, more than double the number who had adopted these systems in 2008. EHRs not only standardize and streamline many of the day-to-day processes of medical recordkeeping, but create a mountain of data that analysts work to effectively leverage to inform healthcare decisions in the future.
Projecting what healthcare will look like in the coming years is nearly impossible. With the ACA in limbo and some healthcare providers backing out of the marketplace, it seems as though American healthcare will transform yet again over the next half decade. Seeing that change in this direction is inevitable, lawmakers have made a new effort to find healthcare models based on population health management — a treatment approach that uses big data to optimize patient outcomes.
Healthcare experts believe risk-sharing will also be a central to this next paradigm shift in the industry. Risk-sharing, in its most basic form, involves creating large pools of patients across a wide range of ages and health conditions. The theory goes; if people with varying health conditions enter into a large coverage pool, risk can be spread more evenly among the pool, thus cutting down on the individual cost of coverage.
In an interview with Forbes, Dr. Brad Stuart explained how this theory can help to divert precious funding towards the creation of potentially life-saving new treatments. “In the accountable care model, patient and provider (and patients and communities) agree to operate in a shared-risk model,” Stuart said. “And the bottom line is that the further the system moves in the direction of risk sharing, the more important savings will become, and the more providers will invest in and support innovation.”
As is the case in almost anything relating to healthcare, the full adoption of data analytics from a patient care perspective has been a slow process, but in recent years, the floodgates have really begun to open.
“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. “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.”
Data collected from sources such as EHRs can help healthcare decision-makers create the most cost-effective pools based on a nearly endless array of data points. With big data and predictive analytics, insurance companies can optimize the placement of particular patients based on their financial means and medical problems in order to provide the most affordable care to those who need it most.
While the future is always uncertain, risk-sharing is helping hospitals to protect patients for anything when the stakes are highest. Healthcare stands to benefit from the ability to see where people’s current health conditions may lead them in the future, and predictive analytics and big data will make that reality a bit more attainable.
The world of IT has already seen the benefits of solid data analysis with programs like TeamQuest. The Vityl suite gives IT managers a detailed look at their infrastructure and an at-a-glance view of its health. Powerful predictive analytics help determine at-risk systems well in advance of actual outages or slowdowns. With this data-driven glimpse into the future, IT professionals can take control of the future of their systems, just like healthcare providers hope to leverage their data to control the future of insurance.