Predictive Analytics Case Study: Steve J. Tutewohl, FSA, MAAA
Twenty years ago Steve Tutewohl's clients were taking bold risks with limited information, little analytical support and hardly any data.
As an actuary working on the provider side, Tutewohl started out in a traditional role in an untraditional environment. In his early years at Valence Health he was focused on educating, informing and bringing knowledge to providers so they could level the playing field with payers when they were negotiating and managing risks.
Today Tutewohl's clients have "data that is above and beyond what the payer has."
Tutewohl and his team developed a model that combines traditional paid claims from payers and clinical data from provider systems, such as electronic medical records, pharmacy use and lab results to give providers unprecedented insights into population health. This model gives providers a competitive edge over payers. It allows them to stay profitable by identifying gaps in care, detecting early warning signs for hospital admission and measuring the quality of care, among other metrics.
"I've had a blank canvas for nearly 20 years to design and define what that is," said Tutewohl, the Strategic Accounts Officer, who leads the company's analytics and actuarial services. His team designs and executes risk-based contracting strategies by bridging healthcare IT and business.
The Affordable Care Act (ACA) created an incentive for providers to take more control. As the industry moves toward value-based service delivery models, both providers and payers are equally focused on managing population health, while lowering costs.
Healthcare is at a critical juncture, Tutewohl said, which creates a great opportunity for actuaries.
One of the first ACA challenges actuaries were uniquely prepared to address was the financial impact of risk adjustment transfers when the healthcare exchange opened.
"The insurance industry had never seen anything of that magnitude before," Tutewohl said. "It was either catastrophic or a big huge boon depending on how it paid out to you. To me, as an actuary, it was intellectually intriguing because it's unknown."
Tutewohl was intent on providing clients with as much insight as possible, so they know where they stand financially throughout the year. In order to do this, his team created a suite of analytic services, including:
- Risk score projections to estimate year-end metric
- Risk score opportunity models that identify likely missing HCC coding
- Risk transfer year-end projections based upon a series of complex assumptions
- Allocations of risk transfers back to individual members to see which segments of the block of business are profitable and which are loss leaders
An increased focus on population health management has created several applications for the actuarial skill set and they continue to expand, Tutewohl said. Actuaries possess a technical knowledge of data and modeling in addition to understanding the business drivers related to managing risk and patient populations.
Yet, many of the problems actuaries try to solve are not pre-defined, Tutewohl said. So they have to be able to ask a question, get an answer, ask three more questions and get eight more answers - and be self-driven, passionate and stubborn enough to continue to find information among the data that's available.
Predictive modeling has allowed actuaries in healthcare to take a vast amount of information, join it together to learn about individual patients as well as overall patient populations, and design programs to manage both.
Tutewohl is increasingly focused on solving even bigger problems. In the transforming healthcare landscape, he is helping healthcare systems remain relevant - whether that is increasing their market share or figuring out a new path.
"That's the mission of what we try to do with the data and analytics to support the health systems and health plans that we work with," Tutewohl said.
"There is no better place to be. Healthcare is a $3-to-4 trillion industry that is in an environment of constant change. It's recession proof. What makes it appealing is the amount of data that is out there. We're still scratching the surface of how we use that data."