Leveraging Behavioral Economics to Drive Success in CDHPs

Christina Mattina

Experts from Express Scripts discussed how data on consumer behavior can be used to improve health outcomes and control the costs of care during a session of the Academy of Managed Care Pharmacy 2017 Nexus meeting.
Bill S. Patterson, MBA, senior director of benefit solutions, and Christopher G. Lehmuth, MBA, BS, senior director of enterprise data science and information products, explained how Express Scripts combines both of their fields of expertise to help members get the most out of their plans and, ideally, improve their health while spending less money.
Behavioral economics, a field that links intentions to actions, is especially relevant as consumers are increasingly being asked to make more decisions relating to their plan benefits, Patterson said. In order to remain competitive while containing costs, more and more businesses are offering consumer-directed health plans (CDHPs) combining health savings accounts and high-deductible health plans, and Express Scripts anticipates that 4 in 5 employers will offer CDHPs by 2020.
Throughout the session, Patterson and Lehmuth used the fictional example of an employee, “Melanie,” who has diabetes, chronic pain, and depression, and is newly enrolled in a CDHP. By providing better education to plan members like her, promoting medication adherence, and helping them budget, “the industry is pivoting to support them” in novel ways, Patterson said.
Lehmuth delved deeper into the data science side of the equation, explaining that data from claims, patient portals, call centers, and other platforms are transformed into insights that are actionable for stakeholders. The sheer volume of data now available, as well as the ability to update the data in real time and link them across sources, allow for greater possibilities but also present a number of new challenges.
“This is a problem,” Lehmuth said of a survey in which 77% of healthcare executives graded their organization at a C or lower in terms of their preparedness to act on data. “We know this is an issue, but it’s also a huge opportunity.”
He emphasized that data science is a tool to help with decision support, allowing clinicians to focus more on patient care, but it is not intended to replace diagnoses or other critical decisions by healthcare professionals. These clinicians play an essential role in helping quantitative data scientists zero in on which data can be transformed into retrospective, predictive, or prescriptive insights.
Returning to the fictional patient Melanie, Lehmuth presented a slide showing how using predictive insights could have been used to alert her and her physician after identifying an accelerating pattern in her healthcare spending, thus allowing them to work together on ways to improve her health outcomes. With those insights in her hands, Melanie will better understand the health and financial risks she faces and how to avoid them. For instance, she could be encouraged to switch to generic metformin or have her diabetes monitored more often through glycated hemoglobin tests.
“Healthcare is changing, and we’re using behavioral economics to drive better decisions, which can lead to healthier outcomes,” Patterson concluded. “Data and analysis are transforming the way we develop actionable insights for Melanie, for her physician, and for healthcare providers in general.”
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