Following a recent PwC report asserting that health insurers must take a more active role in working with healthcare providers on clinical analytics, Hartford, Conn.-based Aetna announced a partnership with Cambridge, Mass.-based GNS Healthcare to use data-driven models to identify members at risk for metabolic syndrome, a condition that leads to heart disease.
A person has the disorder if they have three or more of these conditions: large waist size, high blood pressure, high triglycerides, low HDL ('good') cholesterol and/or high blood sugar. GNS' Reverse Engineering and Forward Simulation platform will take an at-risk member's health information and predict which condition the member might develop next and how quickly. (For example, someone with high triglycerides and low HDL might be at risk for high blood pressure within a year).
To improve or eliminate the risk factors, the model then matches each member with specific interventions that are most effective for that condition.
"Reducing or eliminating the impact of metabolic syndrome can improve the health of millions of people and reduce health care costs. Aetna offers many programs to help members understand their risks and take steps to improve their health. Using data, we will now know very quickly which of these strategies works best for specific members," said Michael Palmer, the head of the Aetna Innovation Labs, in a statement. "We will also know where we can make improvements or create new programs to help our members."
Carol McCall, chief strategy officer for GNS, adds that the models will be built from "millions of distinct data elements Aetna provides."
"Working with Aetna to learn about the progression toward metabolic syndrome using massive real world data is a natural extension of our capabilities," she added.
If the program is successful in treating metabolic syndrome, it could be extended to other syndromes as well, the companies say.