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CHICAGO (August 27, 2019) – BCS Financial Corporation (BCS), which provides insurance and financial products to Blue Cross Blue Shield Companies, has selected Blue Health Intelligence®’s (BHI®) award-winning predictive algorithm to identify members who have or may develop health conditions that cost more than $250,000 a year. The goal is to help individual Blue Plans work with these high cost claimants (HiCCs) to improve their health outcomes and mitigate escalating expenses.
While HiCCs represent fewer than one in 1,000 of all Blue Plan members, they are expected to generate nearly $20 billion in annual costs by 2022. In developing meaningful solutions for this vulnerable population, BHI found that three of every five high cost members are new or emerging, and many suffer from heart disease, cancer, or neurological disorders. The remaining 40% have recurring high costs each year, and typically suffer from chronic conditions such as blood disorders, metabolic illnesses, and renal disease. Contributing factors for all HiCCs include specialty drugs, new genetic therapies, and advanced treatments such as cancer immunotherapy.
The BCS and BHI HiCC solution, currently being implemented by five Blue Plans, is called the High Cost Predictor Algorithm (HCPA). It uses machine learning to efficiently achieve the needle-in-a-haystack work of identifying who among tens of millions of Plan members will reach or exceed more than $250,000 in annual costs, including a few thousand whose care is expected to exceed $1 million per year. Earlier this year, BHI was recognized by MedTech Awards as having the best predictive analytics solution.
“BCS is committed to helping Blue Plans and their members achieve high-quality healthcare at a lower cost through a variety of tools and reinsurance solutions, and we are thrilled to add this leading-edge solution to our cost-containment offerings,” said Peter Costello, BCS Financial’s president and chief operating officer.
BHI specifically trained and validated the HCPA using longitudinal claims information from more than 190 million Americans in its National Data Repository, along with publicly available socioeconomic and claims derived data. BHI’s data scientists evaluated thousands of predictive variables to isolate the clinical complexities, utilization patterns, and contextual factors most closely linked to extremely high costs.
“The combination of BHI’s machine learning, artificial intelligence, and clinical validation make these predictions extremely scalable, actionable, and accurate,” said Swati Abbott, BHI’s CEO. “As a result, BHI is proud to be supporting BCS’ early identification efforts to help lower members’ high costs and improve their health experiences.”
The HCPA is now part of the BCS Risk Navigator suite of cost-containment solutions. Using its National Data Repository, BHI augments the predictive model output with additional historical insights on each member to aid nurse reviewers.
