New machine learning company Cardinal Analytx closed a $6.1 million Series A financing round to fund the development of its healthcare technology with data science, engineering and clinical capabilities. Investors included Cardinal Partners, Premera Blue Cross and the Stanford-StartX Fund.
To reduce the costs associated with health insurance, the company developed a machine learning platform that uses artificial intelligence-based predictive modeling and intervention recommendations to identify potential high-cost members and provide customized medical recommendations. The information allows care managers and clinical teams to anticipate and prevent situations leading to high healthcare costs like surgeries or hospital stays.
“Unexpected increases in healthcare costs that result from potentially dangerous and expensive medical conditions can have a lasting effect,” CEO Thomas McKinley said in a press release. “Conventional analytic approaches have identified existing high-cost enrollees, but that’s already too late and does not effectively address prevention. Cardinal Analytx’s approach looks for members who are likely to have serious medical events before they occur and then outlines a clinical intervention plan to mitigate escalating health concerns before the onset.”
To test the solution, Cardinal Analytx partnered on a pilot program with Premera Blue Cross to analyze the data from 1.4 million members and predict new high-cost members for the next year. The technology was able to accurately predict individuals who would become high-cost members, 67% of which were not identified by other approaches.
“Cardinal Analytx enabled us to better predict which members could benefit from early interventions and provide effective recommendations to engage them in healthier behaviors,” Premera Blue Cross’s executive vice president of healthcare services Dr. John Espinola said in the statement. “The pilot results were outstanding, compelling us to invest in a team and company that is on the cusp of transforming how we help patients who need it the most.”
The company came out of the Stanford University-affiliated StartX startup accelerator and was founded by doctors and Stanford professors Arnie Milstein and Nigam Shah — whose research found that only 10% of insurance enrollees make up 70% of healthcare spending and that 60% of high-cost members were not high-cost the previous year.
“Our goal is to bring precision to the practice of medicine by coupling a machine’s accuracy with a human’s judgment and intuition,” Shah said.
