ArborMetrix Platform Selected by MI Breast Oncology Quality Initiative
ArborMetrix, the Ann Arbor-based startup that aims to “filter the noise” out of the statistical approach to healthcare, says its cloud-based platform will replace the current platform used by the Michigan Breast Oncology Initiative (MiBOQI).
The 26-hospital Collaborative Quality Initiative (CQI) will implement ArborMetrix’s technology to improve quality, safety, outcomes, and effectiveness of breast cancer treatment across Michigan. Blue Cross Blue Shield is underwriting this effort.
“We enrolled almost every woman with breast cancer in Michigan,” says ArborMetrix CEO Brett Furst, noting that in addition to the 26 hospitals, MiBOQI also includes 420 physicians. “Our platform will run across virtually every oncology practice.”
The MiBOQI program is the first of its kind in the country, and Furst says ArborMetrix eventually wants to take it national. To push that goal forward, ArborMetrix is poised to announce a significant round of new funding later this month. ArborMetrix has also grown out of its current space and will soon be moving to a bigger office downtown in the hopes of drawing more talent.
“We’re growing really quickly,” Furst adds. “Our success in Michigan had led to us getting involved in initiative in other states like Pennsylvania, California, and Texas.”
Unlike guidelines for other medical conditions, protocols for breast cancer—which is the most frequently diagnosed cancer in Michigan women—often change due to new medications and other discoveries. The ArborMetrix platform and real-time dashboard will allow MiBOQI keep pace with best practices nationally, analyze data faster to measure clinical performance, improve breast cancer diagnosis and care, and ensure adherence to evidence-based guidelines.
“Evidence-based guidelines tell what to do in certain situations, but there aren’t many answers for the long haul,” Furst explains. “How do we do more with data and help doctors learn from one another? Our innovation was to provide tools to efficiently turn all this data into knowledge.”