Startup

Basys.ai grabs $2.4M for its prior authorization tech powered by Mayo Clinic’s data

Prior authorization, a fancy term for your doctor needing to gain approval from your health insurance company before doing

Basys.ai grabs $2.4M for its prior authorization tech powered by Mayo Clinic’s data

Prior authorization, a fancy term for your doctor needing to gain approval from your company before doing a medical procedure, has typically been a heavily manual process involving lots of steps, reviews and people having to work together.

Seeking approval from the insurance company is meant to prevent unnecessary procedures and keep healthcare costs ; however, the lengthy process of prior authorization often leads to delayed or even abandoned care. And the administrative costs associated account for between 20% and 34% of U.S. healthcare expenditures.

In an effort to fix this, the Centers for & Medicaid Services (CMS) issued a proposal in February designed to address how burdensome prior authorization is the healthcare system, calling for this process to join the digital world.

Some experts have said the CMS proposal paves the way for technology companies to introduce their solutions that will ultimately strengthen the way healthcare data is used.

One new company taking advantage is Basys.ai, which helps health plans and health systems adopt value-based care, starting with prior authorization. It was founded in early 2022 by Amber Nigam and Jie , who met while in Harvard's health data program.

Basys combines generative AI and deep learning to power its “engine,” which can automate up to 90% of the prior authorization requests for drugs and procedures at high accuracy, Nigam told TechCrunch. The platform also doesn't require sensitive data from insurance companies or doctors, thus reducing the typical integration time from up to a year down to weeks.

“The engine is trained extensive Joslin Diabetes Center and Mayo Clinic's longitudinal data of more than 10 million patients,” Nigam said. “This translates to flattening the cost curve for patients and reducing administrative burden by leveraging AI.”

In addition, by automating the encoding of payer policies, Basys can more quickly timelines with health plans at a rate of up to nine months faster than most of its competitors, of which Nigam said included companies like Cohere Health.

The company makes its commercial launch today, buoyed by $2.4 million pre- funding. Nina Capital led the round and was joined by a group of investors, including Eli Lilly (Lilly Ventures), Mayo Clinic, Two Lanterns Venture Partners, Ventures and Chaac Ventures.

Basys initially began selling to providers and had been bringing in revenue, but has since pivoted its business model to selling to health insurance companies. It is initiating pilots with two large payers in Massachusetts and Minnesota, Nigam said.

The company is also working on capturing patient outcomes through reducing readmission rates and determining the progression of the patient's disease has stopped or slowed down.

“We also make sure we have a lot of about the patients,” Nigam said. “Sometimes when you make decisions, it is not entirely based on one or two attributes; it's based on hundreds or thousands of attributes along with the understanding of the insurance company's policies. Once you match these policies with the patient information, then resolving a prior authorization request is more nuanced.”

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