Boston, Massachusetts-based Caresyntax has announced the close of a $100 million Series C funding round.
Caresyntax Closes $100 Million Funding Round
The funding round was led by San Francisco, California-based PFM Health Sciences, LP. Optum Ventures, Intel Capital, Lauxera Capital Partners, Vesalius Biocapital III, Arno Capital, and Rezayat Investments also participated in the funding round. Existing investors took part as well including IPF Partners, the Relyens Group, and Surgical.AI.
Caresyntax’s “digital surgery platform” uses proprietary software and artificial intelligence (AI) to analyze operating room data and provide insights to the care team and critical stakeholders. Caresyntax will use some of the funding to develop its AI analytics and expand its platforms.
OTW spoke with Caresyntax Founder and CEO Dennis Kogan about the uniqueness of the Caresyntax platform. “Our platform is unique in that it lives at the intersection of data collection and analysis. Some companies have solutions that enable them to collect real-life operating room data, and some are able to turn that data into actionable insights, but our platform is uniquely positioned to do both.”
Kogan continued, “We are also vendor agnostic and have a Patient Safety Organization designation, which encourages hospitals to utilize new technology and AI, like our digital surgery platform, without fear of litigation. This designation removes barriers for hospital partners related to legal concerns associated with video of adverse surgical events, encouraging broader adoption and creation of new, proprietary primary-source data assets.”
Hospital operating rooms suffered when the COVID-19 pandemic hit and many are reporting a surgical backlog. A backlog Caresyntax hopes to ameliorate with its technology.
Kogan remarked to OTW, “Our growth comes at a critical time for hospitals as they look to rebuild post-pandemic. From March to July 2020 alone, hospitals lost over $200 billion, and it could take years to work through the surgical backlog. Caresyntax can help hospitals address the COVID-19 backlog and increase hospital resilience by making their operating rooms as efficient and effective as possible through a data-first strategy.”

Discussion
This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?
Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.
We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.
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