Regard serves as a “medical co-pilot” for busy doctors – TechCrunch

Legacy healthcare software systems are often complicated and cumbersome for providers to use, reducing time spent with patients. That is why Concerning (formerly HealthTensor) has developed a platform to help diagnose common medical conditions, such as heart failure, COVID-19, anxiety and depression. The Los Angeles-based startup announced today that it has raised $15.3 million in Series A funding led by Calibrate Ventures and Foundry Group. Returning investors TenOneTen Ventures and Susa Ventures also participated, along with new backers Brook Byers of Byers Capital and Drew Houston.

This brings the total raised by Regard since its inception in 2017 to $20.5 million. The Series A capital will be used to increase the number of Regard customers. It is currently used by 15 hospitals and under contract with 84 others.

Co-founder and CEO Eli Ben-Joseph told TechCrunch that he and Regard’s other two co-founders, Nate Wilson and Thomas Moulia, were applying to medical school when “we each realized there was a lot disgruntled doctors. Medicine and healthcare were incredibly behind in terms of the software they had access to. As a result, they decided they could make a bigger impact on the medical industry by creating software that helps doctors.

The founders point out a Medscape study this shows that 47% of physicians in all fields said they felt burnt out in the past year. This is partly due to the COVID-19 pandemic, but of course physicians also have a great workout, with those in outpatient clinics reporting the highest proportion of burnout. Therefore, more healthcare workers leave the field.

Regard wants to help with what he describes as a “medical co-pilot” who can recognize about 50 common medical conditions, including heart failure, kidney disease, pneumonia, COVID-19, anxiety and depression, respiratory failure and sepsis, using an algorithm developed by a team of doctors and engineers. It is designed to complement patients’ medical records and save them time in their note-taking process.

“We strongly believe that the physician of the future is overwhelmingly supported and enabled by technology rather than hindered by it,” Ben-Joseph said. “We see a world where most clinical decisions are made by computer and are data driven. For medicine to eventually become personalized, it will need to be supported by software that enables a clinician’s medical workflow.

Ben-Joseph said the algorithm was built using pre-approved customer data and verified by doctors before being rolled out to customers. “Our internal bar is that an algorithm should be at least 90% accurate before it goes live,” he added. “That is determined by our team of doctors. Ninety percent accurate means we limit noise while still having the potential to surface diseases that can have serious clinical implications if ignored.

Regard has partnered with Epic and Cerner, two of the largest electronic medical record (EMR) providers in the United States. Ben-Joseph compares the model to Apple’s App Store – Regard is found in Epic’s and Cerner’s app stores, allowing integration with potential customers. In return, Regard has a revenue sharing agreement with the two EMRs.

For Regard customers, its algorithms work by aggregating and combing through their electronic health records. The company says its technology has been used on 30,000 patients so far and has diagnosed more than 420,000 medical conditions that might otherwise have been missed by doctors.

In terms of competition, Regard faces products made by Nuance and 3M, but Ben-Joseph said these focus on optimizing revenue and billing, and don’t help patient care. “Our product was designed from the ground up with physician workflow in mind and as such we are seeing increased efficiency and revenue across the board.”

In a prepared statement, Mark Laret, Regard board member and former CEO of UCSF Health, said, “Regard addresses two critically important issues in healthcare: it improves the accuracy of clinical documentation, while simultaneously reducing patient workload. I expect this software to become ubiquitous in the healthcare system as providers and hospitals want and need it. »


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