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DeepScribe, an AI-powered medical transcription platform, has raised $30 million in Series A funding led by Nina Achadjian at Index Ventures, with participation from Scale.ai CEO Alex Wang, Figma CEO Dylan Field and existing investors Bee Partners, Stage 2 Capital and 1984 Ventures. The company’s latest round of funding follows its $5.2 million seed round announced in May 2021. DeepScribe was founded in 2017 by Akilesh Bapu, Matthew Ko and Kairui Zeng with the aim of unburdening doctors from tedious data entry and allowing them to focus on their patients.

In 2019, DeepScribe launched its ambient voice AI technology that summarizes natural patient-physician conversations. The idea for DeepScribe was prompted by Bapu and Ko’s own experiences. Bapu’s father was an oncologist and he saw the toll that documentation had on his father’s work/life balance. On the other hand, Ko saw how the burden of clinical documentation was impacting patients’ perception of care when he was the care coordinator for his mother when she was diagnosed with breast cancer.

After being frustrated with the care his mother was receiving, Ko turned to Bapu and his father for help. The pair then began to understand the importance of clinical documentation and realized that recent breakthroughs in artificial intelligence and natural language processing were not being used to remedy the situation. They then decided to create a platform that would address the problem.

“After researching products in the space, we wondered why with over 75% of providers using documentation tools in the space, they were still spending nearly half their day writing notes,” Ko told TechCrunch in an email. “After testing the products, our thesis was that the existing products in the space were not solving the problem, as they still required the physician to summarize the conversation. Speech-to-text solutions were only capable of translating exactly what you say to text on a computer screen. What doctors wanted and what would really solve the problem was an ambient AI that would be able to intelligently understand and summarize a natural patient conversation. With this insight, we set out to build what is now DeepScribe, the world’s first ambient AI scribe.”

Once a physician starts the application, DeepScribe records, summarizes and integrates the conversation into the physician’s health record system of choice. The application records patient exams while it listens and prepares clinical notes. DeepScribe then uploads the notes directly into the fields of Electronic Health Records (EHR), enabling physicians to review and sign their fully prepared notes in the appropriate EHR fields.

The application is compatible with small talk and only includes the medically relevant information in the conversation. The company also notes that the AI-scribe continuously gets smarter by listening and learning about a physician’s conversation style, preferred phrasing and writing preferences.

Over the past 18 months, DeepScribe has scaled to more than 400 physicians around the United States and processed over half a million patient-physician conversations. DeepScribe says its platform saves physicians an average of three hours a day and costs around one-sixth the cost of human medical scribes. To date, the company has saved physicians over 2.5 million minutes of documentation. In terms of reliability, DeepScribe says physicians encounter less than one correction per note on average after 20 days of usage.

The company says this latest investment will accelerate DeepScribe’s growth, as it plans to continue to improve and transform medical documentation workflows and healthcare overall. DeepScribe aims to deploy its technology to multiple large health systems, grow its engineering team and get its AI in the hands of more physicians.

“While there are many things on our roadmap, what excites us the most are the possibilities outside of pure summarization,” Ko said. “We believe that voice will be the building blocks for the future of medicine and holds the ability to transform the diagnosis and treatment of care as we know it. We hope to leverage the data that we are harvesting through the delivery of our service to go beyond providing efficiencies for the physician and to begin improving outcomes for patients.”

Source: New feed

2022-01-12T17:26:13+00:00
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