“Our ambition here isn't to automate humans away,” says Rao. While the main users are patients, the main customers Abridge hopes to attract are health systems and health insurers, who are willing to pay for the use of a platform that could help improve the long-term outcomes for their patients. That is the next step for Abridge, using nudges to get patients to take the next steps-fill their prescriptions, schedule a follow-up visit, get their imaging done. “The most important part of the health journey often happens between visits,” says Rao. The company has 15 full-time employees and plans to use the funding to expand on the engineering and product side to continue developing new features. The algorithms were developed using a de-identified and consented research dataset from UPMC, which is also an investor, and Abridge continues to work with machine learning professors at Carnegie Mellon. The company’s ties to both institutions still run deep. Another big challenge was being able to interpret varying degrees of microphone quality and people talking over each other.Ībridge was founded in 2018, but the cofounders met a couple years earlier, when Konam was pursuing a master's in robotics at Carnegie Mellon University in Pittsburgh, where Rao was a cardiologist at the University of Pittsburgh Medical Center. Privacy and security of protected health information was paramount to the platform design, says Konam. Abridge has also partnered with the drug pricing company GoodRx ( which went public in September) to include information about available coupons next to the name of prescriptions. If youve got another answer, it would be kind of you to add it to our crossword dictionary. Try to find some letters, so you can find your solution more easily. The company’s algorithms had to be able to recognize complicated names of prescriptions, such as atorvastatin for cholesterol or lisinopril for hypertension, on the first try. 1 Answer (s) for the Clue Abridge, perhaps.
What Abridge has built is more complicated than the technology that underpins voice-controlled systems like Alexa or Siri, since those devices have corrections through voice commands. “Because that conversation is upstream of all the diagnostics, therapeutics, labs and other services.” “Our thesis has always been that we should focus on the conversation between a patient and the doctor,” says Konam. The technology skips over discussions of topics like the weather and only focuses on the medically relevant parts of the conversation. Konam and his team spent two years developing algorithms that could understand medical jargon, surface key terms and detect next steps. Google,” where patients often turn to the internet to get answers to pressing medical questions, Abridge has defined over 400,000 medical terms in easy to understand language, pulling from resources like the Mayo Clinic and the National Library of Medicine.