- Nuance’s automated clinical documentation product embedded in the Epic electronic health record is now generally available to provider customers, the Microsoft-owned technology company announced Thursday.
- The Dragon Ambient eXperience Copilot records doctor-patient conversations and drafts notes directly in Epic’s mobile app for physician review. Nuance first announced over the summer that the scribe would be integrated into Epic, one of the largest EHR vendors in the country.
- More than 150 health systems, hospitals and medical centers are set to deploy the DAX Copilot system embedded with Epic, according to Nuance. Those include Rhode Island hospital operator Lifespan Health and North Carolina academic medical system UNC Health.
Clinical documentation has become a popular use case for generative artificial intelligence in healthcare, with a number of technology companies like Amazon, Oracle and NextGen Healthcare unveiling their own products last year.
Generative AI, which can create new content like text or images, could lessen the amount of time clinicians spend recording patient visits and reduce fatigue, technology developers say.
Providers have long reported that they spend hours a day on EHR-related administrative tasks, often cutting into their time with patients and into after-work hours. The growing burden of administrative tasks is sometimes linked to provider burnout, a problem that spiked during the COVID-19 pandemic.
Nuance, which was acquired by Microsoft for nearly $20 billion in 2022, said DAX users cut the amount of time spent on clinical documentation by 50%, allowing them to save time per visit and add additional appointments.
Healthcare executives have shown interest in adopting generative AI tools, especially products that could enhance operational efficiency like documentation, communication with patients or workflow automation, according to a recent survey by Klas Research.
Though relatively few organizations currently use the tools, more than half surveyed said they were looking to implement or buy them within the next year.
But some experts have raised concerns about a too-rapid deployment of generative AI technologies in healthcare, citing concerns about the risk of errors and who would be accountable when mistakes occur. Accuracy and reliability topped the list of potential challenges in the Klas survey.