To reduce the administrative workload for physicians, Ambience Healthcare has launched an AI-driven platform designed to streamline routine clinical processes, according to the company’s announcement.
The technology integrates directly into electronic health records (EHRs) to free up time for clinicians, allowing them to focus more on patient care instead of paperwork. Ambience's platform automates pre-charting, offers real-time AI scribing, and assists with insurance billing codes. These features have been implemented in approximately 40 large healthcare institutions, including UCSF Health, Memorial Hermann Health System, and St. Luke’s Health System, among others, according to a report by MIT News.
Notably, clinicians using the Ambience system are reported to save between two to three hours daily on documentation activities, experience lower burnout levels, and are able to foster higher-quality patient relationships, “We build co-pilots to give clinicians AI superpowers," Ambience CEO Mike Ng MBA ’16 told MIT News, highlighting the transformative impact of the platform on healthcare delivery.
This innovation comes at a time when clinicians typically spend only 27 percent of their workday on direct patient care, as documentation and administrative tasks occupy much of their schedules. With the introduction of Ambience's AI platform, this situation may change.
The founders, Mike Ng and Nikhil Buduma, were inspired by their personal and professional experiences with the healthcare system's inefficiencies, Ng sustained a significant back injury and was shocked by the time spent on non-patient-facing activities by healthcare professionals, while Buduma, who had immigrated from India and dealt with persistent health issues, observed the struggles his family faced with the U.S. medical system amid these experiences, they sharpened their focus on utilizing AI to refine healthcare practices, “There’s a really exciting opportunity to make expertise at some of the major academic medical centers more democratized across the U.S.," Ng sees this as a pathway to scaling specialist knowledge through an AI-infrastructure layer, especially as these models evolve in clinical intelligence, as he told MIT News.
