Tampa General Hospital (TGH) in the US has launched Microsoft’s ambient listening technology for nurses, integrated into Epic’s Rover mobile application.
The initiative seeks to alleviate the administrative workload on nurses, with research indicating that up to 15% of their shifts can be consumed by documentation tasks.
This new solution, designed specifically for bedside nurses, represents TGH’s ongoing efforts to leverage AI to improve productivity, enhance job satisfaction, and elevate patient care quality.
Tampa General chief nursing executive and executive vice-president Wendi Goodson-Celerin said: “Our guiding philosophy has always been to put our team members first, so they feel engaged, supported and empowered to show up at their best for our patients.
“Microsoft's ambient listening technology can give nurses back hours of time per shift that they'd ordinarily spend manually entering data into a computer, and the research shows that this is time they would prefer to spend at the bedside with their patients, upskilling newer nurses and honing their craft.”
Similar to DAX Copilot, which is now part of Microsoft Dragon Copilot and was rolled out to more than 500 TGH-affiliated physicians in June 2024, the technology for nurses captures patient details such as observations, symptoms and experiences, and converts them into specialised clinical summaries within seconds.
This allows nurses to dedicate more time to direct patient care, mentor future nursing staff, and pursue professional development.
TGH expects that within the initial months of implementation, the technology will improve care coordination, reduce charting time, and minimise delays between patient assessments and documentation.
Tampa General chief nursing informatics officer Amit Patel said: “When approaching the rollout of ambient technology for nurses, we took a hard look at how we could use existing technology in new ways to drive the most meaningful impact – both for our team members and for patients.”
In April 2025, TGH implemented Milagro's AI-powered coding platform, resulting in significant improvements in surgical coding and reimbursement processes.
