Can AI Scheduling Actually Reduce Burnout and Improve Safety?
By FairShare Team · · 3 min read
Most claims about scheduling software and burnout are anecdotal. A 2025 study in the peer-reviewed Ochsner Journal is one of the few to actually measure it — and it measured something more specific than satisfaction: patient safety.
In May 2019, the Department of Anesthesiology at Ochsner Health in New Orleans replaced its manual, spreadsheet-based scheduling process with an algorithm-driven system built from more than 400 scheduling rules developed by the department's own steering committee. Researchers then compared data from before and after implementation across three measures: physician satisfaction, vacation-request approval rates, and — notably — intraoperative transitions of care, a recognized patient-safety metric, since handoffs between clinicians mid-case are a known point of risk.
What changed after go-live
Six months after go-live, physician satisfaction scores rose, vacation approvals increased, and the department recorded over 1,000 fewer intraoperative transitions of care compared with the prior scheduling approach. In other words, a scheduling change that reduced burnout symptoms and improved reported work-life balance also happened to reduce a specific, measurable patient-safety risk.
That combination is worth underlining: this isn't a study claiming softer, harder-to-verify wellness benefits. It's measuring something concrete — who's handing off a case to whom, and how often — and finding that fairer, smarter scheduling moved that number in the right direction alongside physician satisfaction.
It also lines up with a related 2022 finding presented at the ASA's ADVANCE Business Event, where an AI-based scheduling system was shown to grant more vacation days, reduce ungranted vacation requests, and improve physician engagement scores during COVID-19 ICU staffing surges — using the same underlying idea: fair, transparent, rules-based scheduling beats an Excel sheet and goodwill. That's the premise behind FairShare's scheduling and coverage tools.
Sources
- Sumrall WD, Oury JV, Gilly GM. Enhancing Physician Satisfaction and Patient Safety Through an Artificial Intelligence–Driven Scheduling System in Anesthesiology. Ochsner Journal. 2025;25(1):44–49.
- American Society of Anesthesiologists, ADVANCE 2022 press release.