Illustrative scenario. This is a composite for planning. It is not a report of a specific peer-reviewed trial.
This is an illustrative composite, not a trial report. The rounding list shows who is at higher fall risk and which precautions are already ordered, so the nurse does not hunt through the chart in the doorway. It is a prompt, not a new score the nurse must obey. Alert fatigue is part of the design problem: if every patient is flagged, the list has failed. No fall-rate reduction is claimed.
Clinical setting
Adult medical and surgical wards during scheduled bedside rounds, using a fall-risk assessment the hospital already documents.
Tools and vendors
EHR fall-risk score
Bedside rounding list
Source
Illustrative composite, Madical AI Use · Aug 3, 2026 · Year 2026
This is an illustrative composite, not a trial report. Late in the afternoon a model estimates how heavy the next shift will be from the current census, planned admissions, and recent acuity. The charge nurse uses it as one input to ask the staffing office for help. It does not cut a shift by itself, and it does not replace the legal and contractual staffing rules of the hospital. No savings percentage is stated.
The Targeted Real-time Early Warning System (TREWS) watches the electronic record and asks a clinician to confirm or dismiss a possible sepsis alert. It was studied prospectively across five hospitals, not as a silent background score. The published association depends on a person acting on the alert within a few hours. It does not diagnose sepsis by itself.
The Epic Sepsis Model is a proprietary score switched on in a large number of U.S. hospitals. Researchers at Michigan Medicine compared it with sepsis in their own hospitalizations, instead of relying on the vendor performance sheet. The paper is included here because a familiar model can still fail local validation. Widespread deployment is not the same thing as demonstrated usefulness.