Protocol for the perioperative outcome risk assessment with computer learning enhancement (Periop ORACLE) randomized study.

ABSTRACT: Background: More than four million people die each year in the month following surgery, and many more experience complications such as acute kidney injury. Some of these outcomes may be prevented through early identification of at-risk patients and through intraoperative risk mitigation. Telemedicine has revolutionized the way at-risk patients are identified in critical care, but intraoperative telemedicine services are not widely used in anesthesiology. Clinicians in telemedicine settings may assist with risk stratification and brainstorm risk mitigation strategies while clinicians in the operating room are busy performing other patient care tasks. Machine learning tools may help clinicians in telemedicine settings leverage the abundant electronic health data available in the perio

SUBMITTER: Fritz B 

PROVIDER: S-EPMC10397896 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature