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Adding Examples to the ASA-Physical Status Classification Improves Correct Assignment to Patients

2017·293 Zitationen·Anesthesiology
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293

Zitationen

7

Autoren

2017

Jahr

Abstract

BACKGROUND: Despite its widespread use, the American Society of Anesthesiologists (ASA)-Physical Status Classification System has been shown to result in inconsistent assignments among anesthesiologists. The ASA-Physical Status Classification System is also used by nonanesthesia-trained clinicians and others. In 2014, the ASA developed and approved examples to assist clinicians in determining the correct ASA-Physical Status Classification System assignment. The effect of these examples by anesthesia-trained and nonanesthesia-trained clinicians on appropriate ASA-Physical Status Classification System assignment in hypothetical cases was examined. METHODS: Anesthesia-trained and nonanesthesia-trained clinicians were recruited via email to participate in a web-based questionnaire study. The questionnaire consisted of 10 hypothetical cases, for which respondents were first asked to assign ASA-Physical Status using only the ASA-Physical Status Classification System definitions and a second time using the newly ASA-approved examples. RESULTS: With ASA-approved examples, both anesthesia-trained and nonanesthesia-trained clinicians improved in mean number of correct answers (out of possible 10) compared to ASA-Physical Status Classification System definitions alone (P < 0.001 for all). However, with examples, nonanesthesia-trained clinicians improved more compared to anesthesia-trained clinicians. With definitions only, anesthesia-trained clinicians (5.8 ± 1.6) scored higher than nonanesthesia-trained clinicians (5.4 ± 1.7; P = 0.041). With examples, anesthesia-trained (7.7 ± 1.8) and nonanesthesia-trained (8.0 ± 1.7) groups were not significantly different (P = 0.100). CONCLUSIONS: The addition of examples to the definitions of the ASA-Physical Status Classification System increases the correct assignment of patients by anesthesia-trained and nonanesthesia-trained clinicians.

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Healthcare Technology and Patient MonitoringArtificial Intelligence in Healthcare and EducationCardiac, Anesthesia and Surgical Outcomes
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