Why the study?
Can attending anesthesiologists accurately predict the duration of anesthesia induction?
Can attending anesthesiologists accurately predict the duration of anesthesia induction?
Anesthesiologists can predict anesthesia induction time well in aggregate, but individual case predictions are often inaccurate, especially in complex cases.
Individual induction time predictions lack accuracy despite aggregate correlation; leaves open whether refined models or training can improve per-case precision.
In Brief In a prospective, observational study, the attending anesthesiologists’ prediction of anesthesia release time (ART) of the patient to the surgical team was highly correlated with actual ART (r = 0.77; P ≤ 0.001). However, this was true only in the aggregate (n = 1265 patients). Indeed, offsetting degrees of under- and over-predicting (24% each) reduced accuracy to only 53% per individual case. For example, under-prediction was associated with ASA physical status IV, a regional anesthetic technique, age >65 yr, and the use of invasive hemodynamic monitoring (P = 0.006). In fact, as the degree of case difficulty increased, the correlation coefficient between predicted and actual ART decreased, indicating a poor predictive value with more difficult inductions (r = 0.82 to r = 0.44; P ≤ 0.004). We conclude that knowledge of the presence of specific factors that lead to inaccurate predictions of time required for induction of anesthesia may enhance the accuracy of the operating room schedule. IMPLICATIONS: For a large group of patients, attending anesthesiologists perform well in predicting the time required before releasing a patient to the surgical team after induction of anesthesia. However, for a given patient the accuracy is only 53%.
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Ehrenwerth et al. (2006) studied this question.
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