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ECONOMICS, EDUCATION, AND POLICY

Can the Attending Anesthesiologist Accurately Predict the Duration of Anesthesia Induction?

Jan Ehrenwerth, MD^*, Alejandro Escobar, MD^*, Elizabeth A. Davis, RDCS^*, Gail A. Watrous, RN^*, Gene S. Fisch, PhD, Zeev N. Kain, MD, MBA^*, and Paul G. Barash, MD^*

From the *Department of Anesthesiology, and General Clinical Research Center, Yale University School of Medicine and Yale-New Haven Hospital, New Haven, Connecticut.

Address correspondence to Paul G. Barash, MD, Department of Anesthesiology, Yale University School of Medicine, 333 Cedar Street, PO Box 208051, New Haven, CT 06520-8051. Address e-mail to paul.barash{at}yale.edu.

Abstract

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.