• Karuna Wongtangman, Omid Azimaraghi, Jeffrey Freda, Fran Ganz-Lord, Peter Shamamian, Alexandra Bastien, Parsa Mirhaji, Carina P Himes, Samuel Rupp, Susan Green-Lorenzen, Richard V Smith, Elilary Montilla Medrano, Preeti Anand, Simon Rego, Salimah Velji, and Matthias Eikermann.
• Department of Anesthesiology, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA; Department of Anesthesiology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand. Electronic address: kwongtangm@montefiore.org.
• J Clin Anesth. 2022 Dec 1; 83: 110987110987.

ObjectiveAvoidable case cancellations within 24 h reduce operating room (OR) efficiency, add unnecessary costs, and may have physical and emotional consequences for patients and their families. We developed and validated a prediction tool that can be used to guide same day case cancellation reduction initiatives.DesignRetrospective hospital registry study.SettingUniversity-affiliated hospitals network (NY, USA).Patients246,612 (1/2016-6/2021) and 58,662 (7/2021-6/2022) scheduled elective procedures were included in the development and validation cohort.MeasurementsCase cancellation within 24 h was defined as cancelling a surgical procedure within 24 h of the scheduled date and time. Our candidate predictors were defined a priori and included patient-, procedural-, and appointment-related factors. We created a prediction tool using backward stepwise logistic regression to predict case cancellation within 24 h. The model was subsequently recalibrated and validated in a cohort of patients who were recently scheduled for surgery.Main Results8.6% and 8.7% scheduled procedures were cancelled within 24 h of the intended procedure in the development and validation cohort, respectively. The final weighted score contains 29 predictors. A cutoff value of 15 score points predicted a 10.3% case cancellation rate with a negative predictive value of 0.96, and a positive predictive value of 0.21. The prediction model showed good discrimination in the development and validation cohort with an area under the receiver operating characteristic curve (AUC) of 0.79 (95% confidence interval 0.79-0. 80) and an AUC of 0.73 (95% confidence interval 0.72-0.73), respectively.ConclusionsWe present a validated preoperative prediction tool for case cancellation within 24 h of surgery. We utilize the instrument in our institution to identify patients with high risk of case cancellation. We describe a process for recalibration such that other institutions can also use the score to guide same day case cancellation reduction initiatives.Copyright © 2022. Published by Elsevier Inc.

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