• Franklin Dexter, Richard H Epstein, Javier Campos, and Richard P Dutton.
• From the *Division of Management Consulting, Department of Anesthesia, University of Iowa, Iowa City, Iowa; †Department of Anesthesiology, University of Miami, Miller School of Medicine, Miami, Florida; ‡Department of Anesthesia, University of Iowa, Iowa City, Iowa; and §Anesthesia Quality Institute, Schaumburg, Illinois.
• Anesth. Analg. 2016 Nov 1; 123 (5): 1297-1301.

BackgroundIn order to provide guidance to organizations considering elective weekend surgical case scheduling, we analyzed data from the American Society of Anesthesiologist's Anesthesia Quality Institute. We determined the US anesthesia workload on Saturdays and Sundays.MethodsThe American Society of Anesthesiologist's Anesthesia Quality Institute data were from all US anesthesia groups that submitted cases to the National Anesthesia Clinical Outcomes Registry for 2013. For each of the N = 2,075,188 cases, we identified the local date and time of the start of anesthesia care and the duration of anesthesia care. Anesthesia workload was measured as the time from the start to the end of continuous anesthesia care. Because elective cases are rarely scheduled on Sundays, we considered the difference in workload between Saturday and Sunday to estimate elective case scheduling. This difference would be an overestimate if some patients' scheduled cases were postponed from Friday to Saturday. Data are reported as mean ± standard error; N = 13 four-week periods.ResultsThe difference in the anesthesia minutes between Saturdays versus Sundays 7:00 AM to 2:59 PM (ie, elective caseload) represented just 0.38% ± 0.02% of the total minutes nationwide; Saturday 1.57% ± 0.03% versus Sunday 1.19% ± 0.02%. The P < .00001 comparing the 0.38% with 1.0% and, also, with 0.5% (upper 99% confidence interval = 0.42%).ConclusionsThe imputed Saturday elective schedule represents a tiny percentage of overall anesthetic workload nationwide. Saturday elective surgery is currently an uncommon practice in the United States. Based on this prior knowledge, organizations considering changes to their current scheduling strategies should perform a thorough statistical analysis of their local workload prior to implementation and apply evidence-based criteria to guide their decision-making process.

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