Dexter F, Epstein RH, Campos J, Dutton RP. US National Anesthesia Workload on Saturday and Sunday Mornings.
Anesth Analg 2017;
123:1297-1301. [PMID:
27607479 DOI:
10.1213/ane.0000000000001447]
[Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND
In 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.
METHODS
The 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.
RESULTS
The 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%).
CONCLUSIONS
The 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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