A Quantile Regression Approach to Estimating the Distribution of Anesthetic Procedure Time during Induction

Hsin-Lun Wu, Wen-Kuei Chang, Ken-Hua Hu, Richard M Langford, Mei-Yung Tsou and Kuang-Yi Chang

PLOS ONE, 2015, vol. 10, issue 8, 1-10

Abstract: Although procedure time analyses are important for operating room management, it is not easy to extract useful information from clinical procedure time data. A novel approach was proposed to analyze procedure time during anesthetic induction. A two-step regression analysis was performed to explore influential factors of anesthetic induction time (AIT). Linear regression with stepwise model selection was used to select significant correlates of AIT and then quantile regression was employed to illustrate the dynamic relationships between AIT and selected variables at distinct quantiles. A total of 1,060 patients were analyzed. The first and second-year residents (R1-R2) required longer AIT than the third and fourth-year residents and attending anesthesiologists (p = 0.006). Factors prolonging AIT included American Society of Anesthesiologist physical status ≧ III, arterial, central venous and epidural catheterization, and use of bronchoscopy. Presence of surgeon before induction would decrease AIT (p

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0134838

DOI: 10.1371/journal.pone.0134838

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