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

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 i...

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Bibliographic Details
Published in:PloS one 2015-08, Vol.10 (8), p.e0134838-e0134838
Main Authors: Wu, Hsin-Lun, Chang, Wen-Kuei, Hu, Ken-Hua, Langford, Richard M, Tsou, Mei-Yung, Chang, Kuang-Yi
Format: Article
Language:English
Subjects:
Airway management
Anesthesia
Anesthesia - methods
Anesthesiology
Anesthesiology - education
Bronchoscopy
Catheterization
Efficiency
Health aspects
Hospitals
Humans
Influence
Information processing
Injectable anesthetics
Internship and Residency
Intubation
Management
Medical personnel
Medicine
Monte Carlo simulation
Operating rooms
Patients
Quantiles
Regression Analysis
Regression models
Retrospective Studies
Statistical analysis
Studies
Surgeons
Surgery
Surgical Procedures, Operative
Time Factors
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Summary: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 < 0.001). Types of surgery also had significant influence on AIT. Quantile regression satisfactorily estimated extra time needed to complete induction for each influential factor at distinct quantiles. Our analysis on AIT demonstrated the benefit of quantile regression analysis to provide more comprehensive view of the relationships between procedure time and related factors. This novel two-step regression approach has potential applications to procedure time analysis in operating room management.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0134838