Predicting Surgery Duration from a New Perspective: Evaluation from a Database on Thoracic Surgery
Jin Wang, Javier Cabrera, Kwok-Leung Tsui, Hainan Guo, Monique Bakker,, John B. Kostis

TL;DR
This study analyzes how clinical and non-clinical factors, including scheduling and surgeon experience, influence thoracic surgery durations using regression models on hospital data.
Contribution
It introduces a comprehensive analysis of non-clinical effects on surgery duration, considering interactions and scheduling patterns in thoracic surgeries.
Findings
Surgery duration decreases with surgeon experience.
Scheduling more than four surgeries per day increases duration.
Surgery position in sequence affects duration and varies by surgeon.
Abstract
BACKGROUND: Clinical factors influence surgery duration. This study also investigated non-clinical effects. METHODS: 22 months of data about thoracic operations in a large hospital in China were reviewed. Linear and nonlinear regression models were used to predict the duration of the operations. Interactions among predictors were also considered. RESULTS: Surgery duration decreased with the number of operations a surgeon performed in a day (P<0.001). Also, it was found that surgery duration decreased with the number of operations allocated to an OR as long as there were no more than four surgeries per day in the OR (P<0.001), but increased with the number of operations if it was more than four (P<0.01). The duration of surgery was affected by its position in a sequence of surgeries performed by a surgeon. In addition, surgeons exhibited different patterns of the effects of surgery type…
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Taxonomy
TopicsCardiac, Anesthesia and Surgical Outcomes · Hospital Admissions and Outcomes · Surgical Simulation and Training
