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Predicting Surgery Duration from a New Perspective: Evaluation from a Database on Thoracic Surgery

2017/12/21 by Jin Wang, Javier Cabrera, Wang, Jin +9
Medicine · #Applications (stat.AP) #Cardiac, Anesthesia and Surgical Outcomes #FOS: Computer and information sciences #Hospital Admissions and Outcomes #Surgical Simulation and Training

paper · pdf · doi:10.48550/arxiv.1712.07809

openalex publication_date 2017/12/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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 for surgeries in different positions in the day. CONCLUSIONS: Surgery duration was affected not only by clinical effects but also some non-clinical effects. Scheduling and allocation decisions significantly influenced surgery duration.

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