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arXiv · 1712.07809

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
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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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Jin Wang, Javier Cabrera, Kwok-Leung Tsui, Hainan Guo, Monique Bakker, John B. Kostis. 2017-12-21. Predicting Surgery Duration from a New Perspective: Evaluation from a Database on Thoracic Surgery. https://arxiv.org/abs/1712.07809

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