2020
DOI: 10.1155/2020/3582796
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Clinical and Nonclinical Effects on Operative Duration: Evidence from a Database on Thoracic Surgery

Abstract: Background. Due to the high maintenance costs, it is critical to make full use of operating rooms (ORs). Operative duration is an important factor that guides research on surgery scheduling. Clinical effects, for example, surgery type, rationally influences operative duration. In this study, we also investigate whether the planning and scheduling decisions in ORs influence the operative duration. Methods. For our study, we collected and reviewed data on 2,451 thoracic operations from a large hospital in China.… Show more

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Cited by 9 publications
(4 citation statements)
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“…The shorter execution time in autonomous modes compared to manual and foot-operated modes is due to users focusing only on the main task while the robotic manipulator handles camera repositioning. Since a long operation time is associated with a high workload, the ability to shorten task duration leads to a lower mental workload [27]. The time out FoV resulted significantly lower (p-value < 0.01) in the autonomous modalities with a mean value of 12.43 ± 22.83 s and 79.30 ± 138.28 s for AM T and M M T and 31.32 ± 57.14 s and 121.15 ± 131.92 s for AM R and F M R respectively.…”
Section: Wire Chaser Task Resultsmentioning
confidence: 99%
“…The shorter execution time in autonomous modes compared to manual and foot-operated modes is due to users focusing only on the main task while the robotic manipulator handles camera repositioning. Since a long operation time is associated with a high workload, the ability to shorten task duration leads to a lower mental workload [27]. The time out FoV resulted significantly lower (p-value < 0.01) in the autonomous modalities with a mean value of 12.43 ± 22.83 s and 79.30 ± 138.28 s for AM T and M M T and 31.32 ± 57.14 s and 121.15 ± 131.92 s for AM R and F M R respectively.…”
Section: Wire Chaser Task Resultsmentioning
confidence: 99%
“…Common ML models used for procedure duration prediction include linear regression, 21,30,[32][33][34][35][36] tree-based algorithms such as regression trees, bagged trees, and random forests, [19][20][21]31,34,37 neural networks, 34 and Support Vector Machines (SVM). 20,37 Of the features that were selected (Table 2), Table 6 in Appendix III indicates that the expected duration feature has higher impact on the treebased models than on the linear regression models, while the procedure group feature is important for all models tested.…”
Section: Discussionmentioning
confidence: 99%
“…Thoracic anesthesia does not happen in a social vacuum [22]. Focusing on individual competence in thoracic anesthesia is insufficient [23].…”
Section: We Learn Together Day After Daymentioning
confidence: 99%