Intraoperative remaining surgery duration estimation to improve operating room scheduling

The creation and evaluation of an estimation system

Master thesis (2020)

Authors

K.N.M.M.H. Osman Mechanical Engineering

Contributors

J.J. van den Dobbelsteen Medical Instruments & Bio-Inspired Technology - Mechanical, Maritime and Materials Engineering (supervisor 1)
B.H.W. Hendriks Medical Instruments & Bio-Inspired Technology - Mechanical, Maritime and Materials Engineering (supervisor 2)
M.C. Goorden RST/Biomedical Imaging - AS (supervisor 2)
A.C.P. Geudon (supervisor 1)
Faculty
Mechanical Engineering
Copyright: © 2020 Karim Osman
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Published Date

16-07-2020

Language

English

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Faculty

Mechanical Engineering

Abstract

One of the main elements for creating an optimal operating room schedule is an accurate surgery duration estimation. Currently, this estimation is only done preoperatively. However, multiple factors during the surgery itself could influence the duration, for example bleeding. Literature showed the possibility of intraoperatively estimating a surgery duration based on surgical progress. However, one of the main concerns was the usability of such a system in the operating room workflow. Therefore, this research was focused on two parts: (1) the creation of an automatic intraoperative remaining surgery duration estimation system and (2) the evaluation of such a system for the operating room workflow. Two types of surgeries were used for the estimation, the Laparoscopic Cholecystectomy and the Total Laparoscopic Hysterectomy. The estimation was created using multiple statistical regressor methods, such as linear regression and random forest, and progress-based methods based on the nearest-neighbors algorithm and Dynamic Time Warping method. The evaluation was done on two levels: the system level based on the error of the estimation, and the operating room workflow based on surgical data from 2016 to 2019 and interviews with the operating room program coordinators. Results showed that an intraoperative remaining surgery duration estimation system based on surgical phases was able to re-estimate the duration with an error of about 10 minutes, an acceptable error for the operating room workflow. Moreover, the third quarter of the surgery showed to be the essential part where an accurate estimation is needed. Furthermore, an automatic system showed additional benefits such as being unbiased, continuous, and reducing unnecessary disturbance in the operating rooms. Overall, this research showed that an intraoperative remaining surgery duration system based on surgical phases is promising for the operating room workflow. Future research is needed to understand how to implement such a system in the operating room workflow.