What is it about?

Many hospitals encounter surgery cancelations for various reasons. We present a methodology applying data mining and simulation to optimize operating room (OR) scheduling in a urology department in West China Hospital. To the best of our knowledge, this is 1 of the first efforts to seek an optimal schedule solution based on cancelation risk of elective surgeries as well as OR allocation between elective and nonelective surgeries. First, chi-square test and random forest prediction modeling were used to predict potential elective surgeries with high cancelation risk, and the factors, including surgeon, number of days since admission of patient, first surgery or not, etc., that influence elective surgery cancelation were identified. Second, a simulation technology was designed to compare 7 different scheduling strategies. The results demonstrated that for elective surgery, cancelation rate low surgery first outperformed the others and increased the productivity of the ORs from 72% to 83%, while for nonelective surgery performed in a separate OR, there was no improvement because the supply was greater than necessary at present. However, in total, the selected strategies led to 7% higher productivity.

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Why is it important?

Operating room is a hospital's revenue and cost center and is closely linked with other key hospital resources. The operating performance of the OR is crucial for effective and efficient hospital management. However, at present, ORs in most hospitals at home and abroad are plagued by elective surgery cancelation, which negatively influences the hospitals, medical staff, patients, and their families. To address the problem of elective surgery cancelation and to improve the operating performance of the ORs in the urology department in WCH, this study build RF classification models to identify potential elective surgeries with high cancelation risk. Discrete event simulation techniques were used to perform and compare different surgical scheduling strategies.


Our study was based on actual data from the urology department in WCH; hence, the findings of this study may not be applicable to all departments and hospitals because of different circumstances. However, this study provides an alternative strategy or solution to improve the OR scheduling and management.

shuzhen zhao

Read the Original

This page is a summary of: A random forest and simulation approach for scheduling operation rooms: Elective surgery cancelation in a Chinese hospital urology department, The International Journal of Health Planning and Management, June 2018, Wiley,
DOI: 10.1002/hpm.2552.
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