1School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China 2School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
[Objective] This study aims to optimize the management of large hospital operating rooms with the help of data analytics. [Objective] We collected about fifty thousand surgical cases from one large hospital in China. Then, we conducted regression analysis for correlation of surgical indicators, cluster analysis and association rule mining for resource usage, as well as the time series forecasting to predict the number of surgical cases. Finally, we discussed optimization strategies for operating rooms. [Results] The duration of 75% surgical procedures showed significant ties with other indicators. The FP-Growth algorithm with minimum confidence of 0.85 identified reliable patterns of resource usage. The accuracy of time series forecasting was increased by at least 37.5% due to the use of weekly numbers of surgical procedures. [Limitations] We did not link the operating room dataset with records from other medical information systems. Therefore, the proposed method might not work for other hospital departments. Meanwhile, our method needs to be examined with data from other hospitals. [Conclusions] This study could help to optimize the large hospital operating rooms.
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