Can machine learning optimize the efficiency of the operating room in the era of COVID-19?

Can machine learning optimize the efficiency of the operating room in the era of COVID-19?

Can J Surg 2020;63(6):E527-E529 | PDF | Appendix

Natasha Rozario; Duncan Rozario, MD

Summary

The cancellation of large numbers of surgical procedures because of the coronavirus disease 2019 (COVID-19) pandemic has drastically extended wait lists and negatively affected patient care and experience. As many facilities resume clinical work owing to the currently low burden of disease in our community, we are faced with operative booking protocols and procedures that are not mathematically designed to optimize efficiency. Using a subset of artificial intelligence called “machine learning,” we have shown how the use of operating time can be optimized with a custom Python (a high-level programming language) script and an open source machine-learning algorithm, the ORTools software suite from the Google AI division of Alphabet Inc. This allowed the creation of customized models to optimize the efficiency of operating room booking times, which resulted in a reduction in nursing overtime of 21% — a theoretical cost savings of $469 000 over 3 years.


Accepted Oct. 14, 2020

Affiliations: From the Department of Mathematics, University of Waterloo, Waterloo, Ont. (N. Rozario); and the Oakville Trafalgar Memorial Hospital, Oakville, Ont. (D. Rozario).

Competing interests: None declared.

Contributors: Both authors contributed substantially to the conception, writing and revision of this article and approved the final version for publication.

DOI: 10.1503/cjs.016520

Correspondence to: N. Rozario, Faculty of Mathematics, University of Waterloo, 200 University Ave W, Waterloo ON N2L 3G1, mail@natasharozario.com