Improving Operating Room Efficiency: Machine Learning Approach to Predict Case-Time Duration.

ABSTRACT:

Background

Accurate estimation of operative case-time duration is critical for optimizing operating room use. Current estimates are inaccurate and earlier models include data not available at the time of scheduling. Our objective was to develop statistical models in a large retrospective data set to improve estimation of case-time duration relative to current standards.

Study design

We developed models to predict case-time duration using linear regression and supervised machine learning. For each of these models, we generated an all-inclusive model, service-specific models, and surgeon-specific models. In the latter 2 approaches, individual models were created for each surgical service and surgeon, respectively. Our data set included 46,986 scheduled operations performed at

SUBMITTER: Bartek MA 

PROVIDER: S-EPMC7077507 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature