An Ensemble Learning Approach to Improving Prediction of Case Duration for Spine Surgery: Algorithm Development and Validation.

ABSTRACT:

Background

Estimating surgical case duration accurately is an important operating room efficiency metric. Current predictive techniques in spine surgery include less sophisticated approaches such as classical multivariable statistical models. Machine learning approaches have been used to predict outcomes such as length of stay and time returning to normal work, but have not been focused on case duration.

Objective

The primary objective of this 4-year, single-academic-center, retrospective study was to use an ensemble learning approach that may improve the accuracy of scheduled case duration for spine surgery. The primary outcome measure was case duration.

Methods

We compared machine learning models using surgical and patient features to our institutional method, which

SUBMITTER: Gabriel RA 

PROVIDER: S-EPMC9912154 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature