Multiservice machine learning models enhance surgical resource planning.

Multiservice machine learning models were developed to predict postsurgical length of stay (LOS) and discharge disposition at the time of case posting. An analysis of 63,574 patients showed the LOS model achieved an area under the curve (AUC) of 0.81. Incorporating relative value units and historical LOS improved prediction accuracy for both short and prolonged stays by up to 9%. These models aim to improve resource allocation and support timely discharge planning for elective surgeries.