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Predicting Hospital Length of Stay in Orthopedic Trauma Patients Using Fracture‐Specific Machine Learning Models: A Multicenter Retrospective Prediction‐Modeling Study

P. Marouzi Amir Ahmadi Seyyedeh Fatemeh Mousavi Baigi M. Ebrahimzadeh S. Tabatabaei Masomeh Sarbaz Khalil Kimiafar

Sep 2026 · Health Science Reports · Vol 9 · 0 citations · 46 references

Medicine

TL;DR

This study aimed to develop and validate fracture‐specific machine learning models for predicting short vs. long hospital stay across fracture types and the limitations of conventional approaches.

Abstract

Hospital length of stay (LOS) is a key indicator for resource allocation, bed management, and discharge planning in orthopedic trauma care. Given the substantial heterogeneity of LOS across fracture types and the limitations of conventional approaches, this study aimed to develop and validate fracture‐specific machine learning models for predicting short vs. long hospital stay.

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