Prediction of financial deficits of postoperative patients in the intensive care unit using machine learning.

ABSTRACT:

Background

Operational loss, defined as unanticipated financial deficits in intensive care unit (ICU) management, is challenging to predict yet critical for hospital sustainability. This study aimed to evaluate whether machine-learning models can predict financial loss events in postoperative ICU patients.

Methods

We conducted a retrospective analysis of postoperative patients admitted to the ICU at Tohoku University Hospital between April 2017 and March 2021. A total of 22 clinical and administrative variables collected within 24 h of ICU admission were used to develop machine-learning models. The outcome was defined as financial loss events, determined by a negative contribution margin below the break-even threshold of - 909 USD. The dataset was randomly split into trainin

SUBMITTER: Ikumi S 

PROVIDER: S-EPMC12540221 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature