Protocol for the impact of machine learning-based clinician decision support algorithims in perioperative care (IMAGINATIVE) in Singapore general hospital : a large prospective randomised controlled trial.

ABSTRACT:

Introduction

As surgical accessibility improves, the incidence of postoperative complications is expected to rise. The implementation of a precise and objective risk stratification tool holds the potential to mitigate these complications by early identification of high-risk patients. Moreover, it could address the escalating costs from resource misallocation. In Singapore General Hospital (SGH), we introduced the Combined Assessment of Risk Encountered in Surgery-Machine Learning (CARES-ML) in June 2023, focusing on predicting 30-day postoperative mortality and the need for post-surgery intensive care unit (ICU) stays. The IMAGINATIVE Trial aims to evaluate the efficacy of such systems in a large academic medical centre.

Methods and analysis

This study adopts type 1 effectiv

SUBMITTER: Abdullah HR 

PROVIDER: S-EPMC11667320 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature