Development and multicentre validation of the FLEX score: personalised preoperative surgical risk prediction using attention-based ICD-10 and Current Procedural Terminology set embeddings.

ABSTRACT:

Background

Preoperative knowledge of surgical risks can improve perioperative care and patient outcomes. However, assessments requiring clinician examination of patients or manual chart review can be too burdensome for routine use.

Methods

We conducted a multicentre retrospective study of 243 479 adult noncardiac surgical patients at four hospitals within the Mass General Brigham (MGB) system in the USA. We developed a machine learning method using routinely collected coding and patient characteristics data from the electronic health record which predicts 30-day mortality, 30-day readmission, discharge to long-term care, and hospital length of stay.

Results

Our method, the Flexible Surgical Set Embedding (FLEX) score, achieved state-of-the-art performance to identify

SUBMITTER: Liu R 

PROVIDER: S-EPMC10870132 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature