Development and validation of a point-of-care clinical risk score to predict surgical site complication-associated readmissions following open spine surgery.

ABSTRACT:

Background

Surgical site complications (SSCs) contribute to increased healthcare costs. Predictive analytics can aid in identifying high-risk patients and implementing optimization strategies. This study aimed to develop and validate a risk-assessment score for SSC-associated readmissions (SSC-ARs) in patients undergoing open spine surgery.

Methods

The Premier Healthcare Database (PHD) of adult patients (n=157,664; 3,182 SSC-ARs) between January 2019 and September 2020 was used for retrospective data analysis to create an SSC risk score using mixed effects logistic regression modeling. Full and reduced models were developed using patient-, facility-, or procedure-related predictors. The full model used 37 predictors and the reduced used 19.

Results

The reduced model e

SUBMITTER: Mueller KB 

PROVIDER: S-EPMC10982919 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature