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A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.

Çaǧlar Çaǧlayan1, Sean L Barnes2, Lisa L Pineles3

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This study developed a predictive model for multi-drug resistant organism (MDRO) colonization in intensive care units (ICUs). The model identifies high-risk patients, aiding in timely infection control measures.

Keywords:
Methicillin-resistant Staphylococcus aureus (MRSA)carbapenem-resistant Enterobacteriaceae (CRE)data-centric analyticshealthcare-associated infections (HAIs)machine learning (ML)multidrug-resistant organisms (MDROs)predictive analyticsvancomycin-resistant enterococci (VRE)

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Area of Science:

  • Healthcare epidemiology
  • Infectious disease modeling
  • Clinical informatics

Background:

  • Rising prevalence of multi-drug resistant organisms (MDROs) like MRSA, VRE, and CRE in healthcare settings poses a significant threat.
  • Effective infection control strategies are crucial to mitigate the spread of MDROs within hospitals.

Purpose of the Study:

  • To develop and validate a data-driven modeling framework for predicting MDRO colonization upon ICU admission.
  • To identify key socio-demographic and clinical factors associated with MDRO colonization.

Main Methods:

  • Utilized electronic healthcare record data and a universal MDRO screening program.
  • Employed logistic regression, random forest, and XGBoost algorithms for predictive modeling.
  • Performed threshold optimization to maximize model sensitivity and specificity.

Main Results:

  • Analyzed 4,670 ICU admissions; overall MDRO colonization rate was 17.59%.
  • Achieved high predictive performance: e.g., 82% sensitivity and 83% specificity for overall MDROs using Random Forest.
  • Identified predictors including long-term care facility stay and recent isolation precautions.

Conclusions:

  • The developed data-driven model serves as a clinical decision support tool for early identification of high-risk patients.
  • Enables timely and selective implementation of infection control measures in ICUs.
  • Aims to reduce MDRO transmission and improve patient outcomes in critical care settings.