A public health risk model using prior healthcare exposures identifies healthcare-associated pathogen carriage

Background: Early identification of patients colonized with multidrug-resistant organisms (MDROs) facilitates infection control interventions. We assessed a Public Health Risk Model’s ability to predict carbapenem-resistant Enterobacterales and other MDROs. Methods: We retrospectively analyzed a medical intensive care unit patient cohort screened at time of admission for MDRO carriage (1/2017–1/2018). Encounters were linked to Illinois Hospital Discharge Data and assigned a public health risk model probability score. We compared the model’s performance to traditional screening strategies that use variables locally available to clinicians at time of admission (i.e., transfer from other hospital, tracheostomy, gastrostomy, pressure ulcer). Model discrimination was evaluated by quantifying the area under the curve (AUC). For each approach, we assessed sensitivity, specificity, and number needed to screen (NNS) to detect one MDRO carrier. Results: Model probability calculation was successful in 1237/1250 (98.9%) admissions. The model identified carbapenem-resistant Enterobacterales colonization well (AUC 0.82) and generalized to predict colonization with other healthcare-associated MDROs, including carbapenem-resistant Pseudomonas aeruginosa (AUC 0.82) and vancomycin-resistant enterococci (AUC 0.76). The model did not predict MDROs with known local community reservoirs, i.e., third-generation cephalosporin-resistant Enterobacterales (AUC 0.61) and methicillin-resistant Staphylococcus aureus (AUC 0.59). At the same NNS, the model had higher sensitivity compared to use of traditional screening strategies (68% versus 41%). Conclusion: A risk model using patient-level healthcare exposure data from a state public health dataset identified critically ill patients likely to harbor healthcare-associated MDROs at the time of admission.