American journal of infection control · 2026
Electronic operational classification of hospital-onset bacteremia and fungemia in Epic Cosmos: A retrospective observational study.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Al Mohajer Mayar, Leach Rebecca, Aschenberg Laura, Andersen Kevin, Lasco Todd
Аннотация
BACKGROUND: Hospital-onset bacteremia and fungemia (HOB) has been proposed as an electronic surveillance outcome, but deidentified electronic health record data require transparent organism handling when chart review is unavailable.
METHODS: We analyzed deidentified HOB records from Epic Cosmos and retained the first positive blood-culture event per admission on or after hospital day 4. Organism text was standardized and linked to a locally developed workbook based on common-commensal organism logic and review by infectious diseases physicians and laboratory directors. Events were assigned to 4 algorithm-defined operational classes: likely pathogen, possible pathogen, likely contaminant, or unclassified. We summarized class distribution and organism patterns. A logistic model comparing likely contaminant with likely pathogen events was exploratory.
RESULTS: Among 77,261 event-level records, 69,303 first events per admission comprised the analytic cohort. Events were likely pathogen (44,239; 63.8%), possible pathogen (6,093; 8.8%), likely contaminant (663; 1.0%), or unclassified (18,308; 26.4%). Unclassified events lacked usable organism tokens. Staphylococcus epidermidis accounted for 10.4% of classifiable organism tokens and 66.5% of likely contaminant tokens. The likely contaminant class was intentionally narrow.
CONCLUSIONS: A transparent electronic algorithm classified HOB events into operational surveillance classes at scale. Site-level validation is needed before benchmarking or reporting.
METHODS: We analyzed deidentified HOB records from Epic Cosmos and retained the first positive blood-culture event per admission on or after hospital day 4. Organism text was standardized and linked to a locally developed workbook based on common-commensal organism logic and review by infectious diseases physicians and laboratory directors. Events were assigned to 4 algorithm-defined operational classes: likely pathogen, possible pathogen, likely contaminant, or unclassified. We summarized class distribution and organism patterns. A logistic model comparing likely contaminant with likely pathogen events was exploratory.
RESULTS: Among 77,261 event-level records, 69,303 first events per admission comprised the analytic cohort. Events were likely pathogen (44,239; 63.8%), possible pathogen (6,093; 8.8%), likely contaminant (663; 1.0%), or unclassified (18,308; 26.4%). Unclassified events lacked usable organism tokens. Staphylococcus epidermidis accounted for 10.4% of classifiable organism tokens and 66.5% of likely contaminant tokens. The likely contaminant class was intentionally narrow.
CONCLUSIONS: A transparent electronic algorithm classified HOB events into operational surveillance classes at scale. Site-level validation is needed before benchmarking or reporting.