Algorithm Helps Determine Patients’ Risk For Carrying, Being Infected With Multidrug-Resistant Organisms, Study Finds

Healio (4/26, Feller) reported, “Natural language processing could reduce the need for manual chart reviews to determine a patient’s risk for carrying or being infected with multidrug-resistant organisms, according to a study” presented at the Society for Healthcare Epidemiology of America Spring Conference. In the study, researchers “tested a natural language processing (NLP) algorithm’s ability to analyze clinician notes for terms related to long-term care facility (LTCF) exposure, which is a risk factor for carriage of multidrug-resistant organisms (MDROs).” They then “trained a machine learning model to identify LTCF exposure from the H&P notes, which it did with a C-statistic of 0.89 (95% CI: 0.80-0.98), indicating that it was highly accurate.”