Key PointsQuestionCan a natural language processing (NLP) model accurately classify patient-initiated electronic health record (EHR) messages and triage positive COVID-19 cases?FindingsIn this cohort study of 10 172 patients, 3048 messages reported COVID-19–positive test results, and the mean (SD) message response time for patients who received treatment (364.10 [784.47] minutes) was faster than for those who did not (490.38 [1132.14] minutes). This novel NLP model classified patient messages with 94% accuracy and a sensitivity of 85% for messages that mentioned confirmed COVID-19 infection, discussed COVID-19 without mentioning a positive test result, or were unrelated to COVID-19.MeaningThese findings suggest that NLP-EHR integration can effectively triage patients reporting positive at-home COVID-19 test results via the EHR, reducing the time to first message response and increasing the likelihood of receiving an antiviral prescription within the 5-day treatment window.