Using Automated Text Processing to Assess the Patient Experience of an On-Demand Tele-Urgent Care

Abstract

Novel methods are needed to evaluate the perceptions of patients using telehealth. Automated text processing methods presents a golden opportunity to classify and analyze unstructured survey responses from patients. This study analyzed 585 unstructured entries from telehealth patients. Satisfied patients who returned for a second visit applauded the efficiency and physician interactions. While unsatisfied patients who did not return for a second visit complained of misdiagnosis and inefficiencies in e-prescription. Patient experience was significantly different between weekdays and weekends (p<0.05). Overall, tele-urgent are convenient for patients however, there are current facilitators related to patient-provider interaction and health information exchange that need further optimization.