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.

Digital Health Experiences of Incarcerated Populations Using Telemedicine in North Carolina Prisons

“…In addition, we found that patients’ overall satisfaction level was an indicator of their preferred choice of modality in the future, as we would expect; such that lower telemedicine satisfaction was associated with patients’ choosing to be seen in-person for future appointments. Our findings among incarcerated individuals concur prior studies involving the general public showing that telemedicine prior experiences were associated with lower satisfaction levels (14,15).…”