Literature DB >> 35062178

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

Saif Khairat1, Xinyi Zhang1, Makena Boyd2, Barbara Edson2, Robert Gianforcaro2.   

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.

Entities:  

Keywords:  Experience; Patient; Telemedicine

Mesh:

Year:  2022        PMID: 35062178     DOI: 10.3233/SHTI210945

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  1 in total

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

Authors:  Saif Khairat; Erin Wallace; Aaron Bohlmann; Ashlyn Zebrowski; Kaitlyn Stabile; Yuxiao Yao; Adnan Lakdawala; Barbara Edson; Terri Catlett
Journal:  J Patient Exp       Date:  2022-04-19
  1 in total

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