What patients "see" doctors in online fever clinics during COVID-19 in Wuhan?

J Am Med Inform Assoc. 2020 Jul 1;27(7):1067-1071. doi: 10.1093/jamia/ocaa062.

Abstract

Objective: In December 2019, coronavirus disease 2019 (COVID-19) occurred in Wuhan, China. Online fever clinics were developed by hospitals, largely relieving the hospital's burden. Online fever clinics could help people stay out of crowded hospitals and prevent the risk of cross infections. The objective of our study was to describe the patient characteristics of an online fever clinic and explore the most important concerns and question of online patients.

Materials and methods: Our study extracted data from fever clinic records in medical information systems from January 24 to February 18, 2020 in a tertiary hospital in Wuhan. We described the characteristics of patients in fever clinic, then we extracted and classified questions of patient consultations through the online fever clinic dataset.

Results: For the 64 487 patients who attended the online fever clinic, the average age was 30.4 years, and 37 665 (58.4%) were female patients. The current state of patients from online were home without isolation (52 360 [81.2%]), home isolated (11 152 [17.29%]), and outpatient observation (975 [1.51%]). From the 594 patient questions analyzed, confirming diagnosis and seeking medical treatment account for 60.61% and 38.05%, respectively, followed by treating (25.59%), preventing (4.38%), and relieving anxiety (1.68%).

Discussion: Online fever clinics can effectively relieve patients' mood of panic, and doctors can guide patients with suspected of COVID-19 to isolate and protect themselves through online fever clinic. Online fever clinics can also help to reduce the pressure of hospital fever clinics and prevent cross infection.

Conclusions: This study indicated the importance of online fever clinics during the COVID-19 outbreak for prevention and control.

Keywords: COVID-19; consumer health informatics; descriptive research; online fever clinic; online health.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Betacoronavirus*
  • COVID-19
  • China / epidemiology
  • Coronavirus Infections / complications
  • Coronavirus Infections / diagnosis*
  • Coronavirus Infections / epidemiology
  • Coronavirus Infections / prevention & control
  • Datasets as Topic
  • Diagnosis, Differential
  • Disease Outbreaks
  • Female
  • Fever / etiology*
  • Humans
  • Male
  • Middle Aged
  • Outpatient Clinics, Hospital
  • Pandemics / prevention & control
  • Physicians
  • Pneumonia, Viral / complications
  • Pneumonia, Viral / diagnosis*
  • Pneumonia, Viral / epidemiology
  • Pneumonia, Viral / prevention & control
  • SARS-CoV-2
  • Telemedicine*
  • Tertiary Care Centers
  • Young Adult