Validation of telemedicine-based self-assessment of vital signs for patients with COVID-19: A pilot study.
J Telemed Telecare
; : 1357633X211011825, 2021 May 09.
Article
in English
| MEDLINE | ID: covidwho-1221690
ABSTRACT
INTRODUCTION:
In the ongoing COVID-19 pandemic, the development of a system that would prevent the infection of healthcare providers is in urgent demand. We sought to investigate the feasibility and validity of a telemedicine-based system in which healthcare providers remotely check the vital signs measured by patients with COVID-19.METHODS:
Patients hospitalized with confirmed or suspected COVID-19 measured and uploaded their vital signs to secure cloud storage. Additionally, the respiratory rates were monitored using a mat-type sensor placed under the bed. We assessed the time until the values became available on the Cloud and the agreements between the patient-measured vital signs and simultaneous healthcare provider measurements.RESULTS:
Between 26 May-23 September 2020, 3835 vital signs were measured and uploaded to the cloud storage by the patients (n=16, median 72 years old, 31% women). All patients successfully learned how to use these devices with a 10-minute lecture. The median time until the measurements were available on the cloud system was only 0.35 min, and 95.2% of the vital signs were available within 5 min of the measurement. The agreement between the patients' and healthcare providers' measurements was excellent for all parameters. Interclass coefficient correlations were as follows systolic (0.92, p<0.001), diastolic blood pressure (0.86, p<0.001), heart rate (0.89, p<0.001), peripheral oxygen saturation (0.92, p<0.001), body temperature (0.83, p<0.001), and respiratory rates (0.90, p<0.001).CONCLUSIONS:
Telemedicine-based self-assessment of vital signs in patients with COVID-19 was feasible and reliable. The system will be a useful alternative to traditional vital sign measurements by healthcare providers during the COVID-19 pandemic.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Prognostic study
Language:
English
Journal:
J Telemed Telecare
Journal subject:
Medical Informatics
/
Health Services
Year:
2021
Document Type:
Article
Affiliation country:
1357633X211011825
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