Engagement With the Centers for Disease Control and Prevention Coronavirus Self-Checker and Guidance Provided to Users in the United States From March 23, 2020, to April 19, 2021: Thematic and Trend Analysis.
COVID-19
Self-Checker
automated symptom checker
clinical assessment tool
medical care
online information seeking
triage
Journal
Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882
Informations de publication
Date de publication:
10 03 2023
10 03 2023
Historique:
received:
04
05
2022
accepted:
22
12
2022
revised:
05
10
2022
pubmed:
7
2
2023
medline:
15
3
2023
entrez:
6
2
2023
Statut:
epublish
Résumé
In 2020, at the onset of the COVID-19 pandemic, the United States experienced surges in healthcare needs, which challenged capacity throughout the healthcare system. Stay-at-home orders in many jurisdictions, cancellation of elective procedures, and closures of outpatient medical offices disrupted patient access to care. To inform symptomatic persons about when to seek care and potentially help alleviate the burden on the healthcare system, Centers for Disease Control and Prevention (CDC) and partners developed the CDC Coronavirus Self-Checker ("Self-Checker"). This interactive tool assists individuals seeking information about COVID-19 to determine the appropriate level of care by asking demographic, clinical, and nonclinical questions during an online "conversation." This paper describes user characteristics, trends in use, and recommendations delivered by the Self-Checker between March 23, 2020, and April 19, 2021, for pursuing appropriate levels of medical care depending on the severity of user symptoms. User characteristics and trends in completed conversations that resulted in a care message were analyzed. Care messages delivered by the Self-Checker were manually classified into three overarching conversation themes: (1) seek care immediately; (2) take no action, or stay home and self-monitor; and (3) conversation redirected. Trends in 7-day averages of conversations and COVID-19 cases were examined with development and marketing milestones that potentially impacted Self-Checker user engagement. Among 16,718,667 completed conversations, the Self-Checker delivered recommendations for 69.27% (n=11,580,738) of all conversations to "take no action, or stay home and self-monitor"; 28.8% (n=4,822,138) of conversations to "seek care immediately"; and 1.89% (n=315,791) of conversations were redirected to other resources without providing any care advice. Among 6.8 million conversations initiated for self-reported sick individuals without life-threatening symptoms, 59.21% resulted in a recommendation to "take no action, or stay home and self-monitor." Nearly all individuals (99.8%) who were not sick were also advised to "take no action, or stay home and self-monitor." The majority of Self-Checker conversations resulted in advice to take no action, or stay home and self-monitor. This guidance may have reduced patient volume on the medical system; however, future studies evaluating patients' satisfaction, intention to follow the care advice received, course of action, and care modality pursued could clarify the impact of the Self-Checker and similar tools during future public health emergencies.
Sections du résumé
BACKGROUND
In 2020, at the onset of the COVID-19 pandemic, the United States experienced surges in healthcare needs, which challenged capacity throughout the healthcare system. Stay-at-home orders in many jurisdictions, cancellation of elective procedures, and closures of outpatient medical offices disrupted patient access to care. To inform symptomatic persons about when to seek care and potentially help alleviate the burden on the healthcare system, Centers for Disease Control and Prevention (CDC) and partners developed the CDC Coronavirus Self-Checker ("Self-Checker"). This interactive tool assists individuals seeking information about COVID-19 to determine the appropriate level of care by asking demographic, clinical, and nonclinical questions during an online "conversation."
OBJECTIVE
This paper describes user characteristics, trends in use, and recommendations delivered by the Self-Checker between March 23, 2020, and April 19, 2021, for pursuing appropriate levels of medical care depending on the severity of user symptoms.
METHODS
User characteristics and trends in completed conversations that resulted in a care message were analyzed. Care messages delivered by the Self-Checker were manually classified into three overarching conversation themes: (1) seek care immediately; (2) take no action, or stay home and self-monitor; and (3) conversation redirected. Trends in 7-day averages of conversations and COVID-19 cases were examined with development and marketing milestones that potentially impacted Self-Checker user engagement.
RESULTS
Among 16,718,667 completed conversations, the Self-Checker delivered recommendations for 69.27% (n=11,580,738) of all conversations to "take no action, or stay home and self-monitor"; 28.8% (n=4,822,138) of conversations to "seek care immediately"; and 1.89% (n=315,791) of conversations were redirected to other resources without providing any care advice. Among 6.8 million conversations initiated for self-reported sick individuals without life-threatening symptoms, 59.21% resulted in a recommendation to "take no action, or stay home and self-monitor." Nearly all individuals (99.8%) who were not sick were also advised to "take no action, or stay home and self-monitor."
CONCLUSIONS
The majority of Self-Checker conversations resulted in advice to take no action, or stay home and self-monitor. This guidance may have reduced patient volume on the medical system; however, future studies evaluating patients' satisfaction, intention to follow the care advice received, course of action, and care modality pursued could clarify the impact of the Self-Checker and similar tools during future public health emergencies.
Identifiants
pubmed: 36745776
pii: v25i1e39054
doi: 10.2196/39054
pmc: PMC10039408
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
e39054Informations de copyright
©Ami B Shah, Eghosa Oyegun, William Brett Hampton, Antonio Neri, Nicole Maddox, Danielle Raso, Paramjit Sandhu, Anita Patel, Lisa M Koonin, Leslie Lee, Lauren Roper, Geoffrey Whitfield, David A Siegel, Emily H Koumans. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.03.2023.
Références
Emerg Med J. 2021 Feb;38(2):106-108
pubmed: 33310732
JAMA Pediatr. 2013 Feb;167(2):112-8
pubmed: 23254373
PLoS One. 2018 Jun 26;13(6):e0199284
pubmed: 29944708
BMJ Open. 2019 Aug 1;9(8):e027743
pubmed: 31375610
Med J Aust. 2020 Jun;212(11):514-519
pubmed: 32391611
Health Secur. 2020 Sep/Oct;18(5):392-402
pubmed: 33107763
BMJ Open. 2020 Dec 16;10(12):e040269
pubmed: 33328258
J Med Internet Res. 2020 Nov 23;22(11):e22924
pubmed: 33147165