Internet Hospitals Help Prevent and Control the Epidemic of COVID-19 in China: Multicenter User Profiling Study
Identifieur interne : 000411 ( 2020/Analysis ); précédent : 000410; suivant : 000412Internet Hospitals Help Prevent and Control the Epidemic of COVID-19 in China: Multicenter User Profiling Study
Auteurs :Source :
- Journal of Medical Internet Research [ 1439-4456 ] ; 2020.
Abstract
During the spread of the novel coronavirus disease (COVID-19), internet hospitals in China were engaged with epidemic prevention and control, offering epidemic-related online services and medical support to the public.
The aim of this study is to explore the role of internet hospitals during the prevention and control of the COVID-19 outbreak in China.
Online epidemic-related consultations from multicenter internet hospitals in China during the COVID-19 epidemic were collected. The counselees were described and classified into seven type groups. Symptoms were recorded and compared with reported patients with COVID-19. Hypochondriacal suspicion and offline visit motivation were detected within each counselees’ group to evaluate the social panic of the epidemic along with the consequent medical-seeking behaviors. The counselees’ motivation and the doctors’ recommendation for an offline visit were compared. Risk factors affecting the counselees’ tendency of hypochondriacal suspicion and offline visit motivation were explored by logistic regression models. The epidemic prevention and control measures based on internet hospitals were listed, and the corresponding effects were discussed.
A total of 4913 consultations were enrolled for analysis with the median age of the counselees at 28 years (IQR 22-33 years). There were 104 (2.12%) healthy counselees, 147 (2.99%) hypochondriacal counselees, 34 (0.69%) exposed counselees, 853 (17.36%) mildly suspicious counselees, 42 (0.85%) moderately suspicious counselees, 3550 (72.26%) highly suspicious counselees, and 183 (3.72%) severely suspicious counselees. A total of 94.20% (n=4628) of counselees had epidemic-related symptoms with a distribution similar to those of COVID-19. The hypochondriacal suspicion (n=2167, 44.11%) was common. The counselees’ motivation and the doctors’ recommendation for offline visits were inconsistent (
Internet hospitals can serve different types of epidemic counselees, offer essential medical supports to the public during the COVID-19 outbreak, reduce the social panic, promote social distancing, enhance the public’s ability of self-protection, correct improper medical-seeking behaviors, reduce the chance of nosocomial cross-infection, and facilitate epidemiological screening, thus, playing an important role on preventing and controlling COVID-19.
Url:
DOI: 10.2196/18908
PubMed: 32250962
PubMed Central: 7159055
Affiliations:
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Internet Hospitals Help Prevent and Control the Epidemic of COVID-19 in China: Multicenter User Profiling Study</title></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">32250962</idno><idno type="pmc">7159055</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7159055</idno><idno type="RBID">PMC:7159055</idno><idno type="doi">10.2196/18908</idno><date when="2020">2020</date><idno type="wicri:Area/Pmc/Corpus">000738</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000738</idno><idno type="wicri:Area/Pmc/Curation">000738</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000738</idno><idno type="wicri:Area/Pmc/Checkpoint">000349</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000349</idno><idno type="wicri:Area/Ncbi/Merge">000C87</idno><idno type="wicri:Area/Ncbi/Curation">000C87</idno><idno type="wicri:Area/Ncbi/Checkpoint">000C87</idno><idno type="wicri:Area/Main/Merge">000411</idno><idno type="wicri:Area/Main/Curation">000411</idno><idno type="wicri:Area/Main/Exploration">000411</idno><idno type="wicri:Area/2020/Extraction">000411</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Internet Hospitals Help Prevent and Control the Epidemic of COVID-19 in China: Multicenter User Profiling Study</title></analytic><series><title level="j">Journal of Medical Internet Research</title><idno type="ISSN">1439-4456</idno><idno type="eISSN">1438-8871</idno><imprint><date when="2020">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec sec-type="background"><title>Background</title><p>During the spread of the novel coronavirus disease (COVID-19), internet hospitals in China were engaged with epidemic prevention and control, offering epidemic-related online services and medical support to the public.</p></sec><sec sec-type="objective"><title>Objective</title><p>The aim of this study is to explore the role of internet hospitals during the prevention and control of the COVID-19 outbreak in China.</p></sec><sec sec-type="methods"><title>Methods</title><p>Online epidemic-related consultations from multicenter internet hospitals in China during the COVID-19 epidemic were collected. The counselees were described and classified into seven type groups. Symptoms were recorded and compared with reported patients with COVID-19. Hypochondriacal suspicion and offline visit motivation were detected within each counselees’ group to evaluate the social panic of the epidemic along with the consequent medical-seeking behaviors. The counselees’ motivation and the doctors’ recommendation for an offline visit were compared. Risk factors affecting the counselees’ tendency of hypochondriacal suspicion and offline visit motivation were explored by logistic regression models. The epidemic prevention and control measures based on internet hospitals were listed, and the corresponding effects were discussed.</p></sec><sec sec-type="results"><title>Results</title><p>A total of 4913 consultations were enrolled for analysis with the median age of the counselees at 28 years (IQR 22-33 years). There were 104 (2.12%) healthy counselees, 147 (2.99%) hypochondriacal counselees, 34 (0.69%) exposed counselees, 853 (17.36%) mildly suspicious counselees, 42 (0.85%) moderately suspicious counselees, 3550 (72.26%) highly suspicious counselees, and 183 (3.72%) severely suspicious counselees. A total of 94.20% (n=4628) of counselees had epidemic-related symptoms with a distribution similar to those of COVID-19. The hypochondriacal suspicion (n=2167, 44.11%) was common. The counselees’ motivation and the doctors’ recommendation for offline visits were inconsistent (<italic>P</italic><.001) with a Cohen kappa score of 0.039, indicating improper medical-seeking behaviors. Adult counselees (odds ratio [OR]=1.816, <italic>P</italic><.001) with epidemiological exposure (OR 7.568, <italic>P</italic><.001), shortness of breath (OR 1.440, <italic>P</italic>=.001), diarrhea (OR 1.272, <italic>P</italic>=.04), and unrelated symptoms (OR 1.509, <italic>P</italic><.001) were more likely to have hypochondriacal suspicion. Counselees with severe illnesses (OR 2.303, <italic>P</italic><.001), fever (OR 1.660, <italic>P</italic><.001), epidemiological exposure history (OR 1.440, <italic>P</italic>=.01), and hypochondriacal suspicion (OR 4.826, <italic>P</italic><.001) were more likely to attempt an offline visit. Reattending counselees (OR 0.545, <italic>P</italic>=.002) were less motivated to go to the offline clinic.</p></sec><sec sec-type="conclusions"><title>Conclusions</title><p>Internet hospitals can serve different types of epidemic counselees, offer essential medical supports to the public during the COVID-19 outbreak, reduce the social panic, promote social distancing, enhance the public’s ability of self-protection, correct improper medical-seeking behaviors, reduce the chance of nosocomial cross-infection, and facilitate epidemiological screening, thus, playing an important role on preventing and controlling COVID-19.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Tanne, Jh" uniqKey="Tanne J">JH Tanne</name></author><author><name sortKey="Hayasaki, E" uniqKey="Hayasaki E">E Hayasaki</name></author><author><name sortKey="Zastrow, M" uniqKey="Zastrow M">M Zastrow</name></author><author><name sortKey="Pulla, P" 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Jpa" uniqKey="Ioannidis J">JPA Ioannidis</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bedford, J" uniqKey="Bedford J">J Bedford</name></author><author><name sortKey="Enria, D" uniqKey="Enria D">D Enria</name></author><author><name sortKey="Giesecke, J" uniqKey="Giesecke J">J Giesecke</name></author><author><name sortKey="Heymann, Dl" uniqKey="Heymann D">DL Heymann</name></author><author><name sortKey="Ihekweazu, C" uniqKey="Ihekweazu C">C Ihekweazu</name></author><author><name sortKey="Kobinger, G" uniqKey="Kobinger G">G Kobinger</name></author><author><name sortKey="Lane, Hc" uniqKey="Lane H">HC Lane</name></author><author><name sortKey="Memish, Z" uniqKey="Memish Z">Z Memish</name></author><author><name sortKey="Oh, M" uniqKey="Oh M">M Oh</name></author><author><name sortKey="Sall, Aa" uniqKey="Sall A">AA Sall</name></author><author><name sortKey="Schuchat, A" uniqKey="Schuchat A">A Schuchat</name></author><author><name sortKey="Ungchusak, K" uniqKey="Ungchusak K">K Ungchusak</name></author><author><name sortKey="Wieler, Lh" uniqKey="Wieler L">LH Wieler</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list></list><tree></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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