Analysis of Risk Factors on Readmission Cases of COVID-19 in the Republic of Korea: Using Nationwide Health Claims Data.
Identifieur interne : 000944 ( Main/Exploration ); précédent : 000943; suivant : 000945Analysis of Risk Factors on Readmission Cases of COVID-19 in the Republic of Korea: Using Nationwide Health Claims Data.
Auteurs : Woo-Hwi Jeon [Corée du Sud] ; Jeong Yeon Seon [Corée du Sud] ; So-Youn Park [Corée du Sud] ; In-Hwan Oh [Corée du Sud]Source :
- International journal of environmental research and public health [ 1660-4601 ] ; 2020.
Descripteurs français
- KwdFr :
- Adolescent (MeSH), Adulte (MeSH), Adulte d'âge moyen (MeSH), Betacoronavirus (MeSH), Comorbidité (MeSH), Coronavirus (MeSH), Dépenses de santé (statistiques et données numériques), Enfant (MeSH), Enfant d'âge préscolaire (MeSH), Examen des demandes de remboursement d'assurance (statistiques et données numériques), Facteurs de risque (MeSH), Facteurs sexuels (MeSH), Facteurs socioéconomiques (MeSH), Facteurs âges (MeSH), Femelle (MeSH), Humains (MeSH), Infections à coronavirus (épidémiologie), Jeune adulte (MeSH), Loi du khi-deux (MeSH), Mâle (MeSH), Nourrisson (MeSH), Pandémies (MeSH), Pneumopathie virale (épidémiologie), Ressources en santé (statistiques et données numériques), Réadmission du patient (statistiques et données numériques), République de Corée (épidémiologie), Sujet âgé (MeSH).
- MESH :
- statistiques et données numériques : Dépenses de santé, Examen des demandes de remboursement d'assurance, Ressources en santé, Réadmission du patient.
- épidémiologie : Infections à coronavirus, Pneumopathie virale, République de Corée.
- Adolescent, Adulte, Adulte d'âge moyen, Betacoronavirus, Comorbidité, Coronavirus, Enfant, Enfant d'âge préscolaire, Facteurs de risque, Facteurs sexuels, Facteurs socioéconomiques, Facteurs âges, Femelle, Humains, Jeune adulte, Loi du khi-deux, Mâle, Nourrisson, Pandémies, Sujet âgé.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Age Factors (MeSH), Aged (MeSH), Betacoronavirus (MeSH), Chi-Square Distribution (MeSH), Child (MeSH), Child, Preschool (MeSH), Comorbidity (MeSH), Coronavirus (MeSH), Coronavirus Infections (epidemiology), Female (MeSH), Health Expenditures (statistics & numerical data), Health Resources (statistics & numerical data), Humans (MeSH), Infant (MeSH), Insurance Claim Review (statistics & numerical data), Male (MeSH), Middle Aged (MeSH), Pandemics (MeSH), Patient Readmission (statistics & numerical data), Pneumonia, Viral (epidemiology), Republic of Korea (epidemiology), Risk Factors (MeSH), Sex Factors (MeSH), Socioeconomic Factors (MeSH), Young Adult (MeSH).
- MESH :
- geographic , epidemiology : Republic of Korea.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- statistics & numerical data : Health Expenditures, Health Resources, Insurance Claim Review, Patient Readmission.
- Adolescent, Adult, Age Factors, Aged, Betacoronavirus, Chi-Square Distribution, Child, Child, Preschool, Comorbidity, Coronavirus, Female, Humans, Infant, Male, Middle Aged, Pandemics, Risk Factors, Sex Factors, Socioeconomic Factors, Young Adult.
Abstract
In South Korea, 4.5% patients of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were readmitted to hospitals after discharge. However, there is insufficient research on risk factors for readmission and management of patients after discharge is poor. In this study, 7590 confirmed coronavirus disease (COVID-19) patients were defined as a target for analysis using nationwide medical claims data. The demographic characteristics, underlying diseases, and the use of medical resources were used to examine the association with readmission through the chi-square test and then logistic regression analysis was performed to analyze factors affecting readmission. Of the 7590 subjects analyzed, 328 patients were readmitted. The readmission rates of men, older age and patients with medical benefits showed a high risk of readmission. The Charlson Comorbidity Index score was also related to COVID-19 readmission. Concerning requiring medical attention, there was a higher risk of readmission for the patients with chest radiographs, computed tomography scans taken and lopinavir/ritonavir at the time of their first admission. Considering the risk factors presented in this study, classifying patients with a high risk of readmission and managing patients before and after discharge based on priority can make patient management and medical resource utilization more efficient. This study also indicates the importance of lifestyle management after discharge.
DOI: 10.3390/ijerph17165844
PubMed: 32806775
PubMed Central: PMC7460295
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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(epidemiology)</term><term>Republic of Korea (epidemiology)</term><term>Risk Factors (MeSH)</term><term>Sex Factors (MeSH)</term><term>Socioeconomic Factors (MeSH)</term><term>Young Adult (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adolescent (MeSH)</term><term>Adulte (MeSH)</term><term>Adulte d'âge moyen (MeSH)</term><term>Betacoronavirus (MeSH)</term><term>Comorbidité (MeSH)</term><term>Coronavirus (MeSH)</term><term>Dépenses de santé (statistiques et données numériques)</term><term>Enfant (MeSH)</term><term>Enfant d'âge préscolaire (MeSH)</term><term>Examen des demandes de remboursement d'assurance (statistiques et données numériques)</term><term>Facteurs de risque (MeSH)</term><term>Facteurs sexuels (MeSH)</term><term>Facteurs socioéconomiques (MeSH)</term><term>Facteurs âges (MeSH)</term><term>Femelle (MeSH)</term><term>Humains (MeSH)</term><term>Infections à coronavirus (épidémiologie)</term><term>Jeune adulte (MeSH)</term><term>Loi du khi-deux (MeSH)</term><term>Mâle (MeSH)</term><term>Nourrisson (MeSH)</term><term>Pandémies (MeSH)</term><term>Pneumopathie virale (épidémiologie)</term><term>Ressources en santé (statistiques et données numériques)</term><term>Réadmission du patient (statistiques et données numériques)</term><term>République de Corée (épidémiologie)</term><term>Sujet âgé (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Republic of Korea</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Health Expenditures</term><term>Health Resources</term><term>Insurance Claim Review</term><term>Patient Readmission</term></keywords><keywords scheme="MESH" qualifier="statistiques et données numériques" xml:lang="fr"><term>Dépenses de santé</term><term>Examen des demandes de remboursement d'assurance</term><term>Ressources en santé</term><term>Réadmission du patient</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term><term>République de Corée</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Age Factors</term><term>Aged</term><term>Betacoronavirus</term><term>Chi-Square Distribution</term><term>Child</term><term>Child, Preschool</term><term>Comorbidity</term><term>Coronavirus</term><term>Female</term><term>Humans</term><term>Infant</term><term>Male</term><term>Middle Aged</term><term>Pandemics</term><term>Risk Factors</term><term>Sex Factors</term><term>Socioeconomic Factors</term><term>Young Adult</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adolescent</term><term>Adulte</term><term>Adulte d'âge moyen</term><term>Betacoronavirus</term><term>Comorbidité</term><term>Coronavirus</term><term>Enfant</term><term>Enfant d'âge préscolaire</term><term>Facteurs de risque</term><term>Facteurs sexuels</term><term>Facteurs socioéconomiques</term><term>Facteurs âges</term><term>Femelle</term><term>Humains</term><term>Jeune adulte</term><term>Loi du khi-deux</term><term>Mâle</term><term>Nourrisson</term><term>Pandémies</term><term>Sujet âgé</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In South Korea, 4.5% patients of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were readmitted to hospitals after discharge. However, there is insufficient research on risk factors for readmission and management of patients after discharge is poor. In this study, 7590 confirmed coronavirus disease (COVID-19) patients were defined as a target for analysis using nationwide medical claims data. The demographic characteristics, underlying diseases, and the use of medical resources were used to examine the association with readmission through the chi-square test and then logistic regression analysis was performed to analyze factors affecting readmission. Of the 7590 subjects analyzed, 328 patients were readmitted. The readmission rates of men, older age and patients with medical benefits showed a high risk of readmission. The Charlson Comorbidity Index score was also related to COVID-19 readmission. Concerning requiring medical attention, there was a higher risk of readmission for the patients with chest radiographs, computed tomography scans taken and lopinavir/ritonavir at the time of their first admission. Considering the risk factors presented in this study, classifying patients with a high risk of readmission and managing patients before and after discharge based on priority can make patient management and medical resource utilization more efficient. This study also indicates the importance of lifestyle management after discharge.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">32806775</PMID><DateCompleted><Year>2020</Year><Month>09</Month><Day>02</Day></DateCompleted><DateRevised><Year>2020</Year><Month>09</Month><Day>03</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1660-4601</ISSN><JournalIssue CitedMedium="Internet"><Volume>17</Volume><Issue>16</Issue><PubDate><Year>2020</Year><Month>08</Month><Day>12</Day></PubDate></JournalIssue><Title>International journal of environmental research and public health</Title><ISOAbbreviation>Int J Environ Res Public Health</ISOAbbreviation></Journal><ArticleTitle>Analysis of Risk Factors on Readmission Cases of COVID-19 in the Republic of Korea: Using Nationwide Health Claims Data.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">E5844</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.3390/ijerph17165844</ELocationID><Abstract><AbstractText>In South Korea, 4.5% patients of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were readmitted to hospitals after discharge. However, there is insufficient research on risk factors for readmission and management of patients after discharge is poor. In this study, 7590 confirmed coronavirus disease (COVID-19) patients were defined as a target for analysis using nationwide medical claims data. The demographic characteristics, underlying diseases, and the use of medical resources were used to examine the association with readmission through the chi-square test and then logistic regression analysis was performed to analyze factors affecting readmission. Of the 7590 subjects analyzed, 328 patients were readmitted. The readmission rates of men, older age and patients with medical benefits showed a high risk of readmission. The Charlson Comorbidity Index score was also related to COVID-19 readmission. Concerning requiring medical attention, there was a higher risk of readmission for the patients with chest radiographs, computed tomography scans taken and lopinavir/ritonavir at the time of their first admission. Considering the risk factors presented in this study, classifying patients with a high risk of readmission and managing patients before and after discharge based on priority can make patient management and medical resource utilization more efficient. This study also indicates the importance of lifestyle management after discharge.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Jeon</LastName><ForeName>Woo-Hwi</ForeName><Initials>WH</Initials><Identifier Source="ORCID">0000-0002-8544-4115</Identifier><AffiliationInfo><Affiliation>Department of Preventive Medicine, School of Medicine, Kyung Hee University, Seoul 02447, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Seon</LastName><ForeName>Jeong Yeon</ForeName><Initials>JY</Initials><AffiliationInfo><Affiliation>Department of Preventive Medicine, School of Medicine, Kyung Hee University, Seoul 02447, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Park</LastName><ForeName>So-Youn</ForeName><Initials>SY</Initials><AffiliationInfo><Affiliation>Department of Medical Education and Humanities, School of Medicine, Kyung Hee University, Seoul 02447, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Oh</LastName><ForeName>In-Hwan</ForeName><Initials>IH</Initials><AffiliationInfo><Affiliation>Department of Preventive Medicine, School of Medicine, Kyung Hee University, Seoul 02447, Korea.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>HI18C0446</GrantID><Agency>Korea Health Industry Development Institute</Agency><Country>International</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>08</Month><Day>12</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Int J Environ Res Public Health</MedlineTA><NlmUniqueID>101238455</NlmUniqueID><ISSNLinking>1660-4601</ISSNLinking></MedlineJournalInfo><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName><SupplMeshName Type="Organism" UI="C000656484">severe acute respiratory syndrome coronavirus 2</SupplMeshName></SupplMeshList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000367" MajorTopicYN="N">Age Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016009" MajorTopicYN="N">Chi-Square Distribution</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002675" MajorTopicYN="N">Child, Preschool</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015897" MajorTopicYN="N">Comorbidity</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017934" MajorTopicYN="N">Coronavirus</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005102" MajorTopicYN="N">Health Expenditures</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006295" MajorTopicYN="N">Health Resources</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007223" MajorTopicYN="N">Infant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007345" MajorTopicYN="N">Insurance Claim Review</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010359" MajorTopicYN="N">Patient Readmission</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D056910" MajorTopicYN="N" Type="Geographic">Republic of Korea</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012307" MajorTopicYN="N">Risk Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012737" MajorTopicYN="N">Sex Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012959" MajorTopicYN="N">Socioeconomic Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">COVID-19</Keyword><Keyword MajorTopicYN="Y">readmission</Keyword><Keyword MajorTopicYN="Y">risk factors</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>07</Month><Day>14</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>08</Month><Day>10</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>08</Month><Day>11</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>8</Month><Day>19</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>8</Month><Day>19</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>9</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32806775</ArticleId><ArticleId IdType="pii">ijerph17165844</ArticleId><ArticleId IdType="doi">10.3390/ijerph17165844</ArticleId><ArticleId 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Oh</name><name sortKey="Park, So Youn" sort="Park, So Youn" uniqKey="Park S" first="So-Youn" last="Park">So-Youn Park</name><name sortKey="Seon, Jeong Yeon" sort="Seon, Jeong Yeon" uniqKey="Seon J" first="Jeong Yeon" last="Seon">Jeong Yeon Seon</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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