Use and Content of Primary Care Office-Based vs Telemedicine Care Visits During the COVID-19 Pandemic in the US.
Identifieur interne : 000169 ( Main/Exploration ); précédent : 000168; suivant : 000170Use and Content of Primary Care Office-Based vs Telemedicine Care Visits During the COVID-19 Pandemic in the US.
Auteurs : G Caleb Alexander [États-Unis] ; Matthew Tajanlangit [États-Unis] ; James Heyward [États-Unis] ; Omar Mansour [États-Unis] ; Dima M. Qato [États-Unis] ; Randall S. Stafford [États-Unis]Source :
- JAMA network open [ 2574-3805 ] ; 2020.
Descripteurs français
- KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Afro-Américains (MeSH), Betacoronavirus (MeSH), Consultation médicale (statistiques et données numériques), Femelle (MeSH), Humains (MeSH), Infections à coronavirus (épidémiologie), Jeune adulte (MeSH), Mâle (MeSH), Pandémies (MeSH), Pneumopathie virale (épidémiologie), Population d'origine européenne (MeSH), Prestations des soins de santé (statistiques et données numériques), Soins de santé primaires (statistiques et données numériques), Sujet âgé (MeSH), Télémédecine (statistiques et données numériques), États-Unis (épidémiologie), Études transversales (MeSH).
- MESH :
- statistiques et données numériques : Consultation médicale, Prestations des soins de santé, Soins de santé primaires, Télémédecine.
- épidémiologie : Infections à coronavirus, Pneumopathie virale, États-Unis.
- Adulte, Adulte d'âge moyen, Afro-Américains, Betacoronavirus, Femelle, Humains, Jeune adulte, Mâle, Pandémies, Population d'origine européenne, Sujet âgé, Études transversales.
- Wicri :
- geographic : États-Unis.
English descriptors
- KwdEn :
- Adult (MeSH), African Americans (MeSH), Aged (MeSH), Betacoronavirus (MeSH), COVID-19 (MeSH), Coronavirus Infections (epidemiology), Cross-Sectional Studies (MeSH), Delivery of Health Care (statistics & numerical data), European Continental Ancestry Group (MeSH), Female (MeSH), Humans (MeSH), Male (MeSH), Middle Aged (MeSH), Office Visits (statistics & numerical data), Pandemics (MeSH), Pneumonia, Viral (epidemiology), Primary Health Care (statistics & numerical data), SARS-CoV-2 (MeSH), Telemedicine (statistics & numerical data), United States (epidemiology), Young Adult (MeSH).
- MESH :
- geographic , epidemiology : United States.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- statistics & numerical data : Delivery of Health Care, Office Visits, Primary Health Care, Telemedicine.
- Adult, African Americans, Aged, Betacoronavirus, COVID-19, Cross-Sectional Studies, European Continental Ancestry Group, Female, Humans, Male, Middle Aged, Pandemics, SARS-CoV-2, Young Adult.
Abstract
Importance
Little is known about the association between the coronavirus disease 2019 (COVID-19) pandemic and the level and content of primary care delivery in the US.
Objective
To quantify national changes in the volume, type, and content of primary care delivered during the COVID-19 pandemic, especially with regard to office-based vs telemedicine encounters.
Design, Setting, and Participants
Analysis of serial cross-sectional data from the IQVIA National Disease and Therapeutic Index, a 2-stage, stratified nationally representative audit of outpatient care in the US from the first calendar quarter (Q1) of 2018 to the second calendar quarter (Q2) of 2020.
Main Outcomes and Measures
Visit type (office-based or telemedicine), overall and stratified by patient population and geographic region; assessment of blood pressure or cholesterol measurement; and initiation or continuation of prescription medications.
Results
In the 8 calendar quarters between January 1, 2018, and December 31, 2019, between 122.4 million (95% CI, 117.3-127.5 million) and 130.3 million (95% CI, 124.7-135.9 million) quarterly primary care visits occurred in the US (mean, 125.8 million; 95% CI, 121.7-129.9 million), most of which were office-based (92.9%). In 2020, the total number of encounters decreased to 117.9 million (95% CI, 112.6-123.2 million) in Q1 and 99.3 million (95% CI, 94.9-103.8 million) in Q2, a decrease of 21.4% (27.0 million visits) from the average of Q2 levels during 2018 and 2019. Office-based visits decreased 50.2% (59.1 million visits) in Q2 of 2020 compared with Q2 2018-2019, while telemedicine visits increased from 1.1% of total Q2 2018-2019 visits (1.4 million quarterly visits) to 4.1% in Q1 of 2020 (4.8 million visits) and 35.3% in Q2 of 2020 (35.0 million visits). Decreases occurred in blood pressure level assessment (50.1% decrease, 44.4 million visits) and cholesterol level assessment (36.9% decrease, 10.2 million visits) in Q2 of 2020 compared with Q2 2018-2019 levels, and assessment was less common during telemedicine than during office-based visits (9.6% vs 69.7% for blood pressure; P < .001; 13.5% vs 21.6% for cholesterol; P < .001). New medication visits in Q2 of 2020 decreased by 26.0% (14.1 million visits) from Q2 2018-2019 levels. Telemedicine adoption occurred at similar rates among White individuals and Black individuals (19.3% vs 20.5% of patient visits, respectively, in Q1/Q2 of 2020), varied by region (low of 15.1% of visits [East North Central region], high of 26.8% of visits [Pacific region]), and was not correlated with regional COVID-19 burden.
Conclusions and Relevance
The COVID-19 pandemic has been associated with changes in the structure of primary care delivery, with the content of telemedicine visits differing from that of office-based encounters.
DOI: 10.1001/jamanetworkopen.2020.21476
PubMed: 33006622
PubMed Central: PMC7532385
Affiliations:
Links toward previous steps (curation, corpus...)
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Qato</name><affiliation wicri:level="3"><nlm:affiliation>Department of Pharmacy Systems, Outcomes, and Policy, University of Illinois at Chicago, Chicago.</nlm:affiliation><country>États-Unis</country><placeName><settlement type="city">Chicago</settlement><region type="state">Illinois</region></placeName><wicri:orgArea>Department of Pharmacy Systems, Outcomes, and Policy, University of Illinois at Chicago</wicri:orgArea></affiliation></author><author><name sortKey="Stafford, Randall S" sort="Stafford, Randall S" uniqKey="Stafford R" first="Randall S" last="Stafford">Randall S. Stafford</name><affiliation wicri:level="2"><nlm:affiliation>Stanford Prevention Research Center, Stanford University, Palo Alto, California.</nlm:affiliation><country>États-Unis</country><placeName><region type="state">Californie</region></placeName><wicri:cityArea>Stanford Prevention Research Center, Stanford University, Palo Alto</wicri:cityArea></affiliation></author></analytic><series><title level="j">JAMA network open</title><idno type="eISSN">2574-3805</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult (MeSH)</term><term>African Americans (MeSH)</term><term>Aged (MeSH)</term><term>Betacoronavirus (MeSH)</term><term>COVID-19 (MeSH)</term><term>Coronavirus Infections (epidemiology)</term><term>Cross-Sectional Studies (MeSH)</term><term>Delivery of Health Care (statistics & numerical data)</term><term>European Continental Ancestry Group (MeSH)</term><term>Female (MeSH)</term><term>Humans (MeSH)</term><term>Male (MeSH)</term><term>Middle Aged (MeSH)</term><term>Office Visits (statistics & numerical data)</term><term>Pandemics (MeSH)</term><term>Pneumonia, Viral (epidemiology)</term><term>Primary Health Care (statistics & numerical data)</term><term>SARS-CoV-2 (MeSH)</term><term>Telemedicine (statistics & numerical data)</term><term>United States (epidemiology)</term><term>Young Adult (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term><term>Adulte d'âge moyen (MeSH)</term><term>Afro-Américains (MeSH)</term><term>Betacoronavirus (MeSH)</term><term>Consultation médicale (statistiques et données numériques)</term><term>Femelle (MeSH)</term><term>Humains (MeSH)</term><term>Infections à coronavirus (épidémiologie)</term><term>Jeune adulte (MeSH)</term><term>Mâle (MeSH)</term><term>Pandémies (MeSH)</term><term>Pneumopathie virale (épidémiologie)</term><term>Population d'origine européenne (MeSH)</term><term>Prestations des soins de santé (statistiques et données numériques)</term><term>Soins de santé primaires (statistiques et données numériques)</term><term>Sujet âgé (MeSH)</term><term>Télémédecine (statistiques et données numériques)</term><term>États-Unis (épidémiologie)</term><term>Études transversales (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>United States</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>Delivery of Health Care</term><term>Office Visits</term><term>Primary Health Care</term><term>Telemedicine</term></keywords><keywords scheme="MESH" qualifier="statistiques et données numériques" xml:lang="fr"><term>Consultation médicale</term><term>Prestations des soins de santé</term><term>Soins de santé primaires</term><term>Télémédecine</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term><term>États-Unis</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>African Americans</term><term>Aged</term><term>Betacoronavirus</term><term>COVID-19</term><term>Cross-Sectional Studies</term><term>European Continental Ancestry Group</term><term>Female</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Pandemics</term><term>SARS-CoV-2</term><term>Young Adult</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adulte</term><term>Adulte d'âge moyen</term><term>Afro-Américains</term><term>Betacoronavirus</term><term>Femelle</term><term>Humains</term><term>Jeune adulte</term><term>Mâle</term><term>Pandémies</term><term>Population d'origine européenne</term><term>Sujet âgé</term><term>Études transversales</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>États-Unis</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>Importance</b></p><p>Little is known about the association between the coronavirus disease 2019 (COVID-19) pandemic and the level and content of primary care delivery in the US.</p></div><div type="abstract" xml:lang="en"><p><b>Objective</b></p><p>To quantify national changes in the volume, type, and content of primary care delivered during the COVID-19 pandemic, especially with regard to office-based vs telemedicine encounters.</p></div><div type="abstract" xml:lang="en"><p><b>Design, Setting, and Participants</b></p><p>Analysis of serial cross-sectional data from the IQVIA National Disease and Therapeutic Index, a 2-stage, stratified nationally representative audit of outpatient care in the US from the first calendar quarter (Q1) of 2018 to the second calendar quarter (Q2) of 2020.</p></div><div type="abstract" xml:lang="en"><p><b>Main Outcomes and Measures</b></p><p>Visit type (office-based or telemedicine), overall and stratified by patient population and geographic region; assessment of blood pressure or cholesterol measurement; and initiation or continuation of prescription medications.</p></div><div type="abstract" xml:lang="en"><p><b>Results</b></p><p>In the 8 calendar quarters between January 1, 2018, and December 31, 2019, between 122.4 million (95% CI, 117.3-127.5 million) and 130.3 million (95% CI, 124.7-135.9 million) quarterly primary care visits occurred in the US (mean, 125.8 million; 95% CI, 121.7-129.9 million), most of which were office-based (92.9%). In 2020, the total number of encounters decreased to 117.9 million (95% CI, 112.6-123.2 million) in Q1 and 99.3 million (95% CI, 94.9-103.8 million) in Q2, a decrease of 21.4% (27.0 million visits) from the average of Q2 levels during 2018 and 2019. Office-based visits decreased 50.2% (59.1 million visits) in Q2 of 2020 compared with Q2 2018-2019, while telemedicine visits increased from 1.1% of total Q2 2018-2019 visits (1.4 million quarterly visits) to 4.1% in Q1 of 2020 (4.8 million visits) and 35.3% in Q2 of 2020 (35.0 million visits). Decreases occurred in blood pressure level assessment (50.1% decrease, 44.4 million visits) and cholesterol level assessment (36.9% decrease, 10.2 million visits) in Q2 of 2020 compared with Q2 2018-2019 levels, and assessment was less common during telemedicine than during office-based visits (9.6% vs 69.7% for blood pressure; P < .001; 13.5% vs 21.6% for cholesterol; P < .001). New medication visits in Q2 of 2020 decreased by 26.0% (14.1 million visits) from Q2 2018-2019 levels. Telemedicine adoption occurred at similar rates among White individuals and Black individuals (19.3% vs 20.5% of patient visits, respectively, in Q1/Q2 of 2020), varied by region (low of 15.1% of visits [East North Central region], high of 26.8% of visits [Pacific region]), and was not correlated with regional COVID-19 burden.</p></div><div type="abstract" xml:lang="en"><p><b>Conclusions and Relevance</b></p><p>The COVID-19 pandemic has been associated with changes in the structure of primary care delivery, with the content of telemedicine visits differing from that of office-based encounters.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">33006622</PMID><DateCompleted><Year>2020</Year><Month>10</Month><Day>15</Day></DateCompleted><DateRevised><Year>2020</Year><Month>12</Month><Day>20</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2574-3805</ISSN><JournalIssue CitedMedium="Internet"><Volume>3</Volume><Issue>10</Issue><PubDate><Year>2020</Year><Month>10</Month><Day>01</Day></PubDate></JournalIssue><Title>JAMA network open</Title><ISOAbbreviation>JAMA Netw Open</ISOAbbreviation></Journal><ArticleTitle>Use and Content of Primary Care Office-Based vs Telemedicine Care Visits During the COVID-19 Pandemic in the US.</ArticleTitle><Pagination><MedlinePgn>e2021476</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1001/jamanetworkopen.2020.21476</ELocationID><Abstract><AbstractText Label="Importance">Little is known about the association between the coronavirus disease 2019 (COVID-19) pandemic and the level and content of primary care delivery in the US.</AbstractText><AbstractText Label="Objective">To quantify national changes in the volume, type, and content of primary care delivered during the COVID-19 pandemic, especially with regard to office-based vs telemedicine encounters.</AbstractText><AbstractText Label="Design, Setting, and Participants">Analysis of serial cross-sectional data from the IQVIA National Disease and Therapeutic Index, a 2-stage, stratified nationally representative audit of outpatient care in the US from the first calendar quarter (Q1) of 2018 to the second calendar quarter (Q2) of 2020.</AbstractText><AbstractText Label="Main Outcomes and Measures">Visit type (office-based or telemedicine), overall and stratified by patient population and geographic region; assessment of blood pressure or cholesterol measurement; and initiation or continuation of prescription medications.</AbstractText><AbstractText Label="Results">In the 8 calendar quarters between January 1, 2018, and December 31, 2019, between 122.4 million (95% CI, 117.3-127.5 million) and 130.3 million (95% CI, 124.7-135.9 million) quarterly primary care visits occurred in the US (mean, 125.8 million; 95% CI, 121.7-129.9 million), most of which were office-based (92.9%). In 2020, the total number of encounters decreased to 117.9 million (95% CI, 112.6-123.2 million) in Q1 and 99.3 million (95% CI, 94.9-103.8 million) in Q2, a decrease of 21.4% (27.0 million visits) from the average of Q2 levels during 2018 and 2019. Office-based visits decreased 50.2% (59.1 million visits) in Q2 of 2020 compared with Q2 2018-2019, while telemedicine visits increased from 1.1% of total Q2 2018-2019 visits (1.4 million quarterly visits) to 4.1% in Q1 of 2020 (4.8 million visits) and 35.3% in Q2 of 2020 (35.0 million visits). Decreases occurred in blood pressure level assessment (50.1% decrease, 44.4 million visits) and cholesterol level assessment (36.9% decrease, 10.2 million visits) in Q2 of 2020 compared with Q2 2018-2019 levels, and assessment was less common during telemedicine than during office-based visits (9.6% vs 69.7% for blood pressure; P < .001; 13.5% vs 21.6% for cholesterol; P < .001). New medication visits in Q2 of 2020 decreased by 26.0% (14.1 million visits) from Q2 2018-2019 levels. Telemedicine adoption occurred at similar rates among White individuals and Black individuals (19.3% vs 20.5% of patient visits, respectively, in Q1/Q2 of 2020), varied by region (low of 15.1% of visits [East North Central region], high of 26.8% of visits [Pacific region]), and was not correlated with regional COVID-19 burden.</AbstractText><AbstractText Label="Conclusions and Relevance">The COVID-19 pandemic has been associated with changes in the structure of primary care delivery, with the content of telemedicine visits differing from that of office-based encounters.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Alexander</LastName><ForeName>G Caleb</ForeName><Initials>GC</Initials><AffiliationInfo><Affiliation>Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Division of General Internal Medicine, Johns Hopkins Medicine, Baltimore, Maryland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tajanlangit</LastName><ForeName>Matthew</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Student, Johns Hopkins University, Baltimore, Maryland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Heyward</LastName><ForeName>James</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Mansour</LastName><ForeName>Omar</ForeName><Initials>O</Initials><AffiliationInfo><Affiliation>Monument Analytics, Baltimore, Maryland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Qato</LastName><ForeName>Dima M</ForeName><Initials>DM</Initials><AffiliationInfo><Affiliation>Department of Pharmacy Systems, Outcomes, and Policy, University of Illinois at Chicago, Chicago.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Stafford</LastName><ForeName>Randall S</ForeName><Initials>RS</Initials><AffiliationInfo><Affiliation>Stanford Prevention Research Center, Stanford University, Palo Alto, California.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D003160">Comparative Study</PublicationType><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>10</Month><Day>01</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>JAMA Netw Open</MedlineTA><NlmUniqueID>101729235</NlmUniqueID><ISSNLinking>2574-3805</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="CommentIn"><RefSource>JAMA Netw Open. 2020 Oct 1;3(10):e2021767</RefSource><PMID Version="1">33006616</PMID></CommentsCorrections></CommentsCorrectionsList><MeshHeadingList><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D001741" MajorTopicYN="N">African Americans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000086382" MajorTopicYN="N">COVID-19</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003430" MajorTopicYN="N">Cross-Sectional Studies</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D003695" MajorTopicYN="N">Delivery of Health Care</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D044465" MajorTopicYN="N">European Continental Ancestry Group</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D009819" MajorTopicYN="N">Office Visits</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011320" MajorTopicYN="N">Primary Health Care</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000086402" MajorTopicYN="N">SARS-CoV-2</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017216" MajorTopicYN="N">Telemedicine</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D014481" MajorTopicYN="N" Type="Geographic">United States</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>10</Month><Day>2</Day><Hour>12</Hour><Minute>8</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>10</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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sortKey="Alexander, G Caleb" sort="Alexander, G Caleb" uniqKey="Alexander G" first="G Caleb" last="Alexander">G Caleb Alexander</name><name sortKey="Heyward, James" sort="Heyward, James" uniqKey="Heyward J" first="James" last="Heyward">James Heyward</name><name sortKey="Heyward, James" sort="Heyward, James" uniqKey="Heyward J" first="James" last="Heyward">James Heyward</name><name sortKey="Mansour, Omar" sort="Mansour, Omar" uniqKey="Mansour O" first="Omar" last="Mansour">Omar Mansour</name><name sortKey="Qato, Dima M" sort="Qato, Dima M" uniqKey="Qato D" first="Dima M" last="Qato">Dima M. Qato</name><name sortKey="Stafford, Randall S" sort="Stafford, Randall S" uniqKey="Stafford R" first="Randall S" last="Stafford">Randall S. Stafford</name><name sortKey="Tajanlangit, Matthew" sort="Tajanlangit, Matthew" uniqKey="Tajanlangit M" first="Matthew" last="Tajanlangit">Matthew Tajanlangit</name><name sortKey="Tajanlangit, Matthew" sort="Tajanlangit, Matthew" uniqKey="Tajanlangit M" first="Matthew" last="Tajanlangit">Matthew Tajanlangit</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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