A comparison of self-report and health care provider data to assess surveillance definitions of influenza-like illness in outpatients.
Identifieur interne : 000223 ( Main/Exploration ); précédent : 000222; suivant : 000224A comparison of self-report and health care provider data to assess surveillance definitions of influenza-like illness in outpatients.
Auteurs : Angela M. Barbara [Canada] ; Mark Loeb ; Lisa Dolovich ; Kevin Brazil ; Margaret L. RussellSource :
- Canadian journal of public health = Revue canadienne de sante publique [ 0008-4263 ]
Descripteurs français
- KwdFr :
- Adolescent (MeSH), Adulte (MeSH), Adulte d'âge moyen (MeSH), Allemagne (ethnologie), Canada (épidémiologie), Enfant (MeSH), Femelle (MeSH), Grippe humaine (diagnostic), Grippe humaine (ethnologie), Grippe humaine (prévention et contrôle), Humains (MeSH), Modèles logistiques (MeSH), Mâle (MeSH), Sensibilité et spécificité (MeSH), Sujet âgé (MeSH), Surveillance de la population (méthodes), Études rétrospectives (MeSH).
- MESH :
- diagnostic : Grippe humaine.
- ethnologie : Allemagne, Grippe humaine.
- méthodes : Surveillance de la population.
- prévention et contrôle : Grippe humaine.
- épidémiologie : Canada.
- Adolescent, Adulte, Adulte d'âge moyen, Enfant, Femelle, Humains, Modèles logistiques, Mâle, Sensibilité et spécificité, Sujet âgé, Études rétrospectives.
- Wicri :
- geographic : Canada.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Aged (MeSH), Canada (epidemiology), Child (MeSH), Female (MeSH), Germany (ethnology), Humans (MeSH), Influenza, Human (diagnosis), Influenza, Human (ethnology), Influenza, Human (prevention & control), Logistic Models (MeSH), Male (MeSH), Middle Aged (MeSH), Population Surveillance (methods), Retrospective Studies (MeSH), Sensitivity and Specificity (MeSH).
- MESH :
- geographic , epidemiology : Canada.
- geographic , ethnology : Germany.
- diagnosis : Influenza, Human.
- ethnology : Influenza, Human.
- methods : Population Surveillance.
- prevention & control : Influenza, Human.
- Adolescent, Adult, Aged, Child, Female, Humans, Logistic Models, Male, Middle Aged, Retrospective Studies, Sensitivity and Specificity.
Abstract
OBJECTIVE
Several surveillance definitions of influenza-like illness (ILI) have been proposed, based on the presence of symptoms. Symptom data can be obtained from patients, medical records, or both. Past research has found that agreements between health record data and self-report are variable depending on the specific symptom. Therefore, we aimed to explore the implications of using data on influenza symptoms extracted from medical records, similar data collected prospectively from outpatients, and the combined data from both sources as predictors of laboratory-confirmed influenza.
METHODS
Using data from the Hutterite Influenza Prevention Study, we calculated: 1) the sensitivity, specificity and predictive values of individual symptoms within surveillance definitions; 2) how frequently surveillance definitions correlated to laboratory-confirmed influenza; and 3) the predictive value of surveillance definitions.
RESULTS
Of the 176 participants with reports from participants and medical records, 142 (81%) were tested for influenza and 37 (26%) were PCR positive for influenza. Fever (alone) and fever combined with cough and/or sore throat were highly correlated with being PCR positive for influenza for all data sources. ILI surveillance definitions, based on symptom data from medical records only or from both medical records and self-report, were better predictors of laboratory-confirmed influenza with higher odds ratios and positive predictive values.
DISCUSSION
The choice of data source to determine ILI will depend on the patient population, outcome of interest, availability of data source, and use for clinical decision making, research, or surveillance.
PubMed: 22338332
PubMed Central: PMC6973605
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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Barbara</name><affiliation wicri:level="1"><nlm:affiliation>Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON. barbara@mcmaster.ca</nlm:affiliation><country wicri:rule="url">Canada</country></affiliation></author><author><name sortKey="Loeb, Mark" sort="Loeb, Mark" uniqKey="Loeb M" first="Mark" last="Loeb">Mark Loeb</name></author><author><name sortKey="Dolovich, Lisa" sort="Dolovich, Lisa" uniqKey="Dolovich L" first="Lisa" last="Dolovich">Lisa Dolovich</name></author><author><name sortKey="Brazil, Kevin" sort="Brazil, Kevin" uniqKey="Brazil K" first="Kevin" last="Brazil">Kevin Brazil</name></author><author><name sortKey="Russell, Margaret L" sort="Russell, Margaret L" uniqKey="Russell M" first="Margaret L" last="Russell">Margaret L. 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Barbara</name><affiliation wicri:level="1"><nlm:affiliation>Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON. barbara@mcmaster.ca</nlm:affiliation><country wicri:rule="url">Canada</country></affiliation></author><author><name sortKey="Loeb, Mark" sort="Loeb, Mark" uniqKey="Loeb M" first="Mark" last="Loeb">Mark Loeb</name></author><author><name sortKey="Dolovich, Lisa" sort="Dolovich, Lisa" uniqKey="Dolovich L" first="Lisa" last="Dolovich">Lisa Dolovich</name></author><author><name sortKey="Brazil, Kevin" sort="Brazil, Kevin" uniqKey="Brazil K" first="Kevin" last="Brazil">Kevin Brazil</name></author><author><name sortKey="Russell, Margaret L" sort="Russell, Margaret L" uniqKey="Russell M" first="Margaret L" last="Russell">Margaret L. Russell</name></author></analytic><series><title level="j">Canadian journal of public health = Revue canadienne de sante publique</title><idno type="ISSN">0008-4263</idno></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent (MeSH)</term><term>Adult (MeSH)</term><term>Aged (MeSH)</term><term>Canada (epidemiology)</term><term>Child (MeSH)</term><term>Female (MeSH)</term><term>Germany (ethnology)</term><term>Humans (MeSH)</term><term>Influenza, Human (diagnosis)</term><term>Influenza, Human (ethnology)</term><term>Influenza, Human (prevention & control)</term><term>Logistic Models (MeSH)</term><term>Male (MeSH)</term><term>Middle Aged (MeSH)</term><term>Population Surveillance (methods)</term><term>Retrospective Studies (MeSH)</term><term>Sensitivity and Specificity (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>Allemagne (ethnologie)</term><term>Canada (épidémiologie)</term><term>Enfant (MeSH)</term><term>Femelle (MeSH)</term><term>Grippe humaine (diagnostic)</term><term>Grippe humaine (ethnologie)</term><term>Grippe humaine (prévention et contrôle)</term><term>Humains (MeSH)</term><term>Modèles logistiques (MeSH)</term><term>Mâle (MeSH)</term><term>Sensibilité et spécificité (MeSH)</term><term>Sujet âgé (MeSH)</term><term>Surveillance de la population (méthodes)</term><term>Études rétrospectives (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Canada</term></keywords><keywords scheme="MESH" type="geographic" qualifier="ethnology" xml:lang="en"><term>Germany</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="diagnostic" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="ethnologie" xml:lang="fr"><term>Allemagne</term><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="ethnology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Population Surveillance</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Surveillance de la population</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="prévention et contrôle" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Canada</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Aged</term><term>Child</term><term>Female</term><term>Humans</term><term>Logistic Models</term><term>Male</term><term>Middle Aged</term><term>Retrospective Studies</term><term>Sensitivity and Specificity</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adolescent</term><term>Adulte</term><term>Adulte d'âge moyen</term><term>Enfant</term><term>Femelle</term><term>Humains</term><term>Modèles logistiques</term><term>Mâle</term><term>Sensibilité et spécificité</term><term>Sujet âgé</term><term>Études rétrospectives</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Canada</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b></p><p>Several surveillance definitions of influenza-like illness (ILI) have been proposed, based on the presence of symptoms. Symptom data can be obtained from patients, medical records, or both. Past research has found that agreements between health record data and self-report are variable depending on the specific symptom. Therefore, we aimed to explore the implications of using data on influenza symptoms extracted from medical records, similar data collected prospectively from outpatients, and the combined data from both sources as predictors of laboratory-confirmed influenza.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>Using data from the Hutterite Influenza Prevention Study, we calculated: 1) the sensitivity, specificity and predictive values of individual symptoms within surveillance definitions; 2) how frequently surveillance definitions correlated to laboratory-confirmed influenza; and 3) the predictive value of surveillance definitions.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>Of the 176 participants with reports from participants and medical records, 142 (81%) were tested for influenza and 37 (26%) were PCR positive for influenza. Fever (alone) and fever combined with cough and/or sore throat were highly correlated with being PCR positive for influenza for all data sources. ILI surveillance definitions, based on symptom data from medical records only or from both medical records and self-report, were better predictors of laboratory-confirmed influenza with higher odds ratios and positive predictive values.</p></div><div type="abstract" xml:lang="en"><p><b>DISCUSSION</b></p><p>The choice of data source to determine ILI will depend on the patient population, outcome of interest, availability of data source, and use for clinical decision making, research, or surveillance.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">22338332</PMID><DateCompleted><Year>2012</Year><Month>03</Month><Day>13</Day></DateCompleted><DateRevised><Year>2020</Year><Month>02</Month><Day>05</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0008-4263</ISSN><JournalIssue CitedMedium="Print"><Volume>103</Volume><Issue>1</Issue><PubDate><MedlineDate>2012 Jan-Feb</MedlineDate></PubDate></JournalIssue><Title>Canadian journal of public health = Revue canadienne de sante publique</Title><ISOAbbreviation>Can J Public Health</ISOAbbreviation></Journal><ArticleTitle>A comparison of self-report and health care provider data to assess surveillance definitions of influenza-like illness in outpatients.</ArticleTitle><Pagination><MedlinePgn>69-75</MedlinePgn></Pagination><Abstract><AbstractText Label="OBJECTIVE" NlmCategory="OBJECTIVE">Several surveillance definitions of influenza-like illness (ILI) have been proposed, based on the presence of symptoms. Symptom data can be obtained from patients, medical records, or both. Past research has found that agreements between health record data and self-report are variable depending on the specific symptom. Therefore, we aimed to explore the implications of using data on influenza symptoms extracted from medical records, similar data collected prospectively from outpatients, and the combined data from both sources as predictors of laboratory-confirmed influenza.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">Using data from the Hutterite Influenza Prevention Study, we calculated: 1) the sensitivity, specificity and predictive values of individual symptoms within surveillance definitions; 2) how frequently surveillance definitions correlated to laboratory-confirmed influenza; and 3) the predictive value of surveillance definitions.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">Of the 176 participants with reports from participants and medical records, 142 (81%) were tested for influenza and 37 (26%) were PCR positive for influenza. Fever (alone) and fever combined with cough and/or sore throat were highly correlated with being PCR positive for influenza for all data sources. ILI surveillance definitions, based on symptom data from medical records only or from both medical records and self-report, were better predictors of laboratory-confirmed influenza with higher odds ratios and positive predictive values.</AbstractText><AbstractText Label="DISCUSSION" NlmCategory="CONCLUSIONS">The choice of data source to determine ILI will depend on the patient population, outcome of interest, availability of data source, and use for clinical decision making, research, or surveillance.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Barbara</LastName><ForeName>Angela M</ForeName><Initials>AM</Initials><AffiliationInfo><Affiliation>Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON. barbara@mcmaster.ca</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Loeb</LastName><ForeName>Mark</ForeName><Initials>M</Initials></Author><Author ValidYN="Y"><LastName>Dolovich</LastName><ForeName>Lisa</ForeName><Initials>L</Initials></Author><Author ValidYN="Y"><LastName>Brazil</LastName><ForeName>Kevin</ForeName><Initials>K</Initials></Author><Author ValidYN="Y"><LastName>Russell</LastName><ForeName>Margaret L</ForeName><Initials>ML</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D003160">Comparative Study</PublicationType><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D016448">Multicenter Study</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Can J Public Health</MedlineTA><NlmUniqueID>0372714</NlmUniqueID><ISSNLinking>0008-4263</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" 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IdType="pubmed">8970487</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>Canada</li></country></list><tree><noCountry><name sortKey="Brazil, Kevin" sort="Brazil, Kevin" uniqKey="Brazil K" first="Kevin" last="Brazil">Kevin Brazil</name><name sortKey="Dolovich, Lisa" sort="Dolovich, Lisa" uniqKey="Dolovich L" first="Lisa" last="Dolovich">Lisa Dolovich</name><name sortKey="Loeb, Mark" sort="Loeb, Mark" uniqKey="Loeb M" first="Mark" last="Loeb">Mark Loeb</name><name sortKey="Russell, Margaret L" sort="Russell, Margaret L" uniqKey="Russell M" first="Margaret L" last="Russell">Margaret L. Russell</name></noCountry><country name="Canada"><noRegion><name sortKey="Barbara, Angela M" sort="Barbara, Angela M" uniqKey="Barbara A" first="Angela M" last="Barbara">Angela M. Barbara</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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