Accuracy of syndrome definitions based on diagnoses in physician claims.
Identifieur interne : 000556 ( Main/Exploration ); précédent : 000555; suivant : 000557Accuracy of syndrome definitions based on diagnoses in physician claims.
Auteurs : Geneviève Cadieux [Canada] ; David L. Buckeridge ; André Jacques ; Michael Libman ; Nandini Dendukuri ; Robyn TamblynSource :
- BMC public health [ 1471-2458 ] ; 2011.
Descripteurs français
- KwdFr :
- Classification internationale des maladies, Codage clinique (), Collecte de données, Consultation médicale (), Enregistrements, Exanthème (), Exanthème (diagnostic), Femelle, Fièvre (), Fièvre (diagnostic), Humains, Infections de l'appareil respiratoire (), Infections de l'appareil respiratoire (diagnostic), Maladies du système nerveux (), Maladies du système nerveux (diagnostic), Mâle, Québec, Sensibilité et spécificité, Services de santé communautaires (), Surveillance de la population (), Techniques et procédures diagnostiques (normes).
- MESH :
- diagnostic : Exanthème, Fièvre, Infections de l'appareil respiratoire, Maladies du système nerveux.
- normes : Techniques et procédures diagnostiques.
- Classification internationale des maladies, Codage clinique, Collecte de données, Consultation médicale, Enregistrements, Exanthème, Femelle, Fièvre, Humains, Infections de l'appareil respiratoire, Maladies du système nerveux, Mâle, Québec, Sensibilité et spécificité, Services de santé communautaires, Surveillance de la population.
English descriptors
- KwdEn :
- Clinical Coding (methods), Community Health Services (statistics & numerical data), Data Collection, Diagnostic Techniques and Procedures (standards), Exanthema (classification), Exanthema (diagnosis), Female, Fever (classification), Fever (diagnosis), Humans, International Classification of Diseases, Male, Nervous System Diseases (classification), Nervous System Diseases (diagnosis), Office Visits (statistics & numerical data), Population Surveillance (methods), Quebec, Registries, Respiratory Tract Infections (classification), Respiratory Tract Infections (diagnosis), Sensitivity and Specificity.
- MESH :
- classification : Exanthema, Fever, Nervous System Diseases, Respiratory Tract Infections.
- diagnosis : Exanthema, Fever, Nervous System Diseases, Respiratory Tract Infections.
- methods : Clinical Coding, Population Surveillance.
- standards : Diagnostic Techniques and Procedures.
- statistics & numerical data : Community Health Services, Office Visits.
- Data Collection, Female, Humans, International Classification of Diseases, Male, Quebec, Registries, Sensitivity and Specificity.
Abstract
BACKGROUND
Community clinics offer potential for timelier outbreak detection and monitoring than emergency departments. However, the accuracy of syndrome definitions used in surveillance has never been evaluated in community settings. This study's objective was to assess the accuracy of syndrome definitions based on diagnostic codes in physician claims for identifying 5 syndromes (fever, gastrointestinal, neurological, rash, and respiratory including influenza-like illness) in community clinics.
METHODS
We selected a random sample of 3,600 community-based primary care physicians who practiced in the fee-for-service system in the province of Quebec, Canada in 2005-2007. We randomly selected 10 visits per physician from their claims, stratifying on syndrome type and presence, diagnosis, and month. Double-blinded chart reviews were conducted by telephone with consenting physicians to obtain information on patient diagnoses for each sampled visit. The sensitivity, specificity, and positive predictive value (PPV) of physician claims were estimated by comparison to chart review.
RESULTS
1,098 (30.5%) physicians completed the chart review. A chart entry on the date of the corresponding claim was found for 10,529 (95.9%) visits. The sensitivity of syndrome definitions based on diagnostic codes in physician claims was low, ranging from 0.11 (fever) to 0.44 (respiratory), the specificity was high, and the PPV was moderate to high, ranging from 0.59 (fever) to 0.85 (respiratory). We found that rarely used diagnostic codes had a higher probability of being false-positives, and that more commonly used diagnostic codes had a higher PPV.
CONCLUSIONS
Future research should identify physician, patient, and encounter characteristics associated with the accuracy of diagnostic codes in physician claims. This would enable public health to improve syndromic surveillance, either by focusing on physician claims whose diagnostic code is more likely to be accurate, or by using all physician claims and weighing each according to the likelihood that its diagnostic code is accurate.
DOI: 10.1186/1471-2458-11-17
PubMed: 21211054
Affiliations:
Links toward previous steps (curation, corpus...)
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Buckeridge</name></author><author><name sortKey="Jacques, Andre" sort="Jacques, Andre" uniqKey="Jacques A" first="André" last="Jacques">André Jacques</name></author><author><name sortKey="Libman, Michael" sort="Libman, Michael" uniqKey="Libman M" first="Michael" last="Libman">Michael Libman</name></author><author><name sortKey="Dendukuri, Nandini" sort="Dendukuri, Nandini" uniqKey="Dendukuri N" first="Nandini" last="Dendukuri">Nandini Dendukuri</name></author><author><name sortKey="Tamblyn, Robyn" sort="Tamblyn, Robyn" uniqKey="Tamblyn R" first="Robyn" last="Tamblyn">Robyn Tamblyn</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2011">2011</date><idno type="RBID">pubmed:21211054</idno><idno type="pmid">21211054</idno><idno type="doi">10.1186/1471-2458-11-17</idno><idno type="wicri:Area/Main/Corpus">000570</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000570</idno><idno type="wicri:Area/Main/Curation">000570</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000570</idno><idno type="wicri:Area/Main/Exploration">000570</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Accuracy of syndrome definitions based on diagnoses in physician claims.</title><author><name sortKey="Cadieux, Genevieve" sort="Cadieux, Genevieve" uniqKey="Cadieux G" first="Geneviève" last="Cadieux">Geneviève Cadieux</name><affiliation wicri:level="4"><nlm:affiliation>Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada. genevieve.cadieux@mail.mcgill.ca</nlm:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal</wicri:regionArea><placeName><settlement type="city">Montréal</settlement><region type="state">Québec</region></placeName><orgName type="university">Université McGill</orgName></affiliation></author><author><name sortKey="Buckeridge, David L" sort="Buckeridge, David L" uniqKey="Buckeridge D" first="David L" last="Buckeridge">David L. Buckeridge</name></author><author><name sortKey="Jacques, Andre" sort="Jacques, Andre" uniqKey="Jacques A" first="André" last="Jacques">André Jacques</name></author><author><name sortKey="Libman, Michael" sort="Libman, Michael" uniqKey="Libman M" first="Michael" last="Libman">Michael Libman</name></author><author><name sortKey="Dendukuri, Nandini" sort="Dendukuri, Nandini" uniqKey="Dendukuri N" first="Nandini" last="Dendukuri">Nandini Dendukuri</name></author><author><name sortKey="Tamblyn, Robyn" sort="Tamblyn, Robyn" uniqKey="Tamblyn R" first="Robyn" last="Tamblyn">Robyn Tamblyn</name></author></analytic><series><title level="j">BMC public health</title><idno type="eISSN">1471-2458</idno><imprint><date when="2011" type="published">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Clinical Coding (methods)</term><term>Community Health Services (statistics & numerical data)</term><term>Data Collection</term><term>Diagnostic Techniques and Procedures (standards)</term><term>Exanthema (classification)</term><term>Exanthema (diagnosis)</term><term>Female</term><term>Fever (classification)</term><term>Fever (diagnosis)</term><term>Humans</term><term>International Classification of Diseases</term><term>Male</term><term>Nervous System Diseases (classification)</term><term>Nervous System Diseases (diagnosis)</term><term>Office Visits (statistics & numerical data)</term><term>Population Surveillance (methods)</term><term>Quebec</term><term>Registries</term><term>Respiratory Tract Infections (classification)</term><term>Respiratory Tract Infections (diagnosis)</term><term>Sensitivity and Specificity</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Classification internationale des maladies</term><term>Codage clinique ()</term><term>Collecte de données</term><term>Consultation médicale ()</term><term>Enregistrements</term><term>Exanthème ()</term><term>Exanthème (diagnostic)</term><term>Femelle</term><term>Fièvre ()</term><term>Fièvre (diagnostic)</term><term>Humains</term><term>Infections de l'appareil respiratoire ()</term><term>Infections de l'appareil respiratoire (diagnostic)</term><term>Maladies du système nerveux ()</term><term>Maladies du système nerveux (diagnostic)</term><term>Mâle</term><term>Québec</term><term>Sensibilité et spécificité</term><term>Services de santé communautaires ()</term><term>Surveillance de la population ()</term><term>Techniques et procédures diagnostiques (normes)</term></keywords><keywords scheme="MESH" qualifier="classification" xml:lang="en"><term>Exanthema</term><term>Fever</term><term>Nervous System Diseases</term><term>Respiratory Tract Infections</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Exanthema</term><term>Fever</term><term>Nervous System Diseases</term><term>Respiratory Tract Infections</term></keywords><keywords scheme="MESH" qualifier="diagnostic" xml:lang="fr"><term>Exanthème</term><term>Fièvre</term><term>Infections de l'appareil respiratoire</term><term>Maladies du système nerveux</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Clinical Coding</term><term>Population Surveillance</term></keywords><keywords scheme="MESH" qualifier="normes" xml:lang="fr"><term>Techniques et procédures diagnostiques</term></keywords><keywords scheme="MESH" qualifier="standards" xml:lang="en"><term>Diagnostic Techniques and Procedures</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Community Health Services</term><term>Office Visits</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Data Collection</term><term>Female</term><term>Humans</term><term>International Classification of Diseases</term><term>Male</term><term>Quebec</term><term>Registries</term><term>Sensitivity and Specificity</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Classification internationale des maladies</term><term>Codage clinique</term><term>Collecte de données</term><term>Consultation médicale</term><term>Enregistrements</term><term>Exanthème</term><term>Femelle</term><term>Fièvre</term><term>Humains</term><term>Infections de l'appareil respiratoire</term><term>Maladies du système nerveux</term><term>Mâle</term><term>Québec</term><term>Sensibilité et spécificité</term><term>Services de santé communautaires</term><term>Surveillance de la population</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>Community clinics offer potential for timelier outbreak detection and monitoring than emergency departments. However, the accuracy of syndrome definitions used in surveillance has never been evaluated in community settings. This study's objective was to assess the accuracy of syndrome definitions based on diagnostic codes in physician claims for identifying 5 syndromes (fever, gastrointestinal, neurological, rash, and respiratory including influenza-like illness) in community clinics.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>We selected a random sample of 3,600 community-based primary care physicians who practiced in the fee-for-service system in the province of Quebec, Canada in 2005-2007. We randomly selected 10 visits per physician from their claims, stratifying on syndrome type and presence, diagnosis, and month. Double-blinded chart reviews were conducted by telephone with consenting physicians to obtain information on patient diagnoses for each sampled visit. The sensitivity, specificity, and positive predictive value (PPV) of physician claims were estimated by comparison to chart review.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>1,098 (30.5%) physicians completed the chart review. A chart entry on the date of the corresponding claim was found for 10,529 (95.9%) visits. The sensitivity of syndrome definitions based on diagnostic codes in physician claims was low, ranging from 0.11 (fever) to 0.44 (respiratory), the specificity was high, and the PPV was moderate to high, ranging from 0.59 (fever) to 0.85 (respiratory). We found that rarely used diagnostic codes had a higher probability of being false-positives, and that more commonly used diagnostic codes had a higher PPV.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>Future research should identify physician, patient, and encounter characteristics associated with the accuracy of diagnostic codes in physician claims. This would enable public health to improve syndromic surveillance, either by focusing on physician claims whose diagnostic code is more likely to be accurate, or by using all physician claims and weighing each according to the likelihood that its diagnostic code is accurate.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">21211054</PMID><DateCompleted><Year>2011</Year><Month>12</Month><Day>14</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>01</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2458</ISSN><JournalIssue CitedMedium="Internet"><Volume>11</Volume><PubDate><Year>2011</Year><Month>Jan</Month><Day>07</Day></PubDate></JournalIssue><Title>BMC public health</Title><ISOAbbreviation>BMC Public Health</ISOAbbreviation></Journal><ArticleTitle>Accuracy of syndrome definitions based on diagnoses in physician claims.</ArticleTitle><Pagination><MedlinePgn>17</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/1471-2458-11-17</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Community clinics offer potential for timelier outbreak detection and monitoring than emergency departments. However, the accuracy of syndrome definitions used in surveillance has never been evaluated in community settings. This study's objective was to assess the accuracy of syndrome definitions based on diagnostic codes in physician claims for identifying 5 syndromes (fever, gastrointestinal, neurological, rash, and respiratory including influenza-like illness) in community clinics.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">We selected a random sample of 3,600 community-based primary care physicians who practiced in the fee-for-service system in the province of Quebec, Canada in 2005-2007. We randomly selected 10 visits per physician from their claims, stratifying on syndrome type and presence, diagnosis, and month. Double-blinded chart reviews were conducted by telephone with consenting physicians to obtain information on patient diagnoses for each sampled visit. The sensitivity, specificity, and positive predictive value (PPV) of physician claims were estimated by comparison to chart review.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">1,098 (30.5%) physicians completed the chart review. A chart entry on the date of the corresponding claim was found for 10,529 (95.9%) visits. The sensitivity of syndrome definitions based on diagnostic codes in physician claims was low, ranging from 0.11 (fever) to 0.44 (respiratory), the specificity was high, and the PPV was moderate to high, ranging from 0.59 (fever) to 0.85 (respiratory). We found that rarely used diagnostic codes had a higher probability of being false-positives, and that more commonly used diagnostic codes had a higher PPV.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Future research should identify physician, patient, and encounter characteristics associated with the accuracy of diagnostic codes in physician claims. This would enable public health to improve syndromic surveillance, either by focusing on physician claims whose diagnostic code is more likely to be accurate, or by using all physician claims and weighing each according to the likelihood that its diagnostic code is accurate.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Cadieux</LastName><ForeName>Geneviève</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada. genevieve.cadieux@mail.mcgill.ca</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Buckeridge</LastName><ForeName>David L</ForeName><Initials>DL</Initials></Author><Author ValidYN="Y"><LastName>Jacques</LastName><ForeName>André</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>Libman</LastName><ForeName>Michael</ForeName><Initials>M</Initials></Author><Author ValidYN="Y"><LastName>Dendukuri</LastName><ForeName>Nandini</ForeName><Initials>N</Initials></Author><Author ValidYN="Y"><LastName>Tamblyn</LastName><ForeName>Robyn</ForeName><Initials>R</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><Agency>Canadian Institutes of Health Research</Agency><Country>Canada</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D003160">Comparative Study</PublicationType><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2011</Year><Month>01</Month><Day>07</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>BMC Public Health</MedlineTA><NlmUniqueID>100968562</NlmUniqueID><ISSNLinking>1471-2458</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D059019" MajorTopicYN="N">Clinical Coding</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003153" MajorTopicYN="N">Community Health Services</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003625" MajorTopicYN="N">Data Collection</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D019937" MajorTopicYN="N">Diagnostic Techniques and Procedures</DescriptorName><QualifierName UI="Q000592" MajorTopicYN="Y">standards</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005076" MajorTopicYN="N">Exanthema</DescriptorName><QualifierName UI="Q000145" MajorTopicYN="N">classification</QualifierName><QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005334" MajorTopicYN="N">Fever</DescriptorName><QualifierName UI="Q000145" MajorTopicYN="N">classification</QualifierName><QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D038801" MajorTopicYN="N">International Classification of Diseases</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D009422" MajorTopicYN="N">Nervous System Diseases</DescriptorName><QualifierName UI="Q000145" MajorTopicYN="N">classification</QualifierName><QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D009819" MajorTopicYN="N">Office Visits</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011159" MajorTopicYN="N">Population Surveillance</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011792" MajorTopicYN="N">Quebec</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012042" MajorTopicYN="N">Registries</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012141" MajorTopicYN="N">Respiratory Tract Infections</DescriptorName><QualifierName UI="Q000145" MajorTopicYN="N">classification</QualifierName><QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012680" MajorTopicYN="N">Sensitivity and Specificity</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate 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IdType="pubmed">14633933</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>Canada</li></country><region><li>Québec</li></region><settlement><li>Montréal</li></settlement><orgName><li>Université McGill</li></orgName></list><tree><noCountry><name sortKey="Buckeridge, David L" sort="Buckeridge, David L" uniqKey="Buckeridge D" first="David L" last="Buckeridge">David L. Buckeridge</name><name sortKey="Dendukuri, Nandini" sort="Dendukuri, Nandini" uniqKey="Dendukuri N" first="Nandini" last="Dendukuri">Nandini Dendukuri</name><name sortKey="Jacques, Andre" sort="Jacques, Andre" uniqKey="Jacques A" first="André" last="Jacques">André Jacques</name><name sortKey="Libman, Michael" sort="Libman, Michael" uniqKey="Libman M" first="Michael" last="Libman">Michael Libman</name><name sortKey="Tamblyn, Robyn" sort="Tamblyn, Robyn" uniqKey="Tamblyn R" first="Robyn" last="Tamblyn">Robyn Tamblyn</name></noCountry><country name="Canada"><region name="Québec"><name sortKey="Cadieux, Genevieve" sort="Cadieux, Genevieve" uniqKey="Cadieux G" first="Geneviève" last="Cadieux">Geneviève Cadieux</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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