Determining the predictive value of Read codes to identify congenital cardiac malformations in the UK Clinical Practice Research Datalink
ABSTRACT Purposes The purposes of this study were to determine (i) the positive predictive value (PPV) of multiple Read codes used to identify congenital cardiac malformation (CCM) cases in the UK Clinical Practice Research Datalink (CPRD); (ii) the accuracy of the diagnosis date; and (iii) the sour...
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Veröffentlicht in: | Pharmacoepidemiology and drug safety 2013-11, Vol.22 (11), p.1233-1238 |
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creator | Hammad, Tarek A. Margulis, Andrea V. Ding, Yulan Strazzeri, Marian M. Epperly, Holly |
description | ABSTRACT
Purposes
The purposes of this study were to determine (i) the positive predictive value (PPV) of multiple Read codes used to identify congenital cardiac malformation (CCM) cases in the UK Clinical Practice Research Datalink (CPRD); (ii) the accuracy of the diagnosis date; and (iii) the source of information that the general practitioners (GPs) use for validating the diagnosis suggested by the code.
Methods
Eight hundred eighty‐eight records with Read diagnostic and procedures codes for CCM, between January 1996 and November 2010, were identified from CPRD. Questionnaires were sent to GPs to verify the diagnoses and date of the code‐identified events.
Results
A total of 719 questionnaires were returned (81% response rate). The PPV of the CCM codes was 93% (670/719). Thirty‐one percent of cases had a different event date than the one recorded in the electronic medical record (EMR); 10% of these differing dates were within 30 days of the code‐identified CCM date. GPs used a variety of data sources to confirm CCM diagnoses. Although the EMR was the most frequently used data source (70%), 66% reported using consultation letters, 9% reported using clinical notes or paper charts, and 35% of GPs reported using the hospital record to confirm the CCM diagnosis.
Conclusions
Clinical Practice Research Datalink Read codes for CCMs have 93% PPV and most likely point to true cases. However, the accuracy of diagnosis dates and the age at diagnosis may not be as reliable. The findings of this study indicate that GPs use information beyond what is available for researchers in the EMR to confirm clinical diagnoses when responding to validation questionnaires. Published 2013. This article is a U.S. Government work and is in the public domain in the USA. |
doi_str_mv | 10.1002/pds.3511 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1465861649</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1465861649</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4171-f5eddc7f16f98709fb932b96cd45080618807a4d06efa2706f5bd4000c9a76483</originalsourceid><addsrcrecordid>eNp1kd1uFCEYhidGY2s18QoMiTHxZCrM8DMcml3tGpvaWKuHhIWPlnYGVpip7iV417J2bBMTjyDw8LzAW1XPCT4kGDdvNjYftoyQB9U-wVLWhDHxcDdnbd0xLveqJzlfYVz2JH1c7TW0nJKS7Ve_ljBCGnzw4QKNl4A2Caw3o78BdKP7CVB06DNoi0y0kNEYkbcQRu-2ZSVcQPCj7pHRyXpt0KB7F9OgRx9DRj78UZ5_RIu-JJgCniZd5AaKM4NO5hItdRH4cP20euR0n-HZPB5U5-_ffVms6uNPRx8Wb49rQ4kgtWNgrRGOcCc7gaVby7ZZS24sZbjDnHQdFppazMHpRmDu2NqW52IjteC0aw-q17feTYrfJ8ijGnw20Pc6QJyyIpSzjhNOZUFf_oNexSmFcrtC0bbtcEPkvdCkmHMCpzbJDzptFcFqV48q9ahdPQV9MQun9QD2DvzbRwFezYDO5btc0sH4fM8JKbpW0sLVt9wP38P2v4HqdHk2B8-8zyP8vON1ulZctIKpbydHarX4enImVkLR9jdTC7U6</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1443380219</pqid></control><display><type>article</type><title>Determining the predictive value of Read codes to identify congenital cardiac malformations in the UK Clinical Practice Research Datalink</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Hammad, Tarek A. ; Margulis, Andrea V. ; Ding, Yulan ; Strazzeri, Marian M. ; Epperly, Holly</creator><creatorcontrib>Hammad, Tarek A. ; Margulis, Andrea V. ; Ding, Yulan ; Strazzeri, Marian M. ; Epperly, Holly</creatorcontrib><description>ABSTRACT
Purposes
The purposes of this study were to determine (i) the positive predictive value (PPV) of multiple Read codes used to identify congenital cardiac malformation (CCM) cases in the UK Clinical Practice Research Datalink (CPRD); (ii) the accuracy of the diagnosis date; and (iii) the source of information that the general practitioners (GPs) use for validating the diagnosis suggested by the code.
Methods
Eight hundred eighty‐eight records with Read diagnostic and procedures codes for CCM, between January 1996 and November 2010, were identified from CPRD. Questionnaires were sent to GPs to verify the diagnoses and date of the code‐identified events.
Results
A total of 719 questionnaires were returned (81% response rate). The PPV of the CCM codes was 93% (670/719). Thirty‐one percent of cases had a different event date than the one recorded in the electronic medical record (EMR); 10% of these differing dates were within 30 days of the code‐identified CCM date. GPs used a variety of data sources to confirm CCM diagnoses. Although the EMR was the most frequently used data source (70%), 66% reported using consultation letters, 9% reported using clinical notes or paper charts, and 35% of GPs reported using the hospital record to confirm the CCM diagnosis.
Conclusions
Clinical Practice Research Datalink Read codes for CCMs have 93% PPV and most likely point to true cases. However, the accuracy of diagnosis dates and the age at diagnosis may not be as reliable. The findings of this study indicate that GPs use information beyond what is available for researchers in the EMR to confirm clinical diagnoses when responding to validation questionnaires. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.</description><identifier>ISSN: 1053-8569</identifier><identifier>EISSN: 1099-1557</identifier><identifier>DOI: 10.1002/pds.3511</identifier><identifier>PMID: 24002995</identifier><identifier>CODEN: PDSAEA</identifier><language>eng</language><publisher>Chichester: Blackwell Publishing Ltd</publisher><subject>Age Factors ; Biological and medical sciences ; Cardiovascular disease ; Child ; Child, Preschool ; Clinical Coding ; Clinical medicine ; Clinical Practice Research Datalink ; Clinical trial. Drug monitoring ; Codes ; congenital abnormalities ; Databases, Factual - statistics & numerical data ; Electronic Health Records - statistics & numerical data ; General pharmacology ; General Practice - methods ; General Practitioners - statistics & numerical data ; heart defects ; Heart Defects, Congenital - diagnosis ; Humans ; Infant ; Medical diagnosis ; Medical sciences ; pharmacoepidemiology ; Pharmacology. Drug treatments ; Predictive Value of Tests ; Questionnaires ; Read/OXMIS codes ; Reproducibility of Results ; Surveys and Questionnaires ; United Kingdom ; validation of congenital cardiac malformation</subject><ispartof>Pharmacoepidemiology and drug safety, 2013-11, Vol.22 (11), p.1233-1238</ispartof><rights>Published 2013. This article is a U.S. Government work and is in the public domain in the USA.</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4171-f5eddc7f16f98709fb932b96cd45080618807a4d06efa2706f5bd4000c9a76483</citedby><cites>FETCH-LOGICAL-c4171-f5eddc7f16f98709fb932b96cd45080618807a4d06efa2706f5bd4000c9a76483</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fpds.3511$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fpds.3511$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,777,781,1412,27905,27906,45555,45556</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27978394$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24002995$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hammad, Tarek A.</creatorcontrib><creatorcontrib>Margulis, Andrea V.</creatorcontrib><creatorcontrib>Ding, Yulan</creatorcontrib><creatorcontrib>Strazzeri, Marian M.</creatorcontrib><creatorcontrib>Epperly, Holly</creatorcontrib><title>Determining the predictive value of Read codes to identify congenital cardiac malformations in the UK Clinical Practice Research Datalink</title><title>Pharmacoepidemiology and drug safety</title><addtitle>Pharmacoepidemiol Drug Saf</addtitle><description>ABSTRACT
Purposes
The purposes of this study were to determine (i) the positive predictive value (PPV) of multiple Read codes used to identify congenital cardiac malformation (CCM) cases in the UK Clinical Practice Research Datalink (CPRD); (ii) the accuracy of the diagnosis date; and (iii) the source of information that the general practitioners (GPs) use for validating the diagnosis suggested by the code.
Methods
Eight hundred eighty‐eight records with Read diagnostic and procedures codes for CCM, between January 1996 and November 2010, were identified from CPRD. Questionnaires were sent to GPs to verify the diagnoses and date of the code‐identified events.
Results
A total of 719 questionnaires were returned (81% response rate). The PPV of the CCM codes was 93% (670/719). Thirty‐one percent of cases had a different event date than the one recorded in the electronic medical record (EMR); 10% of these differing dates were within 30 days of the code‐identified CCM date. GPs used a variety of data sources to confirm CCM diagnoses. Although the EMR was the most frequently used data source (70%), 66% reported using consultation letters, 9% reported using clinical notes or paper charts, and 35% of GPs reported using the hospital record to confirm the CCM diagnosis.
Conclusions
Clinical Practice Research Datalink Read codes for CCMs have 93% PPV and most likely point to true cases. However, the accuracy of diagnosis dates and the age at diagnosis may not be as reliable. The findings of this study indicate that GPs use information beyond what is available for researchers in the EMR to confirm clinical diagnoses when responding to validation questionnaires. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.</description><subject>Age Factors</subject><subject>Biological and medical sciences</subject><subject>Cardiovascular disease</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Clinical Coding</subject><subject>Clinical medicine</subject><subject>Clinical Practice Research Datalink</subject><subject>Clinical trial. Drug monitoring</subject><subject>Codes</subject><subject>congenital abnormalities</subject><subject>Databases, Factual - statistics & numerical data</subject><subject>Electronic Health Records - statistics & numerical data</subject><subject>General pharmacology</subject><subject>General Practice - methods</subject><subject>General Practitioners - statistics & numerical data</subject><subject>heart defects</subject><subject>Heart Defects, Congenital - diagnosis</subject><subject>Humans</subject><subject>Infant</subject><subject>Medical diagnosis</subject><subject>Medical sciences</subject><subject>pharmacoepidemiology</subject><subject>Pharmacology. Drug treatments</subject><subject>Predictive Value of Tests</subject><subject>Questionnaires</subject><subject>Read/OXMIS codes</subject><subject>Reproducibility of Results</subject><subject>Surveys and Questionnaires</subject><subject>United Kingdom</subject><subject>validation of congenital cardiac malformation</subject><issn>1053-8569</issn><issn>1099-1557</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kd1uFCEYhidGY2s18QoMiTHxZCrM8DMcml3tGpvaWKuHhIWPlnYGVpip7iV417J2bBMTjyDw8LzAW1XPCT4kGDdvNjYftoyQB9U-wVLWhDHxcDdnbd0xLveqJzlfYVz2JH1c7TW0nJKS7Ve_ljBCGnzw4QKNl4A2Caw3o78BdKP7CVB06DNoi0y0kNEYkbcQRu-2ZSVcQPCj7pHRyXpt0KB7F9OgRx9DRj78UZ5_RIu-JJgCniZd5AaKM4NO5hItdRH4cP20euR0n-HZPB5U5-_ffVms6uNPRx8Wb49rQ4kgtWNgrRGOcCc7gaVby7ZZS24sZbjDnHQdFppazMHpRmDu2NqW52IjteC0aw-q17feTYrfJ8ijGnw20Pc6QJyyIpSzjhNOZUFf_oNexSmFcrtC0bbtcEPkvdCkmHMCpzbJDzptFcFqV48q9ahdPQV9MQun9QD2DvzbRwFezYDO5btc0sH4fM8JKbpW0sLVt9wP38P2v4HqdHk2B8-8zyP8vON1ulZctIKpbydHarX4enImVkLR9jdTC7U6</recordid><startdate>201311</startdate><enddate>201311</enddate><creator>Hammad, Tarek A.</creator><creator>Margulis, Andrea V.</creator><creator>Ding, Yulan</creator><creator>Strazzeri, Marian M.</creator><creator>Epperly, Holly</creator><general>Blackwell Publishing Ltd</general><general>Wiley</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope><scope>K9.</scope><scope>7X8</scope></search><sort><creationdate>201311</creationdate><title>Determining the predictive value of Read codes to identify congenital cardiac malformations in the UK Clinical Practice Research Datalink</title><author>Hammad, Tarek A. ; Margulis, Andrea V. ; Ding, Yulan ; Strazzeri, Marian M. ; Epperly, Holly</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4171-f5eddc7f16f98709fb932b96cd45080618807a4d06efa2706f5bd4000c9a76483</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Age Factors</topic><topic>Biological and medical sciences</topic><topic>Cardiovascular disease</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Clinical Coding</topic><topic>Clinical medicine</topic><topic>Clinical Practice Research Datalink</topic><topic>Clinical trial. Drug monitoring</topic><topic>Codes</topic><topic>congenital abnormalities</topic><topic>Databases, Factual - statistics & numerical data</topic><topic>Electronic Health Records - statistics & numerical data</topic><topic>General pharmacology</topic><topic>General Practice - methods</topic><topic>General Practitioners - statistics & numerical data</topic><topic>heart defects</topic><topic>Heart Defects, Congenital - diagnosis</topic><topic>Humans</topic><topic>Infant</topic><topic>Medical diagnosis</topic><topic>Medical sciences</topic><topic>pharmacoepidemiology</topic><topic>Pharmacology. Drug treatments</topic><topic>Predictive Value of Tests</topic><topic>Questionnaires</topic><topic>Read/OXMIS codes</topic><topic>Reproducibility of Results</topic><topic>Surveys and Questionnaires</topic><topic>United Kingdom</topic><topic>validation of congenital cardiac malformation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hammad, Tarek A.</creatorcontrib><creatorcontrib>Margulis, Andrea V.</creatorcontrib><creatorcontrib>Ding, Yulan</creatorcontrib><creatorcontrib>Strazzeri, Marian M.</creatorcontrib><creatorcontrib>Epperly, Holly</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Pharmacoepidemiology and drug safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hammad, Tarek A.</au><au>Margulis, Andrea V.</au><au>Ding, Yulan</au><au>Strazzeri, Marian M.</au><au>Epperly, Holly</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Determining the predictive value of Read codes to identify congenital cardiac malformations in the UK Clinical Practice Research Datalink</atitle><jtitle>Pharmacoepidemiology and drug safety</jtitle><addtitle>Pharmacoepidemiol Drug Saf</addtitle><date>2013-11</date><risdate>2013</risdate><volume>22</volume><issue>11</issue><spage>1233</spage><epage>1238</epage><pages>1233-1238</pages><issn>1053-8569</issn><eissn>1099-1557</eissn><coden>PDSAEA</coden><abstract>ABSTRACT
Purposes
The purposes of this study were to determine (i) the positive predictive value (PPV) of multiple Read codes used to identify congenital cardiac malformation (CCM) cases in the UK Clinical Practice Research Datalink (CPRD); (ii) the accuracy of the diagnosis date; and (iii) the source of information that the general practitioners (GPs) use for validating the diagnosis suggested by the code.
Methods
Eight hundred eighty‐eight records with Read diagnostic and procedures codes for CCM, between January 1996 and November 2010, were identified from CPRD. Questionnaires were sent to GPs to verify the diagnoses and date of the code‐identified events.
Results
A total of 719 questionnaires were returned (81% response rate). The PPV of the CCM codes was 93% (670/719). Thirty‐one percent of cases had a different event date than the one recorded in the electronic medical record (EMR); 10% of these differing dates were within 30 days of the code‐identified CCM date. GPs used a variety of data sources to confirm CCM diagnoses. Although the EMR was the most frequently used data source (70%), 66% reported using consultation letters, 9% reported using clinical notes or paper charts, and 35% of GPs reported using the hospital record to confirm the CCM diagnosis.
Conclusions
Clinical Practice Research Datalink Read codes for CCMs have 93% PPV and most likely point to true cases. However, the accuracy of diagnosis dates and the age at diagnosis may not be as reliable. The findings of this study indicate that GPs use information beyond what is available for researchers in the EMR to confirm clinical diagnoses when responding to validation questionnaires. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.</abstract><cop>Chichester</cop><pub>Blackwell Publishing Ltd</pub><pmid>24002995</pmid><doi>10.1002/pds.3511</doi><tpages>6</tpages></addata></record> |
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subjects | Age Factors Biological and medical sciences Cardiovascular disease Child Child, Preschool Clinical Coding Clinical medicine Clinical Practice Research Datalink Clinical trial. Drug monitoring Codes congenital abnormalities Databases, Factual - statistics & numerical data Electronic Health Records - statistics & numerical data General pharmacology General Practice - methods General Practitioners - statistics & numerical data heart defects Heart Defects, Congenital - diagnosis Humans Infant Medical diagnosis Medical sciences pharmacoepidemiology Pharmacology. Drug treatments Predictive Value of Tests Questionnaires Read/OXMIS codes Reproducibility of Results Surveys and Questionnaires United Kingdom validation of congenital cardiac malformation |
title | Determining the predictive value of Read codes to identify congenital cardiac malformations in the UK Clinical Practice Research Datalink |
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