Optimizing Algorithms to Identify Parkinson's Disease Cases Within an Administrative Database
Identifieur interne : 002E69 ( Main/Merge ); précédent : 002E68; suivant : 002E70Optimizing Algorithms to Identify Parkinson's Disease Cases Within an Administrative Database
Auteurs : Nicholas R. Szumski [États-Unis] ; Eric M. Cheng [États-Unis]Source :
- Movement disorders [ 0885-3185 ] ; 2009.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Base de données.
English descriptors
- KwdEn :
Abstract
Patients assigned the diagnostic ICD-9-CM code for Parkinson's disease (PD) in an administrative database may not truly carry that diagnosis because of the various error sources. Improved ability to identify PD cases within databases may facilitate specific research goals. Experienced chart reviewers abstracted the working diagnosis of all 577 patients assigned diagnostic code 332.0 (PD) during 1 year at a VA Healthcare System. We then tested the ability of various algorithms making use of PD and non-PD diagnostic codes, specialty of clinics visited, and medication prescription data to predict the abstracted working diagnosis. Chart review determined 436 (75.6%) patients to be PD or Possibly PD, and 141 (24.4%) to be Not PD. Our tiered consensus algorithm preferentially used data from specialists over non-specialists improved PPV to 83.2% (P = 0.003 vs. baseline). When presence of a PD prescription was an additional criterion, PPV increased further to 88.2% (P = 0.04 vs. without medication criterion), but sensitivity decreased from 87.4 to 77.1% (P = 0.0001). We demonstrate that algorithms provide better identification of PD cases than using a single occurrence of the diagnostic code for PD, and modifications of such algorithms can be tuned to maximize parameters that best meet the goals of a particular database query.
Links toward previous steps (curation, corpus...)
- to stream PascalFrancis, to step Corpus: 001007
- to stream PascalFrancis, to step Curation: 001D12
- to stream PascalFrancis, to step Checkpoint: 000D72
Links to Exploration step
Pascal:09-0094106Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Optimizing Algorithms to Identify Parkinson's Disease Cases Within an Administrative Database</title>
<author><name sortKey="Szumski, Nicholas R" sort="Szumski, Nicholas R" uniqKey="Szumski N" first="Nicholas R." last="Szumski">Nicholas R. Szumski</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>Department of Neurology, UCLA</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
<affiliation wicri:level="2"><inist:fA14 i1="02"><s1>Southwest Parkinson's Disease Research, Education, and Clinical Center (PADRECC)</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
<affiliation wicri:level="2"><inist:fA14 i1="03"><s1>Department of Neurology, VA Greater Los Angeles Healthcare System</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Cheng, Eric M" sort="Cheng, Eric M" uniqKey="Cheng E" first="Eric M." last="Cheng">Eric M. Cheng</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>Department of Neurology, UCLA</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
<affiliation wicri:level="2"><inist:fA14 i1="02"><s1>Southwest Parkinson's Disease Research, Education, and Clinical Center (PADRECC)</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
<affiliation wicri:level="2"><inist:fA14 i1="03"><s1>Department of Neurology, VA Greater Los Angeles Healthcare System</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">09-0094106</idno>
<date when="2009">2009</date>
<idno type="stanalyst">PASCAL 09-0094106 INIST</idno>
<idno type="RBID">Pascal:09-0094106</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">001007</idno>
<idno type="wicri:Area/PascalFrancis/Curation">001D12</idno>
<idno type="wicri:Area/PascalFrancis/Checkpoint">000D72</idno>
<idno type="wicri:doubleKey">0885-3185:2009:Szumski N:optimizing:algorithms:to</idno>
<idno type="wicri:Area/Main/Merge">002E69</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Optimizing Algorithms to Identify Parkinson's Disease Cases Within an Administrative Database</title>
<author><name sortKey="Szumski, Nicholas R" sort="Szumski, Nicholas R" uniqKey="Szumski N" first="Nicholas R." last="Szumski">Nicholas R. Szumski</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>Department of Neurology, UCLA</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
<affiliation wicri:level="2"><inist:fA14 i1="02"><s1>Southwest Parkinson's Disease Research, Education, and Clinical Center (PADRECC)</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
<affiliation wicri:level="2"><inist:fA14 i1="03"><s1>Department of Neurology, VA Greater Los Angeles Healthcare System</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Cheng, Eric M" sort="Cheng, Eric M" uniqKey="Cheng E" first="Eric M." last="Cheng">Eric M. Cheng</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>Department of Neurology, UCLA</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
<affiliation wicri:level="2"><inist:fA14 i1="02"><s1>Southwest Parkinson's Disease Research, Education, and Clinical Center (PADRECC)</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
<affiliation wicri:level="2"><inist:fA14 i1="03"><s1>Department of Neurology, VA Greater Los Angeles Healthcare System</s1>
<s2>Los Angeles, California</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Californie</region>
</placeName>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">Movement disorders</title>
<title level="j" type="abbreviated">Mov. disord.</title>
<idno type="ISSN">0885-3185</idno>
<imprint><date when="2009">2009</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">Movement disorders</title>
<title level="j" type="abbreviated">Mov. disord.</title>
<idno type="ISSN">0885-3185</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithm</term>
<term>Database</term>
<term>Nervous system diseases</term>
<term>Parkinson disease</term>
<term>Predictive value</term>
<term>Sensitivity</term>
<term>Specificity</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Maladie de Parkinson</term>
<term>Pathologie du système nerveux</term>
<term>Algorithme</term>
<term>Base de données</term>
<term>Valeur prédictive</term>
<term>Sensibilité</term>
<term>Spécificité</term>
</keywords>
<keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Base de données</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Patients assigned the diagnostic ICD-9-CM code for Parkinson's disease (PD) in an administrative database may not truly carry that diagnosis because of the various error sources. Improved ability to identify PD cases within databases may facilitate specific research goals. Experienced chart reviewers abstracted the working diagnosis of all 577 patients assigned diagnostic code 332.0 (PD) during 1 year at a VA Healthcare System. We then tested the ability of various algorithms making use of PD and non-PD diagnostic codes, specialty of clinics visited, and medication prescription data to predict the abstracted working diagnosis. Chart review determined 436 (75.6%) patients to be PD or Possibly PD, and 141 (24.4%) to be Not PD. Our tiered consensus algorithm preferentially used data from specialists over non-specialists improved PPV to 83.2% (P = 0.003 vs. baseline). When presence of a PD prescription was an additional criterion, PPV increased further to 88.2% (P = 0.04 vs. without medication criterion), but sensitivity decreased from 87.4 to 77.1% (P = 0.0001). We demonstrate that algorithms provide better identification of PD cases than using a single occurrence of the diagnostic code for PD, and modifications of such algorithms can be tuned to maximize parameters that best meet the goals of a particular database query.</div>
</front>
</TEI>
<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Californie</li>
</region>
</list>
<tree><country name="États-Unis"><region name="Californie"><name sortKey="Szumski, Nicholas R" sort="Szumski, Nicholas R" uniqKey="Szumski N" first="Nicholas R." last="Szumski">Nicholas R. Szumski</name>
</region>
<name sortKey="Cheng, Eric M" sort="Cheng, Eric M" uniqKey="Cheng E" first="Eric M." last="Cheng">Eric M. Cheng</name>
<name sortKey="Cheng, Eric M" sort="Cheng, Eric M" uniqKey="Cheng E" first="Eric M." last="Cheng">Eric M. Cheng</name>
<name sortKey="Cheng, Eric M" sort="Cheng, Eric M" uniqKey="Cheng E" first="Eric M." last="Cheng">Eric M. Cheng</name>
<name sortKey="Szumski, Nicholas R" sort="Szumski, Nicholas R" uniqKey="Szumski N" first="Nicholas R." last="Szumski">Nicholas R. Szumski</name>
<name sortKey="Szumski, Nicholas R" sort="Szumski, Nicholas R" uniqKey="Szumski N" first="Nicholas R." last="Szumski">Nicholas R. Szumski</name>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Santé/explor/MovDisordV3/Data/Main/Merge
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 002E69 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Merge/biblio.hfd -nk 002E69 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Wicri/Santé |area= MovDisordV3 |flux= Main |étape= Merge |type= RBID |clé= Pascal:09-0094106 |texte= Optimizing Algorithms to Identify Parkinson's Disease Cases Within an Administrative Database }}
![]() | This area was generated with Dilib version V0.6.23. | ![]() |