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dc.contributor.authorCutrona, Sarah L.
dc.contributor.authorToh, Sengwee
dc.contributor.authorIyer, Aarthi
dc.contributor.authorFoy, Sarah
dc.contributor.authorDaniel, Gregory W.
dc.contributor.authorNair, Vinit P.
dc.contributor.authorNg, Daniel
dc.contributor.authorButler, Melissa G.
dc.contributor.authorBoudreau, Denise M.
dc.contributor.authorForrow, Susan
dc.contributor.authorGoldberg, Robert J.
dc.contributor.authorGore, Joel M.
dc.contributor.authorMcManus, David D.
dc.contributor.authorRacoosin, Judith A.
dc.contributor.authorGurwitz, Jerry H.
dc.date2022-08-11T08:09:23.000
dc.date.accessioned2022-08-23T16:29:10Z
dc.date.available2022-08-23T16:29:10Z
dc.date.issued2013-01-01
dc.date.submitted2012-08-22
dc.identifier.citation<p>Pharmacoepidemiol Drug Saf. 2013 Jan;22(1):40-54. doi: 10.1002/pds.3310. <a href="http://dx.doi.org/10.1002/pds.3310" target="_blank">Link to article on publisher's site</a></p>
dc.identifier.issn1099-1557
dc.identifier.doi10.1002/pds.3310
dc.identifier.pmid22745038
dc.identifier.urihttp://hdl.handle.net/20.500.14038/37181
dc.description.abstractPURPOSE: To validate an algorithm based upon International Classification of Diseases, 9(th) revision, Clinical Modification (ICD-9-CM) codes for acute myocardial infarction (AMI) documented within the Mini-Sentinel Distributed Database (MSDD). METHODS: Using an ICD-9-CM-based algorithm (hospitalized patients with 410.x0 or 410.x1 in primary position), we identified a random sample of potential cases of AMI in 2009 from four Data Partners participating in the Mini-Sentinel Program. Cardiologist reviewers used information abstracted from hospital records to assess the likelihood of an AMI diagnosis based on criteria from the Joint European Society of Cardiology and American College of Cardiology Global Task Force. Positive predictive values (PPVs) of the ICD-9-based algorithm were calculated. RESULTS: Of the 153 potential cases of AMI identified, hospital records for 143 (93%) were retrieved and abstracted. Overall, the PPV was 86.0% (95% confidence interval; 79.2%, 91.2%). PPVs ranged from 76.3% to 94.3% across the four Data Partners. CONCLUSIONS: The overall PPV of potential AMI cases, as identified using an ICD-9-CM-based algorithm, may be acceptable for safety surveillance; however, PPVs do vary across Data Partners. This validation effort provides a contemporary estimate of the reliability of this algorithm for use in future surveillance efforts conducted using the Food and Drug Administration's MSDD. Copyright © 2012 John Wiley & Sons, Ltd.
dc.language.isoen_US
dc.publisherWiley
dc.relation<p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=22745038&dopt=Abstract">Link to article in PubMed</a></p>
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3601831/
dc.subjectMyocardial Infarction
dc.subjectAlgorithms
dc.subjectOutcome Assessment (Health Care)
dc.subjectUMCCTS funding
dc.subjectCardiology
dc.subjectCardiovascular Diseases
dc.subjectHealth Services Administration
dc.subjectHealth Services Research
dc.titleValidation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program
dc.typeJournal Article
dc.source.journaltitlePharmacoepidemiology and drug safety
dc.source.volume22
dc.source.issue1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/meyers_pp/591
dc.identifier.contextkey3247948
html.description.abstract<p>PURPOSE: To validate an algorithm based upon International Classification of Diseases, 9(th) revision, Clinical Modification (ICD-9-CM) codes for acute myocardial infarction (AMI) documented within the Mini-Sentinel Distributed Database (MSDD).</p> <p>METHODS: Using an ICD-9-CM-based algorithm (hospitalized patients with 410.x0 or 410.x1 in primary position), we identified a random sample of potential cases of AMI in 2009 from four Data Partners participating in the Mini-Sentinel Program. Cardiologist reviewers used information abstracted from hospital records to assess the likelihood of an AMI diagnosis based on criteria from the Joint European Society of Cardiology and American College of Cardiology Global Task Force. Positive predictive values (PPVs) of the ICD-9-based algorithm were calculated.</p> <p>RESULTS: Of the 153 potential cases of AMI identified, hospital records for 143 (93%) were retrieved and abstracted. Overall, the PPV was 86.0% (95% confidence interval; 79.2%, 91.2%). PPVs ranged from 76.3% to 94.3% across the four Data Partners.</p> <p>CONCLUSIONS: The overall PPV of potential AMI cases, as identified using an ICD-9-CM-based algorithm, may be acceptable for safety surveillance; however, PPVs do vary across Data Partners. This validation effort provides a contemporary estimate of the reliability of this algorithm for use in future surveillance efforts conducted using the Food and Drug Administration's MSDD.</p> <p>Copyright © 2012 John Wiley & Sons, Ltd.</p>
dc.identifier.submissionpathmeyers_pp/591
dc.contributor.departmentDepartment of Medicine, Division of Cardiovascular Medicine
dc.contributor.departmentMeyers Primary Care Institute
dc.contributor.departmentDepartment of Medicine, Division of Geriatric Medicine
dc.source.pages40-54


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