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Cited by 262Medical Coding and Health InformationAcute Myocardial Infarction ResearchArtificial Intelligence in Healthcare

The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.

Validity of myocardial infarction diagnoses in administrative databases: a systematic review.

Open access
McCormick, Natalie, Lacaille, Diane, Bhole, Vidula, Avina-Zubieta, J. Antonio·2014·PLoS ONE
DOI 10.1371/journal.pone.0092286PMC PMC3969323
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Abstract

BACKGROUND: Though administrative databases are increasingly being used for research related to myocardial infarction (MI), the validity of MI diagnoses in these databases has never been synthesized on a large scale. OBJECTIVE: To conduct the first systematic review of studies reporting on the validity of diagnostic codes for identifying MI in administrative data. METHODS: MEDLINE and EMBASE were searched (inception to November 2010) for studies: (a) Using administrative data to identify MI; or (b) Evaluating the validity of MI codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value (PPV), negative predictive value, or Kappa scores) for MI, or data sufficient for their calculation. Additonal articles were located by handsearch (up to February 2011) of original papers. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. RESULTS: Thirty studies published from 1984-2010 were included; most assessed codes from the International Classification of Diseases (ICD)-9th revision. Sensitivity and specificity of hospitalization data for identifying MI in most [≥50%] studies was ≥86%, and PPV in most studies was ≥93%. The PPV was higher in the more-recent studies, and lower when criteria that do not incorporate cardiac troponin levels (such as the MONICA) were employed as the gold standard. MI as a cause-of-death on death certificates also demonstrated lower accuracy, with maximum PPV of 60% (for definite MI). CONCLUSIONS: Hospitalization data has higher validity and hence can be used to identify MI, but the accuracy of MI as a cause-of-death on death certificates is suboptimal, and more studies are needed on the validity of ICD-10 codes. When using administrative data for research purposes, authors should recognize these factors and avoid using vital statistics data if hospitalization data is not available to confirm deaths from MI.

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Figure 1 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-style Flowchart of Study Selection and Review. ICD = International Classification of Diseases; MI = myocardial infarction.
Figure 1 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-style Flowchart of Study Selection and Review. ICD = International Classification of Diseases; MI = myocardial infarction.CC BY · PubMed Central
Figure 2 Positive Predictive Values of Myocardial Infarction Diagnoses (versus “Definite” or “Definite/Probable/Possible MI”, or parameters unspecified). The positive predictive values (PPV's) and 95% confidence intervals (where reported) from studies that validated myocardial infarction (MI) diagnoses in hospitalization data, and included a formal set of diagnostic criteria in the reference standard, are ordered left-to-right by publication year of the study (with the earliest-published study on the far left). The PPV's are also stratified by whether cardiac troponin testing was incorporated in the diagnostic criteria. Illustrated in Panel A are the PPV's calculated when the coded diagnoses were compared to the stricter parameter of “Definite MI”, and the PPV's for which no parameter was specified. Illustrated in Panel B are the PPV's calculated when the coded diagnoses were compared to the broader parameter of “Definite and Probable or Possible MI”, along with the same PPV's in Panel A for which no parameter was specified.
Figure 2 Positive Predictive Values of Myocardial Infarction Diagnoses (versus “Definite” or “Definite/Probable/Possible MI”, or parameters unspecified). The positive predictive values (PPV's) and 95% confidence intervals (where reported) from studies that validated myocardial infarction (MI) diagnoses in hospitalization data, and included a formal set of diagnostic criteria in the reference standard, are ordered left-to-right by publication year of the study (with the earliest-published study on the far left). The PPV's are also stratified by whether cardiac troponin testing was incorporated in the diagnostic criteria. Illustrated in Panel A are the PPV's calculated when the coded diagnoses were compared to the stricter parameter of “Definite MI”, and the PPV's for which no parameter was specified. Illustrated in Panel B are the PPV's calculated when the coded diagnoses were compared to the broader parameter of “Definite and Probable or Possible MI”, along with the same PPV's in Panel A for which no parameter was specified.CC BY · PubMed Central

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Metadata

Authors
McCormick, N., Lacaille, D., Bhole, V., & Avina-Zubieta, J. A.
Affiliations
University of British Columbia (CA)
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2014-03-28
Volume
9
Issue
3
Pages
e92286
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0092286
PMC
PMC3969323
OpenAlex
W2016940795
Cited by
262
References
73
Citations by year
2026: 18 · 2025: 16 · 2024: 14 · 2023: 12 · 2022: 25 · 2021: 29 · 2020: 36 · 2019: 34 · 2018: 16 · 2017: 30 · 2016: 14 · 2015: 14 · 2014: 3
FWCI
3.06
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
Funders
  • Arthritis Society
  • Canadian Arthritis Network
Topics
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Acute Myocardial Infarction Research
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
Keywords
myocardial infarction, administrative databases, diagnostic validity, ICD-9 codes, ICD-10 codes, hospitalization data, death certificates, causes of death, cardiac troponin, positive predictive value, sensitivity and specificity
MeSH terms
Adult, Aged, Death Certificates, Hospitalization, Humans, Middle Aged, Myocardial Infarction, Sensitivity and Specificity, Databases, Factual, International Classification of Diseases, Young Adult, Clinical Coding

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