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

. 2014 Mar 28;9(3):e92286. doi: 10.1371/journal.pone.0092286. eCollection 2014. Validity of myocardial infarction diagnoses in administrative databases: a systematic review

Affiliations

¹ Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada; Arthritis Research Centre of Canada, Richmond, British Columbia, Canada.
² Arthritis Research Centre of Canada, Richmond, British Columbia, Canada; Division of Rheumatology, Department of Medicine. University of British Columbia, Vancouver, British Columbia, Canada; Co-chair, Cardiovascular Committee of the CANRAD Network, Richmond, British Columbia, Canada.
³ Arthritis Research Centre of Canada, Richmond, British Columbia, Canada; Division of Rheumatology, Department of Medicine. University of British Columbia, Vancouver, British Columbia, Canada.

PMID: 24682186
PMCID: PMC3969323
DOI: 10.1371/journal.pone.0092286

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

Natalie McCormick et al. PLoS One. 2014.

. 2014 Mar 28;9(3):e92286. doi: 10.1371/journal.pone.0092286. eCollection 2014. Affiliations

¹ Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada; Arthritis Research Centre of Canada, Richmond, British Columbia, Canada.
² Arthritis Research Centre of Canada, Richmond, British Columbia, Canada; Division of Rheumatology, Department of Medicine. University of British Columbia, Vancouver, British Columbia, Canada; Co-chair, Cardiovascular Committee of the CANRAD Network, Richmond, British Columbia, Canada.
³ Arthritis Research Centre of Canada, Richmond, British Columbia, Canada; Division of Rheumatology, Department of Medicine. University of British Columbia, Vancouver, British Columbia, Canada.

PMID: 24682186
PMCID: PMC3969323
DOI: 10.1371/journal.pone.0092286

Item in Clipboard

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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Conflict of interest statement

Competing Interests: VB is the sole proprietor of EpiSolutions Consultancy Services. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

Figures
Figure 1. Preferred Reporting Items for Systematic…

Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-style Flowchart of Study Selection…
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 2. Positive Predictive Values of Myocardial…

Figure 2. Positive Predictive Values of Myocardial Infarction Diagnoses (versus “Definite” or “Definite/Probable/Possible MI”, or…
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.