ArticlePloS one2019
A diagnostic accuracy study validating cardiovascular ICD-9-CM codes in healthcare administrative databases. The Umbria Data-Value Project.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 3 of them syntheses that pooled it.
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Who cites it
55 citing papers in PubMed, 3 syntheses or guidelines pooled it.
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- Accuracy of heart failure ascertainment using routinely collected healthcare data: a systematic review and meta-analysis.Systematic reviews · 2024Pooled it
- Risk of incident heart failure after COVID-19 recovery: a systematic review and meta-analysis.Heart failure reviews · 2023Pooled it
- Impact of glp-1 receptor agonists on hospitalization for heart failure and all-cause death in patients with diabetes with and without heart failure: a real-world study.Clinical research in cardiology : official journal of the German Cardiac Society · 2026Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAdministrative healthcare databases are useful and inexpensive tools that can provide a comprehensive assessment of the burden of diseases in terms of major outcomes, such as mortality, hospital readmissions, and use of healthcare resources. However, a crucial issue is the reliability of information gathered. The aim of this study was to validate ICD-9 codes for several major cardiovascular conditions, i.e., acute myocardial infarction (AMI), atrial fibrillation/flutter (AF), and heart failure (HF), in order to use them for epidemiological, outcome, and health services research.
methodsData from the centralised administrative database of the Umbria Region (890,000 residents, located in Central Italy) were considered. Patients with a first hospital discharge for AMI, AF/flutter, and HF, between 2012 and 2014, were identified using ICD-9-CM codes in primary position. A sample of cases and non-cases was randomly selected, and the corresponding medical charts reviewed by specifically trained investigators. For each disease, case ascertainment was based on all clinical, laboratory, and instrumental examinations available in medical charts. Sensitivity, specificity, and predictive values with 95% confidence intervals (CIs), were calculated.
resultsWe reviewed 458 medical charts, 128 for AMI, 127 for AF/flutter, 127 for HF, and 76 of non-cases for each condition. Diagnostic accuracy measures of the original discharge diagnosis were as follows. AMI: sensitivity 98% (95% CI, 94-100%), specificity 91% (95% CI, 83-97%), positive predictive value (PPV) 95% (95% CI, 89-98%), negative predictive value (NPV) 97% (95% CI, 91-100%). AF/flutter: sensitivity 95% (95% CI, 90-98%), specificity 95% (95% CI, 87-99%), PPV 97% (95% CI, 92-99%), NPV 92% (95% CI, 84-97%). HF: sensitivity 96% (95% CI, 91-99%), specificity 90% (95% CI, 81-96%), PPV 94% (95% CI, 88-97%), NPV 93% (95% CI, 85-98%).
conclusionThe case ascertainment for AMI, AF and flutter, and HF, showed a high level of accuracy (≥ 90%). The healthcare administrative database of the Umbria Region can be confidently used for epidemiological, outcome, and health services research.
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