A diagnostic accuracy study validating cardiovascular ICD-9-CM codes in healthcare administrative databases. The Umbria Data-Value Project

• Published in: PloS one Vol. 14; no. 7; p. e0218919
• Main Authors: Cozzolino, Francesco, Montedori, Alessandro, Abraha, Iosief, Eusebi, Paolo, Grisci, Chiara, Heymann, Anna Julia, Lombardo, Guido, Mengoni, Anna, Orso, Massimiliano, Ambrosio, Giuseppe
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 08-07-2019; Public Library of Science (PLoS)
• Subjects: Accuracy; Aged; Aged, 80 and over; Atrial Fibrillation - blood; Atrial Fibrillation - diagnosis; Atrial Fibrillation - epidemiology; Atrial Fibrillation - physiopathology; Biology and Life Sciences; Cardiac arrhythmia; Cardiology; Cardiovascular disease; Cardiovascular diseases; Cardiovascular Diseases - blood; Cardiovascular Diseases - diagnosis; Cardiovascular Diseases - epidemiology; Cardiovascular Diseases - physiopathology; Charts; Chronic obstructive pulmonary disease; Clinical Coding; Codes; Collaboration; Computer and Information Sciences; Confidence intervals; Congestive heart failure; Data Collection; Data Management; Delivery of Health Care; Diagnosis; Diagnostic systems; Epidemiology; Female; Fibrillation; Flutter; Health care; Heart; Heart attack; Heart attacks; Heart failure; Heart Failure - blood; Heart Failure - diagnostic imaging; Heart Failure - epidemiology; Heart Failure - physiopathology; Hospital admission and discharge; Hospitals; Humans; Identification and classification; Information management; International Classification of Diseases; Italy - epidemiology; Male; Medical diagnosis; Medical Records; Medicine; Medicine and Health Sciences; Methods; Middle Aged; Mortality; Myocardial infarction; Myocardial Infarction - blood; Myocardial Infarction - diagnosis; Myocardial Infarction - epidemiology; Myocardial Infarction - physiopathology; Patient Discharge; Patients; Product safety; Research and Analysis Methods; Sensitivity; Systematic review; Troponin - blood; Vibration; Italy
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0218919

Administrative 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.
Data 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.
We 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%).
The 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.