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

被引:68
作者
Cozzolino, Francesco [1 ,2 ]
Montedori, Alessandro [1 ]
Abraha, Iosief [1 ,3 ]
Eusebi, Paolo [1 ]
Grisci, Chiara [4 ]
Heymann, Anna Julia [5 ]
Lombardo, Guido [6 ]
Mengoni, Anna [2 ]
Orso, Massimiliano [1 ,2 ]
Ambrosio, Giuseppe [2 ]
机构
[1] Reg Hlth Author Umbria, Hlth Planning Serv, Perugia, Italy
[2] Univ Perugia, Sch Med, Maria Misericordia Hosp, Div Cardiol, Perugia, Italy
[3] Azienda Osped Perugia, Ctr Reg Sangue, Serv Immunotrasfus, Perugia, Italy
[4] Univ Perugia, Sect Publ Hlth, Dept Expt Med, Perugia, Italy
[5] Ist Zooprofilatt Sperimentale Umbria & Marche Tog, Perugia, Italy
[6] Univ Perugia, Dept Surg & Biomed Sci, Perugia, Italy
来源
PLOS ONE | 2019年 / 14卷 / 07期
关键词
MYOCARDIAL-INFARCTION; IMPACT; DRUGS;
D O I
10.1371/journal.pone.0218919
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background 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. Methods 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. Results 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, 8397%), 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%). Conclusion 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.
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页数:13
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