Accuracy of ICD-9 codes in identifying patients with peptic ulcer and gastrointestinal hemorrhage in the regional healthcare administrative database of Umbria.

BACKGROUND: Peptic ulcer is a widespread disease, frequently complicated by perforation and bleeding. Administrative databases are useful tool to perform epidemiological and drug utilization studies, but they need a validation process based on a comparison with the original data contained in the medical charts. Our aim was to evaluate the accuracy of the ICD-9 codes in identifying patients with peptic ulcer and gastrointestinal hemorrhage in the regional administrative database of Umbria. METHODS: The index test of our study was the hospital discharge abstract database of the Umbria region (Italy), while the reference standard was the clinical information collected in the medical charts. The study population were adult patients with a hospital discharge for peptic ulcer or gastrointestinal hemorrhage in the period 2012-2014. A random sample of cases and non-cases was selected and the corresponding medical charts were reviewed. Cases of peptic ulcer were confirmed based on endoscopy, radiology, and surgery, while adjudication of gastrointestinal hemorrhage was based on presence of hematemesis, melena, and rectal bleeding. RESULTS: Overall, we reviewed 445 clinical charts of cases and 80 clinical charts of non-cases. The diagnostic accuracy results were: code 531 (gastric ulcer), sensitivity and NPV 98%, specificity 88%, and PPV 91%; code 532 (duodenal ulcer), sensitivity and NPV 100%, specificity and PPV 98%; code 534 (gastrojejunal ulcer), sensitivity and NPV 100%, specificity 70%, and PPV 45%; code 578 (gastrointestinal hemorrhage), sensitivity 96%, specificity 90%, PPV and NPV 94%. CONCLUSIONS: Our results showed a high level of diagnostic accuracy for most of the codes considered. The ICD-9 code 534 of gastrojejunal ulcer had a lower level of specificity and PPV due to false positives, being mainly misclassifications for coding errors. These validated codes can be used for future epidemiological studies and for health services research.

Validity of cerebrovascular ICD-9-CM codes in healthcare administrative databases. The Umbria Data-Value Project.

BACKGROUND: Validation of administrative databases for cerebrovascular diseases is crucial for epidemiological, outcome, and health services research. The aim of this study was to validate ICD-9 codes for hemorrhagic or ischemic stroke in administrative databases, to use them for a comprehensive assessment of the burden of disease in terms of major outcomes, such as mortality, hospital readmissions, and use of healthcare resources. METHODS: We considered the hospital discharge abstract database of the Umbria Region (890,000 residents). Source population was represented by patients aged >18 discharged from hospital with a diagnosis of hemorrhagic or ischemic stroke between 2012 and 2014 using ICD-9-CM codes in primary position. We randomly selected and reviewed medical charts of cases and non-cases from hospitals. For case ascertainment we considered symptoms and instrumental tests reported in the medical charts. Diagnostic accuracy measures were computed using 2x2 tables. RESULTS: We reviewed 767 medical charts for cases and 78 charts for non-cases. Diagnostic accuracy measures were: subarachnoid hemorrhage: sensitivity (SE) 100% (95% CI: 97%-100%), specificity (SP) 96% (90-99), positive predictive value (PPV) 98% (93-100), negative predictive value (NPV) 100% (95-100); intracerebral hemorrhage: SE 100% (97-100), SP 98% (91-100), PPV 98% (94-100), NPV 100% (95-100); other and unspecified intracranial hemorrhage: SE 100% (97-100), SP 96% (90-99), PPV 98% (93-100), NPV 100% (95-100); ischemic stroke due to occlusion and stenosis of precerebral arteries: SE 99% (94-100), SP 66 (57-75), PPV 70% (61-77), NPV 99% (93-100); occlusion of cerebral arteries: SE 100% (97-100), SP 87% (78-93), PPV 91% (84-95), NPV 100% (95-100); acute, but ill-defined, cerebrovascular disease: SE 100% (97-100), SP 78% (69-86), PPV % 83 (75-89), NPV 100% (95-100). CONCLUSIONS: Case ascertainment for both ischemic and hemorrhagic stroke showed good or high levels of accuracy within the regional healthcare databases in Umbria. This database can confidently be employed for epidemiological, outcome, and health services research related to any type of stroke.

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

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, 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%). 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.