Limited Accuracy of Administrative Data for the Identification and Classification of Adult Congenital Heart Disease

Abstract

BackgroundAdministrative data sets utilize billing codes for research and quality assessment. Previous data suggest that such codes can accurately identify adults with congenital heart disease (CHD) in the cardiology clinic, but their use has yet to be validated in a larger population. Methods and ResultsAll administrative codes from an entire health system were queried for a single year. Adults with a CHD diagnosis code (International Classification of Diseases, Ninth Revision, (ICD‐9) codes 745–747) defined the cohort. A previously validated hierarchical algorithm was used to identify diagnoses and classify patients. All charts were reviewed to determine a gold standard diagnosis, and comparisons were made to determine accuracy. Of 2399 individuals identified, 206 had no CHD by the algorithm or were deemed to have an uncertain diagnosis after provider review. Of the remaining 2193, only 1069 had a confirmed CHD diagnosis, yielding overall accuracy of 48.7% (95% confidence interval, 47–51%). When limited to those with moderate or complex disease (n=484), accuracy was 77% (95% confidence interval, 74–81%). Among those with CHD, misclassification occurred in 23%. The discriminative ability of the hierarchical algorithm (C statistic: 0.79; 95% confidence interval, 0.77–0.80) improved further with the addition of age, encounter type, and provider (C statistic: 0.89; 95% confidence interval, 0.88–0.90). ConclusionsICD codes from an entire healthcare system were frequently erroneous in detecting and classifying CHD patients. Accuracy was higher for those with moderate or complex disease or when coupled with other data. These findings should be taken into account in future studies utilizing administrative data sets in CHD.

Keywords

• administrative data
• congenital heart disease
• diagnosis
• diagnosis code