Validation of a Case-Finding Algorithm for Hidradenitis Suppurativa Using Administrative Coding from a Clinical Database

Abstract

BACKGROUND: Requisite to the application of clinical databases for observational research in hidradenitis suppurativa (HS) is the identification of an accurate case cohort. OBJECTIVE: To assess the validity of utilizing administrative codes to establish the HS cohort from a large clinical database. METHODS: In this retrospective study using chart review as the reference standard, we calculated several estimates of the diagnostic accuracy of at least 1 ICD-9 code for HS. RESULTS: Estimates of the diagnostic accuracy of at least 1 ICD-9 code for HS include sensitivity 100% (95% CI 98-100), specificity 83% (95% CI 77-88), positive predictive value 79% (95% CI 72-85), negative predictive value 100% (95% CI 98-100), accuracy 90% (95% CI 86-93), and kappa statistic 79% (95% CI 73-86). CONCLUSION: The case-finding algorithm employing at least 1 ICD-9 code for HS provides balance in achieving accuracy and adequate power, both necessary in the evaluation of a less common disease and its potential association with uncommon or even rare events.