Validity of administrative data for the diagnosis of primary sclerosing cholangitis: a population-based study
Article first published online: 9 MAR 2011
© 2011 John Wiley & Sons A/S
Volume 31, Issue 5, pages 712–720, May 2011
How to Cite
Molodecky, N. A., Myers, R. P., Barkema, H. W., Quan, H. and Kaplan, G. G. (2011), Validity of administrative data for the diagnosis of primary sclerosing cholangitis: a population-based study. Liver International, 31: 712–720. doi: 10.1111/j.1478-3231.2011.02484.x
- Issue published online: 3 APR 2011
- Article first published online: 9 MAR 2011
- Received 1 December 2010, Accepted 27 January 2011
- positive predictive value;
- primary sclerosing cholangitis;
Background/Aims: Administrative databases could be useful in studying the epidemiology of primary sclerosing cholangitis (PSC); however, there is no information regarding the validity of the diagnostic code in administrative databases. The aims of this study were to determine the validity of administrative data for a diagnosis of PSC and generate algorithms for the identification of PSC patients.
Methods: The sensitivity (Se) and positive predictive value (PPV) of a PSC diagnosis based on administrative data from 2000 to 2003 were determined through chart review data. Algorithms were developed by considering variables associated with PSC and coding details. A logistic regression model was constructed using covariates associated with PSC. Based on this model, each subject was assigned a probability of having PSC. A cutoff value was selected that maximized the Se and specificity (Sp) of correctly predicting PSC cases.
Results: In the administrative data, the initial Se and PPV were 83.7 and 7.2% respectively. The optimal algorithm included one PSC code and one inflammatory bowel disease code and had Se 56% and PPV 59%. Overall, the algorithms yielded inadequate PPV and Se estimates to identify a cohort of true PSC cases. The predictive model was constructed using six covariates. For this model, the area under the receiver operating characteristic curve was 93.5%. A cutoff of 0.0729 was used, which maximized the Se 81.9% and Sp 90.7%; however, the PPV was 41.0%.
Conclusion: An algorithm for the identification of true PSC cases from administrative data was not possible. We recommend that PSC receives a distinct ICD code from ascending cholangitis.