A systematic review of validated methods for identifying pancreatitis using administrative data

Abstract

To systematically review algorithms identifying cases of pancreatitis in administrative data, with a focus on studies examining algorithm validity. A literature search was conducted using PubMed and the Iowa Drug Information Service database. Reviews were conducted by two investigators identifying studies using data sources from the USA or Canada. These data sources most likely reflect the coding practices of Mini-Sentinel data partners. Eight studies were obtained examining the validity of an algorithm to identify pancreatitis in either hospital or ambulatory medical records or billing databases. The best-performing algorithm was International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 577.0; with a positive predictive value of 60%-80% and a negative predictive value usually greater than 90%. Populations involved in different studies were heterogeneous; age ranges, level of population risk, pancreatitis etiology, and geographic distribution were highly variable. Validation studies find that the principal ICD-9-CM diagnosis code of 577.0 had the best positive predictive value and specificity. Current studies do not support the use of the ICD-9-CM codes 577.1 and 577.2. Databases enhanced with laboratory values at point of care would invariably increase the specificity of existing algorithms.