Purpose: The aim of this study is to determine (i) the positive predictive value (PPV) of an algorithm using clinical codes to identify incident glaucoma and cataract events in the Clinical Practice Research Datalink (CPRD) and (ii) the ability to capture the correct timing of these clinical events.
Methods: A total of 21,339 and 5349 potential cataract and glaucoma cases, respectively, were identified in CPRD between 1 January 1990 and 31 December 2010. Questionnaires were sent to the general practitioners (GP) of 1169 (5.5%) cataract and 1163 (21.7%) glaucoma cases for validation. GPs were asked to verify the diagnosis and the timing of the diagnosis and to provide other supporting information.
Results: A total of 986 (84.3%) valid cataract questionnaires and 863 (74.2%) glaucoma questionnaires were completed. 92.1% and 92.4% of these used information beyond EMR to verify the diagnosis. Cataract and glaucoma diagnoses were confirmed in the large majority of the cases. The PPV (95% CI) of the cataract and glaucoma Read code algorithm were 92.0% (90.3-93.7%) and 84.1% (81.7-86.6%), respectively. However, timing of diagnosis was incorrect for a substantial proportion of the cases (20.3% and 32.8% of the cataract and glaucoma cases, respectively) among whom 30.4% and 49.2% had discrepancies in diagnosis timing greater than 1 year.
Conclusions: High PPV suggests that the algorithms based on the clinical Read codes are sufficient to identify the cataract and glaucoma cases in CPRD. However, these codes alone may not be able to accurately identify the timing of the diagnosis of these eye disorders. Ltd.
Keywords: clinical practice research datalink; eye disorders; pharmacoepidemiology; read codes; validation of cataract; validation of glaucoma.
Copyright © 2014 John Wiley & Sons, Ltd.