Development and validation of algorithms for the detection of statin myopathy signals from electronic medical records

TitleDevelopment and validation of algorithms for the detection of statin myopathy signals from electronic medical records
Publication TypeJournal Article
Year of Publication2017
AuthorsChan, SL, Tham, MY, Tan, SH, Loke, C, Foo, B, Fan, Y, Ang, PS, Brunham, LR, Sung, C
JournalClinical Pharmacology and Therapeutics
Volume101
Issue5
Pagination667-674
Date Published01/2017
ISSNPrint: 0009-9236; Online: 1532-6535
Abstract

The purpose of this study was to develop and validate sensitive algorithms to detect hospitalized statin-induced myopathy (SIM) cases from electronic medical records (EMRs). We developed four algorithms on a training set of 31,211 patient records from a large tertiary hospital. We determined the performance of these algorithms against manually curated records. The best algorithm used a combination of elevated creatine kinase (>4× the upper limit of normal (ULN)), discharge summary, diagnosis, and absence of statin in discharge medications. This algorithm achieved a positive predictive value of 52-71% and a sensitivity of 72-78% on two validation sets of >30,000 records each. Using this algorithm, the incidence of SIM was estimated at 0.18%. This algorithm captured three times more rhabdomyolysis cases than spontaneous reports (95% vs. 30% of manually curated gold standard cases). Our results show the potential power of utilizing data and text mining of EMRs to enhance pharmacovigilance activities.

DOI10.1002/cpt.526