D. R. Killick

Objectives To use text mining approaches to identify instances of suspected adverse drug reactions recorded in first opinion veterinary free‐text clinical narratives, and to evaluate whether these were also reported to either the Veterinary Medicines Directorate or the relevant Marketing Authorisation holder in order to derive an estimate of the suspected adverse drug reaction (sADR) minimum under‐reporting rate. To characterise sADR reports and explore whether particular features are associated with report submission. Materials and Methods Two regular expressions were developed to identify mentions of “adverse drug reactions” and “side effects” in the free‐text clinical narratives of electronic health records contained within the Small Animal Veterinary Surveillance Network database. Consultations containing a match for the developed regular expressions were manually reviewed for inclusion and further classified to determine the suspected product, seriousness and expectedness of the event, and an indication of whether the event had been reported. The associations between event characteristics and reporting were explored using Fisher's exact tests. Results A total of 10,565 records were manually reviewed from which 827 sADRs were identified. Approximately 90% of these sADRs were not recorded as reported. Suspected adverse drug reactions that were not considered “expected” were recorded as reported more frequently than “expected” sADRs. However, clinical severity did not appear to impact on whether there was a record of reporting. Clinical Significance This is the first estimate of under reporting sADRs based on real world evidence from veterinary clinical records. The under‐reporting rate implied by this study highlights that further interventions are required to improve reporting rate within the veterinary profession in order to support pharmacovigilance activities and improve drug safety.