Quality assessment of antibiotic use data in the Norwegian veterinary prescription register for 2023 - Trishang Udhwani; Kari Grave; Petter Hopp; Kari Olli Helgesen (BMC Veterinary Research)
Abstract Background Antibiotic use data in animals is of interest to understand the development and occurrence of antibiotic resistance from a One Health perspective. Since 2023, it has been mandatory to collect and report data on antibiotic use per animal species or subcategory of species for cattle, pigs, chickens and turkeys in all EU and EEA countries. Norway collects data on use of medicines for animals through the Norwegian Veterinary Prescription Register (VetReg). It is mandatory for veterinarians to report the use of all medicines for food-producing animals and for pharmacies to report to VetReg all medicines dispensed to animal owners for all animal species and to veterinarians. The aim of our study was to evaluate the quality of antibiotic VetReg data for 2023, focusing on the information required to fulfill reporting of use data in accordance with the EU-requirements. The quality attributes, accuracy of data and timeliness of reporting, were evaluated using VetReg data, and completeness was evaluated by comparing VetReg data with sales statistics from wholesalers. Results In general, accuracy varied between the variables and within a variable, depending on whether veterinarians or pharmacies were the data source. For example, 97% of veterinary records included the required subcategory of the animal species, while only 17% of the pharmacy’s records did. Antibiotic use data in VetReg were calculated to cover 85% of the antibiotics sold by wholesaler to pharmacies. Timeliness also varied - i.e. pharmacies reported almost immediately after dispensing, while 29% of veterinary records were not reported within the deadline of seven days. Conclusions Antibiotic use data for animals in Norway in 2023 could be reported to EMA using VetReg data. The data were, however, not fully accurate and complete. This study revealed several specific accuracy issues and issues with timeliness of reporting. These findings provide the basis for targeted quality improvement measures and can be transformed to metrics suitable to track the progress of the ongoing quality improvement work.