OBJECTIVE: The ESAC project is funded by the European Commission to collect reliable and comparable data on antibiotic consumption in all European countries. The aim of this study is to identify the reimbursement status of antimicrobials in participating countries and to assess its impact on the comparability of utilization data collected in national databases. METHODS: A structured questionnaire was sent to national representatives in all participating EU and applicant countries and obtained data were validated by comprehensive literature search. We limited this pilot analysis to reimbursement rules for uncomplicated acute infection in adult persons (economically active), as co-payment schemes often vary widely, depending on health and social status of patient. RESULTS: Thirty countries participated. Two axes of differentiation were discovered in the reimbursement systems. Firstly, the axis of homogeneity: is the reimbursement rate fixed and identical across and among antibiotic classes or not? Secondly the axis of initial private payment: is the reimbursement system without limitations or does the reimbursement start only above a fixed threshold co-payment (prescription cap) or a threshold co-payment for multiple prescription over a given period? Homogeneity without threshold co-payment was observed most frequently (n=13). Homogeneity, with threshold co-payment was observed in eight countries. In the remaining nine countries reimbursement status differs across antibiotic classes, without reimbursement limitation in six countries, with threshold co-payment in three countries. CONCLUSIONS: In many European countries, claims databases based on dispensed reimbursed medication suffice to record antibiotic usage in a valid way, as all antibiotics are to some extent reimbursed. In the other countries, where not all antibiotics are reimbursed and/or where reimbursement starts only above a threshold co-payment, data from claims databases will not reflect the actual level of utilization and need to be completed with alternative methods of data collection.