Adverse Drug Reactions (ADRs) are a crucial public health issue due to the significant health and monetary burden that they can impose. Real-World Data (RWD), e.g., Electronic Health Records, claims data, etc., can support the identification of potentially unknown ADRs and thus, they could provide raw data to mine ADR prevention rules. The PrescIT project aims to create a Clinical Decision Support System (CDSS) for ADR prevention during ePrescription and uses OMOP-CDM as the main data model to mine ADR prevention rules, based on the software stack provided by the OHDSI initiative. This paper presents the deployment of OMOP-CDM infrastructure using the MIMIC-III as a testbed.