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Healthcare delivery and health outcomes of patients could significantly improve if the different electronic health systems of medical institutions were interoperable, that is if they could exchange and combine their data in a meaningful way. In addition, patients are increasingly becoming active sources of data with the growing use of health apps. This valuable information should not be lost, but rather be integrated with the patients’ data in an open platform approach where the distance between caregiver and patient is reduced. Charité Universitätsmedizin Berlin and Berlin Institute of Health (BIH) are members of HiGHmed, a German consortium where eight university hospitals have agreed to the cross-institutional data exchange through novel medical informatics solutions. In this paper, we describe our approach to improve interoperability for the use case Infection Control of the HiGHmed project. Starting from the openEHR standard, we performed a syntactic mapping to the recommended standard and to the . FHIR enables fast exchange of data thanks to the discrete data elements into which information is organized, and OMOP CDM offers a data model specific for population-level analyses. Mapping is essential to identify which data have their correspondent elements in a different data model and can thus be converted into another standard without loss of information. As expected, not all openEHR and FHIR information could be mapped to OMOP CDM as many patient-level data are not important for population-level analysis. However, overall, mapping for the analyzed dataset was performed without major issues and we believe the use case will be able to exploit the advantages of the selected standards.