An upcoming area of interest for biopharmaceutical product development, as well as for public health and healthcare system evaluation, is the study of medical outcomes in so-called 'real world data'. This data can originate from electronic medical records in hospitals, general practitioners, pharmacies, insurance companies and even directly from patients, using forums or mobile health apps.
One of the largest open source initiatives for the standardisation and analysis for this type of data is called OHDSI: Observational Health Data Sciences and Informatics. OHDSI leverages the OMOP data model for observational data, and provides data analysis tools for a broad range of use cases. This talk will focus on a number of examples of the application of the OHDSI tooling for observational research, as well as provide a broader introduction of the topic and the use of open source software in pharmaceutical and healthcare context.