ATLAS is a free, publicly available web-based, open-source software application developed by the OHDSI community to support the design and execution of observational analyses to generate real world evidence from patient level observational data. In this course, Patrick Ryan will walk you through the key features of ATLAS and how to use them to design … Read more
This course gives an introduction into the history of the Observational Medical Outcomes Partnership (OMOP) and the birth of Observational Health Data Sciences and Informatics (OHDSI). It highlights OHDSI’s vision as well as how OHDSI is trying to drive the future of observational research through network studies. The course will then move on to understanding … Read more
In this course you will learn how to quickly deploy OHDSI-in-a-Box, which is a single instance implementation of OHDSI tools and sample data for personal learning and training environments. OHDSI-in-a-Box contains SynPUF data in OMOP CDM, an RDBS including query client, WebAPI, ATLAS, R and Python. In the end of the course we optionally introduce … Read more
As an early Christmas gift, we’ve launched not one, but two new courses in the EHDEN Academy! The population-level effect estimation course focuses on the methodology for generating clinical evidence by performing comparative cohort studies. The course presents a framework for formulating comparative effect research questions and discusses what makes good and bad questions. It … Read more
We are pleased to announce that we’ve just launched the next course in the EHDEN Academy, teaching you deeper insights into phenotype definition, characterisation and evaluation, using ATLAS, Cohort Diagnostics and the PheValuator tool. This is a fundamental aspect of the OHDSI framework for conducting observational research. In a stepwise approach, you will be guided … Read more