In this module you will gain deeper insights into defining phenotypes, characterising and evaluating using OHDSI tools, Cohort Diagnostics, PheValuator, and ATLAS. In a stepwise approach, you will be guided in how to use the various R tools, how Cohort Diagnostics can support characterising a cohort, evaluating its attributes and potential flaws. Understanding the rationale … Read more
In this module you will gain deeper insights into patient prediction modelling using OHDSI tools, in particular ATLAS, and focusing on: Defining prediction questions Identifying useful prediction questions of most relevance to prediction modelling Developing prediction models Evaluating prediction models Presenting prediction models This course was originally delivered in a group setting but has been adapted … Read more
This course describes the infrastructure and tools used to work with patient-level data converted to the OMOP Common Data Model (CDM). Within this course we will cover the process for installing and configuring the OHDSI’s WebAPI and Atlas tools. OHDSI’s WebAPI is a Java-based application that provides a web-based application programming interface (API) for standardized … Read more
This course describes Extract, Transform, and Load (ETL) processes to take your database from raw observational data to the OMOP Common Data Model. Steps 1 and 2 will focus on the tools available for designing ETL logic in a way to communicate to a developer how source data should be handled during conversion to the OMOP Common … Read more
In this module you will be able to gain deeper insights into population-level effect estimation. We cover one specific type of population-level effect estimation method for generating clinical evidence: comparative cohort studies. The course presents a framework for formulating comparative effect research questions and discusses what makes good and bad questions. It furthermore describes how … Read more
The aim of the EHDEN foundation course is to explain first and foremost what the EHDEN project aims to achieve, how it will do this and what the final result will be. However, no project stands alone and therefore we provide more context on how EU research is being done, why real world evidence is … Read more
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