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Activity Number: 99 - The OHDSI Collaboration: Generating Reliable Evidence from Large-Scale Healthcare Data
Type: Invited
Date/Time: Monday, August 3, 2020 : 1:00 PM to 2:50 PM
Sponsor: Council of Chapters
Abstract #309382
Title: The OHDSI Collaboration: Mission, Accomplishments, and the Road Ahead
Author(s): Patrick Ryan*
Companies: Janssen Research and Development
Keywords: Causal inference; Observational study; Healthcare; Predictive modeling
Abstract:

Observational Health Data Sciences and Informatics (OHDSI; ohdsi.org) is an open science community that aims to improve health by empowering the community to collaboratively generate the evidence that promotes better health decisions and better care. OHDSI conducts methodological research to establish scientific best practices for the appropriate use of observational health data, develops open-source analytics software that codify these practices into consistent, transparent, reproducible solutions, and applies these tools and practices to clinical questions to generate evidence that can guide healthcare policy and patient care. OHDSI has focused on three analytic use cases: clinical characterization, population-level effect estimation, and patient-level prediction. The OHDSI community has adopted the OMOP Common Data Model (CDM) as an open community standard to harmonize the structure, content and semantics of patient-level observational data and to assemble a distributed data network; across the OHDSI community, over 130 distinct databases from 19 countries collectively covering more than 500 million patients. This talk will describe prior progress and the road ahead.


Authors who are presenting talks have a * after their name.

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