POSE Phase I: Observational health data sciences and informatics (OHDSI) open source ecosystem (OSE) development

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This project is funded by Pathways to Enable Open-Source Ecosystems (POSE) which seeks to harness the power of open-source development for the creation of new technology solutions to problems of national and societal importance. Observational Health Data Sciences and Informatics (OHDSI) is multi-stakeholder, interdisciplinary, open-science collaborative to capitalize on the value of health data using large-scale analytics. OHDSI’s mission is to improve health by empowering a community to collaboratively generate the evidence that promotes better health decisions and care. OHDSI collaborates on many aspects of the journey from data to evidence, including open community data standards, open-source software development, open methodological research, and open network clinical research. The core of OHDSI is about using a standard based common data model to create computable and reproducible analysis on electronic health data. Electronic health data has privacy protections and restrictions on data sharing. OHDSI has developed methods to convert local proprietary electronic medical record data into a common format thereby allowing the ecosystem to share code (analysis) between organizations and aggregating only result data. The OHDSI community has grown since its inception in 2014 to include 3000 researchers in 70 countries around the world. The community has created a research network of 810 million patient records across 300+ sites in a common data format. There are hundreds of OHDSI-affiliated projects on github using the common data model. The goal of this project is to mature the open source governance in the OHDSI ecosystem and create an “OHDSI Way”. OHDSI currently hosts over 200 open source repositories on github with 13 million lines of code written by over 400 contributors. The specific aims of the project are to formalize open source governance activities, develop contributor onramp programs, host developers conferences, and develop metrics and a dashboard to evaluate the health and maturity of the open source projects. The project will help the OHDSI community make a broader impact into the field of observational research in two ways. The first is by enabling stable and secure software that can be used to preform analytics inside health systems and industry with a low deployment and maintenance costs. The second is by enabling greater extensibility of the ODHSI ecosystem to make the software easier to modify and extend for new purposes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.