We recently profiled HADES — the Health Analytics Data-to-Evidence Suite — in an OHDSI feature story to highlight its impact in observational health research both inside and outside the OHDSI community.
Led by @schuemie, a small core of the community maintains a set of 20 open-source R packages for large scale analytics, including population characterization, population-level causal effect estimation, and patient-level prediction, as well as supporting packages that are critical throughout the journey of observational research. Eight of the 20 packages have matured to be additionally released on CRAN, and they have been downloaded more than 200,000 times combined.
As the reliance on HADES grows, so does the need for additional support throughout our community. Within the feature, you will see a variety of ways that you can impact our open-source tools, from development to testing to documentation, just to name a few. Please give it a read and offer your expertise so that we can ensure future success!