OMOP has built a library of methods, developed for the OMOP Common Data Model, to address the analysis problems of Monitoring of Health Outcomes of Interest and Identification of Non-Specified Conditions. These methods are tested across the OMOP Data Community. These methods are available under the Apache public license. If you would like to contribute to the methods, please contact OMOP by adding a new comment below.
In 2011, the OMOP completed its originally defined set of research experiments to empirically evaluate the performance of alternative methods on their ability to identify true associations between drugs and outcomes. This initial research highlighted opportunities for methods enhancement. The links below contain source code and instructions on how to execute these updated methods.
The links below contain source code and instructions on how to execute these methods for the OMOP performance measurement experiments.
Regularized Identification of Cohorts (RICO) - ProSanos Corporation