A new era of individualized medicine is evolving where novel biomedical discoveries are leading to more effective prevention, treatment, and diagnosis of disease. Although altered phenotypes are one of the most reliable manifestations of altered gene functions, research in extracting, representing, and analyzing phenotype-genotype relationships is still evolving. This project designs, builds and promotes an open-access community infrastructure for standards-based development and sharing of phenotyping algorithms, as well as provide tools and resources for investigators, researchers and their informatics support staff to implement and execute the algorithms on native EHR data.
An applied example of the study’s goal would be a project involving a researcher who would like to extract information from an EHR system about patients who share a set of clinical characteristics (i.e., the phenotype) such as Type 1 diabetes or resistant hypertension. The investigator would have access to standardized tools that can identify relevant cohorts of patients from the EHR and ensure the extracted data is indeed the desired group’s clinical information.
This is a joint project with Vanderbilt University, Mayo Clinic, and Cornell University.
NIH/NIGMS R01 GM105688-01
Weill Cornell Medicine
CHIP collaborators are part of the public, private and nonprofit sectors and have an interest in working toward a world where health outcomes are improved because data is used effectively.Get in Touch