Douglas Ruderfer, PhD, and Lisa Bastarache, MS, are investigating if:
- Online Mendelian Inheritance in Man (OMIM)-based clinical descriptions of genetic disease can be translated to electronic health records (EHRs) to more accurately reflect how these diseases are described in real-world clinical data. The idea is that EHR-informed disease descriptions will improve the ability to identify individuals affected by genetic disease.
- Undiagnosed individuals with a genetic disease can be identified using algorithms that detect phenotypic patterns characteristic of the disease in EHR data.
- Demographic and phenotypic factors that contribute to early or missed diagnosis can be identified from EHR data to improve identification, reduce the diagnostic odyssey, and lower the likelihood that models perpetuate already existing disparities.
You can read more about their work here: https://news.vumc.org/2022/10/13/study-to-search-ehr-for-undiagnosed-ge…
You can also read more about the science behind the Center by visiting the Our Methodology page or browse our published work on our Recent Publications page.
