Omnya El Massad
Senior Director – Data Science & EMR Data Product
The Queen of EMR
Imagine being one of the 400+ million individuals who wait an average of seven years before being diagnosed with a rare or genetic disease. Would you like to know that someone, somewhere is actively working to reduce that time-to-diagnosis? Omnya El Massad is championing a novel way of analyzing patient electronic medical records (EMR) and applying new analytics strategies to find those rare disease patients.
Customarily, analytics professionals use insurance claims data when executing methodologies. While claims data is industry-standard and easily malleable, it only includes final diagnoses and takes a substantial amount of time to collect. EMR data, on the other hand, is uncoded information healthcare providers enter during or after meeting with a patient. The data is challenging to manipulate and unsuited for clinical studies—in its native state. But under Omnya’s leadership, clues of potential diseases can be found.
In her role, Omnya ensures EMR data is structured, accurate, and usable for clinical studies and then leverages machine learning and AI to identify cases with particular indications. Her efforts have led to exciting new modeling, sometimes identifying patients even before HCPs determine a diagnosis.
Recently, one of EVERSANA’s clients was using patient diagnoses and medical histories data to identify potential patients. After initial pushback regarding EMR data accuracy and ease-of-use concerns, Omnya and her team convinced the client to include this information in their analysis. The result? The client was able to find new ways to help patients find clinical trials. This work has expanded to now include the development of a full publication on the approach, and the model is also now being considered for hospital and health systems to be used during future diagnosis in real time.
Omnya continues to evolve the application of EMR data and champions its use in order to reach patients faster to improve overall patient outcomes, especially in new indications that have not received this level of analytical attention. Omnya is not only mining data—she is refining the cast-off material other miners said wasn’t useful and turning it into actionable insights that affect overall patient outcomes and lifetime affordability for patients and payers.