Background
Laura Wiley, PhD, received her PhD and MS from Vanderbilt University Medical Center and her BS and BSCh from the University of Denver. Dr. Wiley has first-hand experience of not having enough research and knowledge to truly understand the right treatment approach for a condition. As a patient, it is an incredibly scary and unmooring experience and as a researcher, it’s frustrating to know that answers are out there but the resources to look for them are lacking. She is inspired by the opportunity to contribute to the vital field of women’s health and ensure the equity of next-generation data science methods, so that all patients benefit equally from these advances.
Research + Funding
In 2022, Dr. Wiley began her Ludeman Center-funded research project titled, “EmPoW-HER: Equitable Phenotyping for Women’s-Health Research.” This project stems from the fact that women have often been left out of heart disease research and don’t receive healthcare following known best practices. Dr. Wiley’s work focuses on using electronic health records to improve women’s health care. However, it is unknown that the existing inequities might affect this technology. Her project will develop a research database that will allow them to understand whether this is happening and develop solutions for the future and to use this database to see if existing tools to identify patients who have heart failure perform worse in women than men.
She recognizes the Ludeman Center for their unique and incredible resources that support cutting edge research in the critical and under-studied area of women's health. They also provide a great deal of intentionality in training women's health researchers at all levels, from their seed grant program to outreach events for high school students.
Transforming Women’s Health
Dr. Wiley’s current research priority as a biomedical informatician is to develop methods to help use electronic health records for research. One of the key tools she uses is called computational phenotyping, which is a method to help identify which patients have certain medical conditions. She uses that information to identify the trials a patient might be eligible for or to help run a study looking to identify optimal treatments or potential side effects in patients with that condition. Her group not only builds these algorithms but is also interested in understanding how these algorithms may be impacted by existing health disparities to then develop new tools and techniques to ensure these methods are fair, consistent and high quality across all research domains.