Claims and electronic health record (EHR) data are known sources of real-world healthcare data — neither of which were created for real-world evidence (RWE) generation — but have proved effective in deeply understanding the patient journey. More recently, it has become evident that medical images, from histopathology slides, X-rays, CT scans to MRI scans and ophthalmic images, can offer RWE insights as well when linked with sources such as claims and EHR. Ophthalmic images, for example, capture fluid levels, lesion growth and visual field, all of which are critical in an ophthalmologist’s diagnosis, treatment and care decisions. These variables are just as relevant for researchers to identify patients for a clinical trial, track disease progression within patient populations or understand how patient groups responded to a certain treatment.
Imaging is a critical part of care and has untapped potential when linked with a data source such as EHR data that reveals other key patient demographics and characteristics. In order to use these images as a source of real-world data (RWD) — all of which exist in different formats — researchers are applying machine learning (ML) techniques and developing algorithms to label and recognize patterns.
Join this webinar to learn about the power of images, specifically ophthalmic images, and how linking them with EHR data and applying ML can help support patient journey and disease progression research.
Bonus: Hear use cases for imaging that include support for clinical trials, optimized dosing schedules and comparative effectiveness studies.
Aaron Y. Lee, MD MSCI, Associate Professor and Retina Surgeon, University of Washington, Department of Ophthalmology
Dr. Aaron Y. Lee, MD, MSCI is an Associate Professor and Vitreoretinal Surgeon at the University of Washington, Department of Ophthalmology, and the recent recipient of the C. Dan and Irene Hunter Endowed Professorship. He completed his undergraduate at Harvard University and his medical training at Washington University in St Louis. He chairs the American Academy of Ophthalmology Information Technology Steering Committee. He currently serves as an Associate Editor for both Translational Vision Science and Technology and Ophthalmology Science, and on the Editorial Board for the American Journal of Ophthalmology and Nature Scientific Reports. He has published over 100 peer-reviewed manuscripts and is known as a leader in the field of artificial intelligence and ophthalmology. Aaron Lee’ s research is focused on the translation of novel computation techniques in machine learning to uncover new disease associations and mechanisms from routine clinical data including electronic health records and imaging.
Michael Mbagwu, MD, Senior Medical Director, Verana Health
Dr. Michael Mbagwu, MD, attended the Ohio State University where he completed a Bachelor of Science in Biomedical Science and graduated Summa Cum Laude with Honors. He subsequently attended Northwestern University Feinberg School of Medicine, where he received a Doctor of Medicine and graduated Cum Laude in Scientia Experimentalis. He then completed a transitional/medical internship year at Presence Resurrection Medical Center before returning to Northwestern to complete his residency training in ophthalmology, where he served as Chief Resident. Dr. Mbagwu went on to complete an Ophthalmic Innovation Fellowship at the Byers Eye Institute/Stanford University School of Medicine and was a consultant at Verana Health. Dr. Mbagwu currently holds the academic rank of Adjunct Clinical Instructor of Ophthalmology at Stanford University School of Medicine and is a practicing physician with the Department of Veterans Affairs, Palo Alto Health Care System.
Zhongdi Chu, PhD, MSc, Quantitative Sciences, Verana Health
Zhongdi Chu, PhD, MSc leads Ophthalmic Imaging on the Verana Health Quantitative Sciences team. Dr. Chu has published more than 60 peer-reviewed publications in top medical journals and given more than a dozen presentations at scientific conferences primarily focused on ophthalmic imaging analytics with computer vision and artificial intelligence. Dr. Chu holds several patents in extracting ocular diseases insights from ophthalmic images. Her research has received more than 2,500 citations to date worldwide in the field of ophthalmology and optical imaging. Dr. Chu has been listed in the 2022 Stanford University Elsevier World’s Top 2% Scientists in the field of clinical medicine, specifically ophthalmology and optometry, and nuclear medicine & medical imaging. Dr. Chu earned her PhD in bioengineering at the University of Washington and today, beyond her work at Verana Health, she serves as a reviewer for over a dozen top journals in the field of ophthalmology.
Who Should Attend?
- Health Economics and Outcomes Research (HEOR)
- Medical Affairs
- Data Science
- Real-World Evidence (RWE)
- Commercial Operations
- Market Analytics & Forecasting
- Epidemiology & Drug Safety
- Clinical Development
What You Will Learn
- Understand the value of imaging data as a real-world data source, and the power of linking it with clinical data stored in electronic health records (EHRs) to inform research across the drug and device lifecycle for life sciences
- Hear about ophthalmic imaging specifically and the challenges and opportunities that exist with using it outside of patient care
- Learn how artificial intelligence (AI) techniques, such as machine learning (ML) and algorithm development, are applied to transform millions of images into usable, quality data for research
- Identify opportunities where linking clinical data and imaging data may be most applicable to better understand patient journey, predict disease progression, inform clinical trials strategy and more
Verana Health® is a digital health company elevating quality in real-world data. Verana Health operates an exclusive real-world data network of more than 20,000 healthcare providers (HCPs) and about 90 million de-identified patients, stemming from its strategic data partnerships with the American Academy of Ophthalmology®, American Academy of Neurology®, and American Urological Association. Using its clinician-informed and artificial intelligence-enhanced VeraQ™ population health data engine, Verana Health transforms structured and unstructured healthcare data into curated, disease-specific data modules, Qdata™. Verana Health’s Qdata helps power analytics solutions and software-as-a-service products for real-world evidence generation, clinical trials enablement, HCP quality reporting, and medical registry data management. Verana Health’s quality data and insights help drive progress in medicine to enhance the quality of care and quality of life for patients. For more information, visit www.veranahealth.com.
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