The National Eye Institute (NEI) collects human data through clinical studies and trials in both its intramural and extramural divisions. Human data are notable for their complexity and lack of interoperability. Yet these data are used for the treatment of the patient from whom they derive. It is important to recognize and characterize the different types of health and healthcare data in order to articulate coherent and complete research questions and to develop treatment methodologies for blinding eye diseases and visual impairment. The Office of Data Science and Health Informatics (ODSHI) coordinates existing activities within the NEI, and across NIH, and other government agencies to provide a nidus for new trans-agency programs in data collection, data sharing and data interoperability. ODSHI works to accelerate scientific discovery, foster collaborative research, and ultimately improve public health through the application of scientific data and knowledge management in the eye health sciences.
Events and Announcements
NEI Welcomes Data and Technology Advancement (DATA) National Service Scholar
Dr. Michelle Hribar from Oregon Health & Science University (OHSU) has joined National Eye Institute (NEI) as a NIH DATA Scholar. She is an Associate Professor in the Ophthalmology and in the department of Medical Informatics and Clinical Epidemiology at OHSU where she leads the ophthalmic informatics research group at Casey Eye Institute. Her NIH funded research focuses on the effective reuse of electronic health record (EHR) data for research in ophthalmology. Dr. Hribar received her PhD in Computer Science from Northwestern University in Evanston, Illinois and began her professional career in high performance computing at NASA Ames Research Center. She has worked at OHSU since 2005 in a variety of different roles in computing and technology before transitioning to faculty in medical informatics and ophthalmology. Her role at the NEI will be to drive community consensus building to improve ocular health care data standardization and spearhead efforts to improve a Common Data Model (CDM) to facilitate research using data collected in routine eye care.
This virtual NEI, FDA, and ONC hosted workshop focused on delineating the state of the science and improving interoperability among ocular imaging modalities and devices to improve biomedical research and patient care.
In early 2022, the National Eye Institute (NEI) issued a Request for Information (RFI) regarding ocular imaging standards. This RFI requested input regarding eight questions. An executive summary of the responses is provided.
Data Science has been included as one of the 7 areas of emphasis in the 2021 NEI Strategic Plan – see how NEI has highlighted important perspective and expertise on this topic.
NIH Common Fund’s Bridge2AI program – NIH has launched a new trans-agency effort to harness the power of AI to propel biomedical and behavioral research forward.
NEI is dedicated to accelerating vision research by sharing impactful data.
National Ophthalmic Disease Genotyping and Phenotyping Network (eyeGENE®)
eyeGENE® is a genomic medicine initiative that’s facilitating research into the causes and mechanisms of rare inherited eye diseases and accelerate pathways to treatments.
NEI Age-Related Macular Degeneration (AMD) Integrative Biology Initiative
Seeks a more precise description of AMD disease pathobiology by using AMD genetic risk factors as sentinels for specific RPE signaling pathways and for changes in RPE physiology.
National Eye Institute Data Commons
Offers a central source for NEI biomedical digital objects including data sets, software and analytical workflow, metadata, standards, and publications.
NIH Common Data Elements (CDE) Repository
Designed to provide access to structured human and machine-readable definitions of data elements that have been recommended or required by NIH Institutes and Centers and other organizations for use in research and for other purposes.
Common Data Elements (CDEs) Course: Standardizing data collection
This course from the National Library of Medicine® is about making data collection and data sharing easier using common data elements (CDEs).
Syed Umair Haqqani
Health Science Policy Analyst