PROJECT SUMMARY Amblyopia is the leading cause of vision loss in children. Delayed diagnosis and/or inadequate treatment of amblyopia in early childhood may result in permanent vision loss. The underlying social determinants of health contributing to the outcomes of children with amblyopia are poorly understood. There is an urgent need to understand the factors contributing to diagnostic delay and treatment failure in amblyopia – an effort that may offer novel opportunities for vision screening policies and community-based interventions that improve vision care. This proposal aims to investigate the delivery of preventive vision care in the US and develop tools to identify children with preventable vision loss. This research will leverage an array of large data sources – including nationally representative surveys, insurance claims, and electronic health records – to identify modifiable factors that may improve the visual outcomes of children with amblyopia. The central hypothesis is that household- and neighborhood-level social determinants of health influence the receipt of vision screening (Aim 1), access to eye specialty care (Aim 2), and treatment success (Aim 3). The investigations will evaluate existing vision screening policies in the US, identify geospatial factors influencing health care access, and help develop a prediction model to identify children who may lose vision from amblyopia. The candidate, Dr. Isdin Oke, is a pediatric ophthalmologist, data scientist, and health services researcher whose long-term goal is to become an independent investigator with expertise in data-driven approaches to reduce preventable vision loss in children. The career development plan will provide expertise in study design, research methods, and advanced biostatistical approaches for conducting health services research. The mentorship team includes expertise in health services research, vision screening, social epidemiology, geospatial analyses, and predictive modeling. The training environment at Boston Children's Hospital provides access to rich data sources and computational infrastructure. The unique combination of the training plan, mentorship team, and institutional environment will accelerate the candidate's development into an NIH-funded independent investigator and leader in data science and health services research in ophthalmology.