Project Grant R01AG103351

The National Institute on Aging awarded Kaiser Foundation Hospitals $830,868 on September 3, 2026, under the Aging Research program (CFDA 93.866) to develop nonparametric methods integrating electronic health record and validated research data for aging-related scientific questions.

Kaiser Foundation Research Institute will develop machine learning methods to improve accuracy and precision of inverse-probability weighted analyses and validation study design for causal inference and prediction model evaluation. The work addresses methodological challenges in leveraging error-prone electronic health record data—particularly unstructured clinical text extracted via text-mining algorithms—alongside validated data from smaller cohorts, such as the Eye Adult Changes in Thought study. Specific deliverables include methods that properly incorporate machine learning-based weights by combining advances in generalized raking with targeted learning approaches, and improved design frameworks for validation studies in causal inference and prediction model evaluation. The research aims to provide reliable scientific and clinical evidence for prognostic tool development in eye diseases including age-related macular degeneration and for understanding relationships between ophthalmic biomarkers and Alzheimer's disease and related dementias risk.

Performance occurs in Seattle, Washington, with a period of performance from award date through June 30, 2031. The award is classified as a Project Grant, the standard assistance type under the NIH Aging Research program.