Explore our growing list of publicly available ADRD datasets and analytic tools.

These tools decrease time to functional accessibility of AD/ADRD healthcare administrative and survey data. There is no single “gold standard” approach to the identification of AD/ADRD (and relevant outcomes) using administrative and/or cognitive function measures.

The choice depends on tradeoffs in performance dependent on a variety of factors. The code and “finder files” you will find on our site are designed to help researchers identify AD/ADRD cohorts and relevant outcomes using a variety of current, validated algorithms.

Current datasets contain relevant cognitive and dementia-related outcomes for the National Health and Nutrition Examination Survey (NHANES), the National Hospital Ambulatory Care Survey (NHAMCS), the National Health Interview Survey (NHIS), Behavioral Risk Factor Surveillance System (BRFSS), and the Medical Expenditure Panel Survey (MEPS).  The resources core is currently developing programming script for use on ResDAC (Medicare claims) data that can be used to identify ADRD.

The Bynum-Standard 1-Year Algorithm

The Bynum-Standard 1-Year Algorithm is a decision-making framework designed to evaluate and optimize short-term strategies or actions over a one-year timeframe, prioritizing efficiency and measurable outcomes.

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CAPRA Resources: NIA IMPACT Collaboratory

NIA IMPACT Collaboratory

This dataset reports 2019 Medicare claims, events, and beneficiary counts in hospitals, EDs, and SNFs, comparing those with and without ADRD. Data are available at the facility level in SAS, Stata, and CSV formats.

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