Project Summary There are over six million people in the United States who currently live with Alzheimer's disease and related dementias (ADRD) with this number expected to double by 2050. As this population continues to grow, and receive care from the US Medicare and Medicaid programs, it is essential to conduct rigorous quantitative analysis to understand how our current care system caring for the complex care needs of this population. Quantitative research on this topic in recent years has been hindered by two key factors. First, the Medicare Advantage program has been growing rapidly and now enrolls over 50% of all Medicare beneficiaries. In MA, private plans are paid to provide for beneficiary care needs, and plans can differ significantly from Traditional Medicare in terms of the services it provides, and the data it collects. The growth of MA necessitates methods development to ensure that outcomes and diagnoses are being accurately accounted for. The second challenge is the COVID-19 pandemic, which led to widespread disruptions in care that make it difficult to measure the causal impact of policies that were implemented during the same time period. The Data Management and Methods Core C of this P01 proposal will address these issues and provide the quantitative and analytic backbone to each of the proposal's four projects. Specifically, Core C will assemble project data and develop methods for tracking and cleaning longitudinal data, calculate uniform, core measures for use in project analysis, develop and validate methods for the use of Medicare Advantage data, provide analytic and statistical support to all projects, develop and test novel methods for conducting longitudinal causal inference study designs in the aftermath of the COVID-19 pandemic, and develop new Medicare Advantage data for our website LTCFocus.org which publicly reports nursing home level statistics and characteristics. This core will innovate through using newly released Health and Retirement Survey data to validate methods for diagnosing ADRD in the MA program, perform validations of Medicare Advantage encounter data to ensure their usefulness in research projects, develop methods for causal inference that incorporate shocks such as the pandemic, and by making previously availible Medicare Advantage data available for researchers and policymakers. The work of this core will be impactful by enabling the projects included in this P01, but also through the validations and methods development which will have broad applicability for other researchers focused on ADRD.