A dynamic microsimulation method for estimating dementia costs in the United States.

INTRODUCTION: Addressing dementia's substantial economic burden on individuals, families, health systems, governments, and payers, requires integrating national data and advanced analytic methods.

METHODS: We described data sources, measures, and simulation methods of a dynamic microsimulation model developed for quantifying dementia costs in the United States and for assessing impact of innovation and change over time. Model internal validation was assessed.

RESULTS: Using nationally representative Health and Retirement Study data on adults over age 50, Medicare and other national data, we produced estimates of individual-level health and economic outcomes over time. Estimates and simulation enabled measurement of population-level dementia prevalence, medical and long-term care costs, unpaid caregiving valuation, quality-of-life, and earnings for persons living with dementia and care partners. Counterfactual scenarios quantified dementia-related quality-of-life and earnings losses. Simulated outcomes aligned with observed data.

CONCLUSIONS: Transparent methods support replication, extension, and informed use of dementia cost estimates in research and policy.