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A dynamic microsimulation method for estimating dementia costs in the United States
Bryan Tysinger1,2, Hanke Heun-Johnson1,2, Duncan Leaf1,2
1Leonard D. Schaeffer Institute for Public Policy and Government Service, University of Southern California, Los Angeles, California, USA.
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.
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