Objective: To estimate the fiscal consequences of schizophrenia compared to the general US population using a "government perspective" fiscal analytic modeling framework capturing lost tax revenue and broader government costs in 2021. Methods: Schizophrenia was modeled from age 23 using a cohort-based Markov chain with 6-week cycles, simulating the effect of antipsychotic treatment sequences on remission and relapse. Markov states were defined using efficacy and safety outcomes from short-and long-term clinical trials. Mortality was based on US lifetables, schizophrenia-related suicide, and cardiovascular risks. A semi-Markov model with annual cycles simulated the likelihood and costs of incarceration and homelessness in community-based individuals. Lifetime fiscal consequences were estimated conditionally to surrival, remission/relapse status, and likelihood of socioeconomic outcomes. Costs and life years were discounted at 3.0% annually. Uncertainty was explored in 1-way and scenario analyses. Results: Unemployment, disability, incarceration, homelessness, health care use, and productivity losses were more common in people living with schizophrenia. Schizophrenia was associated with a $1,540,042 per person lifetime fiscal loss to the government, with $56,707 per life year lived with schizophrenia. Health care costs represented 41.9% of the fiscal losses, 39.4% were due to criminal and homelessness costs, and 17.5% related to foregone tax revenue. Considering a 1.19% prevalence of schizophrenia, the estimated annual fiscal burden in the US was $173.6 billion. Conclusions: The fiscal framework illustrates how schizophrenia influences taxation and government transfer payments over time. These findings can be used to aug ment cost-effectiveness analyses and inform stakeholders of the fiscal impact of schizophrenia to inform priority interventions.
机构:
Research Unit of Scientific Computing-Computer Science and Data Science, University of Nouakchott, Nouakchott, Mauritania
ICUBE Laboratory, Strasbourg University, Strasbourg, FranceResearch Unit of Scientific Computing-Computer Science and Data Science, University of Nouakchott, Nouakchott, Mauritania
Koné, Lalla Aicha
Leonteva, Anna Ouskova
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ICUBE Laboratory, Strasbourg University, Strasbourg, FranceResearch Unit of Scientific Computing-Computer Science and Data Science, University of Nouakchott, Nouakchott, Mauritania
Leonteva, Anna Ouskova
Diallo, Mamadou Tourad
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Research Unit of Scientific Computing-Computer Science and Data Science, University of Nouakchott, Nouakchott, MauritaniaResearch Unit of Scientific Computing-Computer Science and Data Science, University of Nouakchott, Nouakchott, Mauritania
Diallo, Mamadou Tourad
Haouba, Ahmedou
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Research Unit of Scientific Computing-Computer Science and Data Science, University of Nouakchott, Nouakchott, MauritaniaResearch Unit of Scientific Computing-Computer Science and Data Science, University of Nouakchott, Nouakchott, Mauritania
Haouba, Ahmedou
Collet, Pierre
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Institute of Technology for Innovation in Health and Wellness, Faculty of Engineering, Université Andrés Bello, Valparaiso, Viña del Mar, ChileResearch Unit of Scientific Computing-Computer Science and Data Science, University of Nouakchott, Nouakchott, Mauritania