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The economic burden of schizophrenia in Germany: A population-based retrospective cohort study using genetic matching

Published online by Cambridge University Press:  15 April 2020

S. Frey*
Affiliation:
Hamburg Center for Health Economics (HCHE), University of Hamburg, Hamburg Esplanade 36, 20354Hamburg, Germany
*
*Tel.: +49 40 428 38–8042; fax: +49 40 428 38–8043. E-mail address: simon.frey@uni-hamburg.de.
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Abstract

Objective

Prior studies to determine the economic consequences of schizophrenia have largely been undertaken in clinical settings with a small number of cases and have been unable to analyze effects across different age cohorts. The aim of this study is to investigate the burden of schizophrenia in Germany.

Methods

Costs, service utilization, and premature mortality attributable to schizophrenia were estimated for the year 2008 using a retrospective matched cohort design. Therefore, 26,977 control subjects as well as 9411 individuals with a confirmed diagnosis of schizophrenia were drawn from a sickness fund claims database. To reduce conditional bias, the non-parametric genetic matching method was employed.

Results

The final study population comprised 8224 matched pairs. The annual cost attributable to schizophrenia was €11,304 per patient from the payers’ perspective and €20,609 from the societal perspective with substantial variations among age groups: direct medical expenses were highest among patients aged > 65 years, whereas younger individuals (< 25 years) incurred the greatest non-medical costs. The annual burden of schizophrenia from the perspective of German society ranges between €9.63 billion and €13.52 billion.

Conclusion

There are considerable differences in the distribution of costs and service utilization for schizophrenia. Because schizophrenia is characterized by an early age of onset and a long duration, research efforts should be targeted at particular populations to obtain the most beneficial outcomes, both clinically and economically.

Type
Original article
Copyright
Copyright © Elsevier Masson SAS 2014

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