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The European Journal of Health Economics
Article . 2020 . Peer-reviewed
License: CC BY
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The European Journal of Health Economics
Article
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Other literature type . 2020
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Article . 2020
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Modelling Covid-19 under uncertainty: what can we expect?

Authors: Wang, Meimei; Flessa, Steffen;

Modelling Covid-19 under uncertainty: what can we expect?

Abstract

This paper examines the behaviour of mental health care providers in response to marginal payment incentives induced by a discontinuous per diem reimbursement schedule with varying tariff rates over the length of stay. The analyses use administrative data on 12,627 cases treated in 82 psychiatric hospitals and wards in Germany. We investigate whether substantial reductions in marginal reimbursement per inpatient day led to strategic discharge behaviour once a certain length of stay threshold is exceeded. The data do not show gaps and bunches at the duration of treatment when marginal reimbursement decreases. Using logistic regression models, we find that providers did not react to discontinuities in marginal reimbursement by significantly reducing inpatient length of stay around the threshold. These findings are robust in terms of different model specifications and subsamples. The results indicate that if regulators aim to set incentives to decrease LOS, this might not be achieved by cuts in reimbursement over LOS.

Country
Germany
Related Organizations
Keywords

ddc:610, I100, Models, Statistical, SARS-CoV-2, Health Policy, Economics, Econometrics and Finance (miscellaneous), Decision Making, Pneumonia, Viral, Uncertainty, COVID-19 ; Pandemics/economics [MeSH] ; Humans [MeSH] ; Pneumonia, Viral/economics [MeSH] ; Models, Economic [MeSH] ; Editorial ; Coronavirus Infections/economics [MeSH] ; COVID-19 [MeSH] ; Models, Statistical [MeSH] ; Betacoronavirus [MeSH] ; I100 ; SARS-CoV-2 [MeSH] ; Decision Making [MeSH] ; Uncertainty [MeSH], COVID-19, Betacoronavirus, Editorial, Models, Economic, Humans, Coronavirus Infections, Pandemics

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Top 10%
Top 10%
Green
hybrid