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Estimating the Direct Costs of Illness

Authors: A A, Scitovsky;

Estimating the Direct Costs of Illness

Abstract

about estimating the costs of illness has centered around the relative advantages and disadvantages of the two basic methodologies used or proposed-the "human capital" method as against "willingness to pay." Very briefly, the human capital approach requires estimating the direct costs of illness, i.e., the costs of prevention, detection, treatment, and rehabilitation, as well as the indirect costs to society due to lost earnings resulting from morbidity and premature mortality. Willingness-to-pay estimates, by contrast, are based on the amounts persons would be willing to pay to reduce their risk of incurring, or dying from, a given disease or diseases. Although this latter approach is more satisfactory on theoretical grounds, lack of appropriate data has so far limited its use in practice, and most estimates of the costs of illness made to date have used the

Keywords

Costs and Cost Analysis, Humans, Disease, Health Expenditures, Morbidity, Diagnosis-Related Groups, United States, Direct Service Costs

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Powered by OpenAIRE graph
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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!
40
Top 10%
Top 1%
Average
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