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- Johannesson, Magnus, et al.
(författare)
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Designing and conducting cost-benefit analyses
- 1996. - 2
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Ingår i: Quality of life and pharmacoeconomics in clinical trials - Second Edition. - Philadelphia : Lippincott-Raven Publishers. - 9780781703321 ; , s. 1085-1092
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- In cost-benefit analysis both costs and benefits are measured in monetary terms. Unlike cost-effectiveness analysis in which the ratio of costs to effects must be compared with an external standard to judge the desirability of a health program, cost-benefit analysis permits a direct comparison of benefits and costs in the same units (1). The challenge, however, is to measure health benefits in monetary units. According to economic theory, the consequences of a program should be measured as the willingness to pay of the individuals who bear the consequences. These consequences may include benefits such as increased probabilities of survival or improved quality of life, and they may include offsetting adverse effects such as side effects, complications, and inconvenience of treatment. Therefore, the major additional requirement in the design of cost-benefit as compared with cost-effectiveness studies in the health field is a method for measuring willingness to pay for the net consequences of health programs.
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| 2. |
- Johannesson, Magnus, et al.
(författare)
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On the decision rules of cost-effectiveness analysis
- 1993
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Ingår i: Journal of health economics. - : Elsevier B.V. - 1879-1646 .- 0167-6296. ; 12:4, s. 459-467
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Tidskriftsartikel (refereegranskat)abstract
- Birch and Gafni (1992) claim in a recent article that the decision rules of cost-effectiveness/utility analysis (CEA) fail to achieve their stated objectives, namely the maximization of health gains for a given amount of resources. This critique includes the following objections to CEA: First, they argue that CEA does not guarantee improvements in social welfare in situations where multiple health objectives exist (e.g., survival and functional status). Second, they argue that CEA does not consider the health gains forgone by reallocating resources from existing programs to fund new programs. Third, they argue that incremental CEA can lead to inefficient resource allocation when there are alternative levels of programs which compete for budgetary resources. Finally, they argue that the decision rules of CEA are incorrect in the presence of program indivisibilities, and that integer programming techniques are needed. These arguments are illustrated by using hypothetical examples. The analysis by Birch and Gafni is critically examined in this paper. First, we review the optimal decision rules in cost-effectiveness analysis. Second, we show that most of the objections to CEA raised by Birch and Gafni in their examples have no basis if CEA is used in an appropriate way. In fact, they are led to misleading conclusions because they fail to interpret the incremental cost-effectiveness ratios in their examples properly. The inconsistent results in their analysis arise due to (1) their failure to recognize the basis of QALYs as a measure of social welfare; (2) their failure to distinguish between optimal decision rules for independent programs versus mutually exclusive programs; and (3) their failure to exclude dominated alternatives from consideration in analysis of competing programs. Third, we address the valid but well-known point about program indivisibilities. We end with some concluding remarks.
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| 3. |
- Kip, Michelle M. A., et al.
(författare)
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Toward Alignment in the Reporting of Economic Evaluations of Diagnostic Tests and Biomarkers: The AGREEDT Checklist
- 2018
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Ingår i: Medical decision making. - : SAGE PUBLICATIONS INC. - 0272-989X .- 1552-681X. ; 38:7, s. 778-788
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Tidskriftsartikel (refereegranskat)abstract
- Objectives. General frameworks for conducting and reporting health economic evaluations are available but not specific enough to cover the intricacies of the evaluation of diagnostic tests and biomarkers. Such evaluations are typically complex and model-based because tests primarily affect health outcomes indirectly and real-world data on health outcomes are often lacking. Moreover, not all aspects relevant to the evaluation of a diagnostic test may be known and explicitly considered for inclusion in the evaluation, leading to a loss of transparency and replicability. To address this challenge, this study aims to develop a comprehensive reporting checklist. Methods. This study consisted of 3 main steps: 1) the development of an initial checklist based on a scoping review, 2) review and critical appraisal of the initial checklist by 4 independent experts, and 3) development of a final checklist. Each item from the checklist is illustrated using an example from previous research. Results. The scoping review followed by critical review by the 4 experts resulted in a checklist containing 44 items, which ideally should be considered for inclusion in a model-based health economic evaluation. The extent to which these items were included or discussed in the studies identified in the scoping review varied substantially, with 14 items not being mentioned in 47 (75%) of the included studies. Conclusions. The reporting checklist developed in this study may contribute to improved transparency and completeness of model-based health economic evaluations of diagnostic tests and biomarkers. Use of this checklist is therefore encouraged to enhance the interpretation, comparability, andindirectlythe validity of the results of such evaluations.
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