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Assessing quality in decision analytic cost-effectiveness models. A suggested framework and example of application
M Sculpher1, E Fenwick, K Claxton
1Centre for Health Economics, University of York, York, England.
Pharmacoeconomics
|September 8, 2000
Summary
This paper proposes a quality assessment framework for decision analytic models used in cost-effectiveness analysis. It ensures optimal treatment decisions are made under uncertainty, enhancing healthcare resource allocation.
Area of Science:
- Health economics and decision science.
- Methodological research in evidence-based healthcare.
Background:
- Decision analytic modelling is increasingly used in cost-effectiveness analysis.
- A lack of literature exists on best practices for decision analysis quality.
Purpose of the Study:
- To define 'validity' and 'quality' in decision analysis.
- To propose a framework for assessing the quality of cost-effectiveness models.
- To guide analysts and reviewers in evaluating decision models.
Main Methods:
- Reviewing the purpose and scientific characteristics of cost-effectiveness models.
- Developing a taxonomy of quality dimensions: model structure, data, and consistency.
- Suggesting a non-exhaustive list of quality assessment questions.
Main Results:
- Rejection of strict scientific codification for decision models.
- Emphasis on falsifiability and current evidence for scientific validity.
- A proposed framework for assessing model quality based on structure, data, and consistency.
Conclusions:
- A quality assessment framework is necessary and achievable for decision models.
- The framework encourages explicit justification of methods by analysts.
- It enables informed judgments on model relevance, coherence, and usefulness for decision-making.
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