Definition, interpretation and calculation of cost-effectiveness acceptability curves

Area of Science:

• Health Economics
• Biostatistics
• Decision Science

Background:

• Cost-effectiveness (CE) analysis is crucial for healthcare resource allocation.
• Interpreting and computing CE acceptability curves requires clear definitions and methods.
• Existing methods for CE acceptability curves lack formal links to statistical inference.

Purpose of the Study:

• To provide a formal definition of the cost-effectiveness acceptability curve (CEAC) based on the net benefit approach.
• To describe parametric and non-parametric methods for computing CEACs.
• To establish a formal relationship between CEACs and statistical inference (confidence intervals, P-values) in CE analysis.

Main Methods:

• Formal definition of CE acceptability curves using the net benefit framework.
• Application of parametric and non-parametric computational techniques.
• Establishment of statistical inference links via confidence intervals and P-values.

Main Results:

• A precise definition of the CE acceptability curve is presented.
• Both parametric and non-parametric computational methods are detailed.
• A formal connection between CE acceptability curves and statistical inference is demonstrated.

Conclusions:

• The net benefit approach provides a robust definition for CE acceptability curves.
• Parametric and non-parametric methods offer practical computation strategies.
• Understanding the link between CEACs and statistical inference enhances the reliability of CE analysis.