Purpose: Cost-effectiveness analysis of health technologies typically involves the calculation of incremental cost-effectiveness ratios (ICERs). In some jurisdictions, decision makers compare these ICERs to an explicit cost-effectiveness “threshold” as part of their deliberations. The use of a threshold remains controversial and there is disagreement over what such a threshold, if adopted, should represent. Furthermore, there are many issues and limitations with the interpretation of ICERs. This paper argues that the needs of decision makers and patients would be better served by abandoning ICERs and thresholds altogether and adopting instead a decision framework based upon a modified notion of “net benefit”.
Method: Using recent Ontario-based cost-effectiveness analyses as examples, we demonstrate that ICERs cannot be used to rank strategies, nor can ICERs be used to determine the extent to which one strategy is more cost-effective than another. Drawing on the use of "indifference curves" from consumer theory, we propose an alternative approach which does not suffer from the same limitations. This approach is consistent with making decisions on the basis of "net benefit", and may be modified to incorporate concerns for efficiency, equity, societal and ethical values, and patient preferences.
Result: The traditional interpretation of ICERs can be misleading. Comparing ICERs to an explicit threshold cannot satisfy the needs of decision makers or patients – regardless of the threshold used – except under very specific circumstances. These limitations may be addressed by adopting a framework based upon a modified notion of "net benefit".
Conclusion: Abandoning ICERs and thresholds and adopting a decision framework based upon a modified notion of “net benefit” would not only address many of the issues with ICERs and thresholds but would be easier for decision makers to interpret. It would also allow decision makers who adopt multiple decision making criteria (such as concerns for efficiency, equity, societal and ethical values, and patient preferences) to make explicit trade offs between these criteria.
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