Cost-utility analysis when not everyone wants the treatment: modeling split-choice bias

Area of Science:

• Health economics
• Decision analysis
• Biostatistics

Background:

• Cost-utility analysis (CUA) is crucial for evaluating health technologies (HTs).
• CUAs traditionally use mean expected utility (EU) across all eligible patients.
• Patient participation rates are factored into CUA calculations.

Purpose of the Study:

• To analyze the bias in CUA when patient acceptance of new treatments is not fully considered.
• To quantify the underestimation of HT benefits due to ignoring patient preferences.

Main Methods:

• Developed a quality-adjusted life year (QALY)-based utility model.
• Modeled a population of clinically indistinguishable patients with varying outcome valuations.
• Investigated deterministic and probabilistic models of individual patient decision-making.

Main Results:

• Patient acceptance is correlated with perceived utility gain.
• Using mean EU over all patients, rather than acceptors only, biases CUA results.
• This bias leads to an underestimate of the true benefits of an HT.
• The bias magnitude increases as the proportion of treatment acceptors decreases.

Conclusions:

• Standard CUA may underestimate HT benefits by not accounting for patient-specific utility valuation.
• Patient decision-making and acceptance rates are critical factors in accurately assessing treatment value.
• Future CUAs should incorporate patient preference heterogeneity for more precise benefit estimations.