A Generalized Risk-Adjusted Cost-Effectiveness Economic Model for Measuring the Value of Interventions That Delay...

Area of Science:

• Health Economics
• Neurology
• Decision Analysis

Background:

• Neurological conditions often cause mobility impairments, necessitating effective treatments.
• Assessing the economic value of treatments is crucial for healthcare decision-making.
• Traditional cost-effectiveness analysis (CEA) may not fully capture patient-specific factors.

Purpose of the Study:

• To quantify the impact of patient risk preferences and severity adjustments on the economic value of a hypothetical neurological treatment.
• To compare a generalized and risk-adjusted cost-effectiveness (GRACE) model with traditional CEA.

Main Methods:

• Developed a five-state Markov model to assess a hypothetical treatment delaying mobility impairment progression.
• Implemented the GRACE model using US population risk aversion estimates.
• Measured treatment value using risk-aversion and severity-adjusted net monetary benefit (RASA-NMB).

Main Results:

• GRACE increased the valuation of health gains (1.358 GRA-QALYs vs. 1.199 QALYs) and willingness-to-pay ($109,656/GRA-QALY vs. $100,000/QALY).
• RASA-NMB was 11.6% higher with GRACE ($278,324) compared to traditional CEA ($249,311).
• Results demonstrated sensitivity to risk aversion estimates and patient utility functions.

Conclusions:

• The GRACE model, applied to neurology for the first time, enhanced the economic value assessment of a hypothetical treatment.
• GRACE suggests traditional CEA may undervalue treatments for neurological mobility impairments.
• Incorporating risk preferences and severity provides a more comprehensive economic evaluation.