A Generalized Risk Adjusted Cost Effectiveness (GRACE) Economic Model for Measuring the Value of Interventions that Delay Mobility Impairment Across Neurological Conditions.

Objectives: To quantify how incorporating patient risk preferences and severity adjustments impact the value of a hypothetical treatment for mobility impairments caused by neurological conditions.

Methods: A five-state Markov model was developed to measure the health economic value of a hypothetical treatment delaying the progression of mobility impairments by 30.7% vs standard of care (SoC) for 45-year-old, minimally impaired patients diagnosed with a neurological condition. A generalized and risk-adjusted cost-effectiveness (GRACE) model was implemented using relative risk aversion (RRA) estimates from a US general population survey. Treatment value was measured as risk-aversion and severity adjusted net monetary benefit (RASA-NMB), defined as: (i) risk-adjusted health gains (GRA-QALYs) monetized by (ii) risk-aversion and severity-adjusted willingness to pay (RASA-WTP) less (iii) incremental costs. Risk-neutral results (traditional cost effectiveness analysis (TCEA)) were compared.

Results: Incorporating risk preferences and disease severity increased the value of health benefits. Incremental health gains from using the hypothetical treatment (vs. SoC) were valued more when accounting for risk preferences with GRACE (1.358 GRA-QALYs vs. 1.199 QALY). Willingness-to-pay for these health gains was higher when computed under GRACE compared to TCEA ($109,656 per GRA-QALY vs $100,000 per QALY). Overall, net monetary benefit increased by 11.6% (RASA-NMB = $278,324 vs traditional CEA NMB = $249,311) using GRACE vs. TCEA. Results were sensitive to risk-aversion estimates and the functional form of patient utility.

Conclusions: In the first application of GRACE within neurology, GRACE increased the health economic value of a hypothetical neurology treatment, suggesting TCEA may undervalue treatments for mobility-related neurological impairments.