Enabling QALY Estimation in Mental Health Interventions: Mapping the Health of the Nation Outcome Scales onto the EQ-5D-5L
Admassu N. Lamu, Egil Kjerstad, Reinhold Kilian, Annabel S. Mueller-StierlinBackground:
Mental health intervention studies often lack preference-based measures required to estimate quality-adjusted life-years (QALYs) for health economic evaluations. In such circumstances, a mapping study is the second-best alternative to estimate QALYs. This study aimed to develop a mapping algorithm to predict EQ-5D-5L value sets from the Health of the Nation Outcome Scales (HoNOS) among adults with severe mental illness (SMI).
Methods:
Trial data from a community mental health intervention conducted in Germany between 2020 and 2023 were assessed over 24 mo. The data included more than 900 adults aged 18 to 82 y living with SMI. Four econometric approaches were used to map HoNOS to EQ-5D-5L: ordinary least square (OLS), generalised linear regression model (GLM), fractional regression model (FRM), and an adjusted limited dependent variable mixture model (ALDVMM). The German EQ-5D-5L value set was used, while keeping the Norwegian value set in the
Results:
The FRM consistently performed best across all evaluation criteria in both the full sample and cross-validation. In cross-validation, when HoNOS items were used as predictors of the German value set, the FRM yielded RMSE = 0.2204, MAE = 0.1622, and
Conclusions:
The preferred mapping algorithm enables the estimation of EQ-5D-5L utilities from HoNOS data, facilitating the calculation of QALYs when only HoNOS information is available. As our sample includes a broad spectrum of mental health patients, further validation within specific diagnostic groups is recommended to improve predictive accuracy.