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Assessing outcomes for cost-utility analysis in children and adolescents with mental health problems: Are multi-attribute utility instruments (MAUIs) fit for purpose?

Published:December 16, 2022DOI:https://doi.org/10.1016/j.jval.2022.12.007
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      Highlights

      • Multi-attribute utility instruments (MAUIs) such as the EQ-5D-Y, CHU9D, HUI-2&3 and the AQoL-6D - used to assess quality-adjusted life-years (QALYs) have not been psychometrically evaluated in children/adolescents with mental disorders.
        • This study evaluated commonly used MAUIs in children/adolescents with mental disorders and compared them to frequently used non-MAUI outcome measures - both self- and clinician/parent reported.
        • The MAUIs were found to have good concurrent and construct validity when compared to self-report outcome measures but poor validity when compared to clinician or parent/guardian reported measures.
        • This research raises the question of whether QALY gains should be exclusively estimated using self-reported measures.

      Objectives

      The objective of this study was to compare the concurrent and construct validity as well as the sensitivity of five multi-attribute utility instruments (MAUIs) including the AQol-6D, EQ-5D-Y, HUI 2&3, and the CHU9D, one generic paediatric quality of life instrument, (PedsQL) to three routinely collected outcome measures in Australian mental health services (SDQ, CGAS and the HoNOSCA) in children and adolescents diagnosed with internalising (e.g. anxiety/depression), externalising (e.g. ADHD/conduct disorders) and trauma/stress related mental disorders.

      Methods

      A cross-sectional survey of measures including demographic and basic treatment information in children/adolescents recruited via five child and youth mental health services in Queensland and Victoria, Australia. Measures were either proxy or self-report completed, the CGAS and the HONOSCA were clinicians completed.

      Results

      The sample included 426 participants and had a mean age of 13.7 (Range: 7-18 years). Utilities (as calculated from MAUIs) were generally lower in older adolescents and those with internalising disorders. All MAUIs and self-reported clinical measures significantly correlated with each other (absolute correlation range 0.40-0.90), with the AQoL-6D showing generally higher levels of correlations. Correlations between the MAUIs and clinician/proxy reported measures were weak, regardless of diagnosis (absolute correlation range 0.09-0.47). Generally, EQ-5D-Y, HUI-2, AQoL-6D were more sensitive than CHU9D and HUI-3 when distinguishing between different severities according to clinician-assessed CGAS (effect size range 0.17-0.84).

      Conclusion

      The study showed that the commonly used MAUIs had good concurrent and construct validity compared to routinely used self-complete measures but poor validity when compared to clinician/proxy-completed measures. These findings generally held across different diagnoses.
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