Speaker: Sandy Tubeuf, University of Leeds
This study reports the cost-effectiveness of family therapy (FT) compared to treatment as usual (TAU) in self-harming adolescents from a health and social care costs perspective using data from a trial that recruited 832 participants. The primary outcome was adolescents’ QALY at 18 months after randomisation generated from EQ-5D. Additionally, caregiver’s health-related quality of life was assessed using the Health Utilities Index and sensitivity analyses used the aggregated QALY gain for both the young person and his/her main carer as health outcome. Missing data were imputed via chained equations. Both trial arms showed an increase in the mean EQ-5D over 18 months follow-up; the largest and significant differences were at 6 and 12 months favouring FT however, there were no significant differences between arms at 18 months. FT participants incurred £1,266.23 (95% CI £736.04 to £1,796.43) higher costs and gained 0.034 (95% CI -0.004 to 0.065) extra QALYs than TAU patients. The incremental cost-effectiveness ratio (ICER) equalled £36,811.80 per QALY indicating that FT was unlikely to be cost-effective. When combining adolescents’ and caregivers’ QALY gains, the ICER displayed £20,808.21 per QALY gain with a probability for FT to be cost-effective of 64% at £30,000 per QALY. Hence, when health benefits were considered beyond the young person alone, FT would be considered as a cost-effective use of NHS money. This study discusses whether it is appropriate to aggregate QALYs across individuals while this approach is not yet part of the NICE reference case.
Sandy is Associate Professor in Health Economics at the University of Leeds since 2013. She has held positions at the University of Leeds, York and an independent Institute of Research in Health Economics in Paris. She has a PhD in Economics from Aix-Marseille School of Economics, France. Sandy leads economic evaluation alongside clinical trials, especially in mental health and public health interventions. She also has expertise in policy-evaluation methods and analysis of large data to disentangle causal impacts.