Cost-effectiveness analysis of paediatric mental health interventions: a systematic review of model-based economic evaluations

Abstract

Mental health disorders among children and youth are causing significant burden on health care systems. Hence, identifying cost-effective interventions is important for effective mental health care allocation. Although model-based economic evaluations are an essential component of assessing cost-effectiveness, evidence are limited in the context of child and youth mental health care. The objective was to systematically review the model-based economic evaluations of mental health interventions for children and youth.MethodsFour databases (MEDLINE, EMBASE, PsycINFO and Web of Science) were searched using appropriate search terms to retrieve model-based economic evaluations of mental health interventions for children and youth. The reporting quality of the included studies were appraised using the Consolidated health economic evaluation reporting standards (CHEERS) checklist.ResultsThe database search yielded 1921 records. Of the 12 selected for review, 66% were published after year 2015. Most of the studies were related to anxiety and post-traumatic stress disorder. There were eight cost-utility studies, three cost-effectiveness studies, and one study using both forms of analysis. Six studies used Markov models, three used decision trees, and three studies used both types of models. However, the model structure, health states, time horizon, and economic perspective showed wide variation. The reporting quality of the included studies varied from 91 to 96%.ConclusionModel based mental health economic evaluations among children and youth are increasingly being reported in recent research. The included studies used Markov models and decision trees, either alone or in combination, and the majority of the articles were of good reporting quality.

Repercussions of the COVID-19 pandemic on child and adolescent mental health: A matter of concern—A joint statement from EAP and ECPCP

“…In 2022 mental disorders account for at least 18% of global disease burden, and the associated annual global costs are projected to be US$ 6 trillion by 2030 ( 17 ). Hence, identifying cost-effective interventions is important for effective mental health care allocation, while is also essential that the intervention strategies are effective in reducing the burden of disease within the constraints of the allocated resources ( 18 ).…”