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

Sanjeewa Kularatna1, Ruvini Hettiarachchi2, Sameera Senanayake1

  • 1Australian Centre for Health Services Innovation (AusHSI) and Centre for Healthcare Transformation, School of Public Health & Social Work, Queensland University of Technology (QUT), Brisbane, Australia.

Insights

Model-based economic evaluations for child and youth mental health interventions are increasing. This review found most studies used Markov models or decision trees and had good reporting quality.

Area of Science:

  • Health Economics
  • Child and Adolescent Psychiatry
  • Public Health

Background:

  • Child and youth mental health disorders impose a significant burden on healthcare systems.
  • Cost-effective interventions are crucial for efficient mental health care allocation.
  • Evidence on model-based economic evaluations in child and youth mental health is limited.

Purpose of the Study:

  • To systematically review model-based economic evaluations of mental health interventions for children and youth.

Main Methods:

  • A systematic search of four databases (MEDLINE, EMBASE, PsycINFO, Web of Science) was conducted.
  • Model-based economic evaluations of child and youth mental health interventions were retrieved.
  • Reporting quality was assessed using the Consolidated health economic evaluation reporting standards (CHEERS) checklist.

Main Results:

  • 1921 records were identified, with 12 studies selected for review; 66% were published after 2015.
  • Studies primarily focused on anxiety and post-traumatic stress disorder.
  • Common models included Markov models and decision trees, with variations in structure, health states, time horizon, and economic perspective. Reporting quality ranged from 91% to 96%.

Conclusions:

  • Model-based economic evaluations in child and youth mental health are becoming more prevalent.
  • Markov models and decision trees were frequently employed, individually or combined.
  • The majority of reviewed studies demonstrated good reporting quality.

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