Modelling in economic evaluation of mental health prevention: current status and quality of studies

Abstract

Abstract Background The present study aimed to identify and critically appraise the quality of model-based economic evaluation studies in mental health prevention. Methods A systematic search was performed on MEDLINE, EMBASE, EconLit, PsycINFO, and Web of Science. Two reviewers independently screened for eligible records using predefined criteria and extracted data using a pre-piloted data extraction form. The 61-item Philips Checklist was used to critically appraise the studies. Systematic review registration number : CRD42020184519. Results Forty-nine studies were eligible to be included. Thirty studies (61.2%) were published in 2015–2021. Forty-seven studies were conducted for higher-income countries. There were mainly cost-utility analyses (n = 31) with the dominant primary outcome of quality-adjusted life year. The most common model was Markov (n = 26). Most of the studies were conducted from a societal or health care perspective (n = 37). Only ten models used a 50-year time horizon (n = 2) or lifetime horizon (n = 8). A wide range of mental health prevention strategies was evaluated with the dominance of selective/indicate strategy and focusing on common mental health problems (e.g., depression, suicide). The percentage of the Philip checkilst’s criteria fulfilled by included studies was 69.3% on average and ranged from 43.3 to 90%. Among three domains of the Philip checklist, criteria on the model structure were fulfilled the most (72.1% on average, ranging from 50.0% to 91.7%), followed by the data domain (69.5% on average, ranging from 28.9% to 94.0%) and the consistency domain (54.6% on average, ranging from 20.0% to 100%). The practice of identification of ‘relevant’ evidence to inform model structure and inputs was inadequately performed. The model validation practice was rarely reported. Conclusions There is an increasing number of model-based economic evaluations of mental health prevention available to decision-makers, but evidence has been limited to the higher-income countries and the short-term horizon. Despite a high level of heterogeneity in study scope and model structure among included studies, almost all mental health prevention interventions were either cost-saving or cost-effective. Future models should make efforts to conduct in the low-resource context setting, expand the time horizon, improve the evidence identification to inform model structure and inputs, and promote the practice of model validation.

Keywords

• Decision-analytic models
• Economic evaluation
• Value-for-money
• Cost-effectiveness
• Prevention
• Mental health