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

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 e...

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Autores principales: Ha, Nguyen Thu, Huong, Nguyen Thanh, Anh, Vu Nguyen, Anh, Nguyen Quynh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281039/
https://www.ncbi.nlm.nih.gov/pubmed/35831821
http://dx.doi.org/10.1186/s12913-022-08206-9
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author Ha, Nguyen Thu
Huong, Nguyen Thanh
Anh, Vu Nguyen
Anh, Nguyen Quynh
author_facet Ha, Nguyen Thu
Huong, Nguyen Thanh
Anh, Vu Nguyen
Anh, Nguyen Quynh
author_sort Ha, Nguyen Thu
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08206-9.
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spelling pubmed-92810392022-07-15 Modelling in economic evaluation of mental health prevention: current status and quality of studies Ha, Nguyen Thu Huong, Nguyen Thanh Anh, Vu Nguyen Anh, Nguyen Quynh BMC Health Serv Res Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08206-9. BioMed Central 2022-07-13 /pmc/articles/PMC9281039/ /pubmed/35831821 http://dx.doi.org/10.1186/s12913-022-08206-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ha, Nguyen Thu
Huong, Nguyen Thanh
Anh, Vu Nguyen
Anh, Nguyen Quynh
Modelling in economic evaluation of mental health prevention: current status and quality of studies
title Modelling in economic evaluation of mental health prevention: current status and quality of studies
title_full Modelling in economic evaluation of mental health prevention: current status and quality of studies
title_fullStr Modelling in economic evaluation of mental health prevention: current status and quality of studies
title_full_unstemmed Modelling in economic evaluation of mental health prevention: current status and quality of studies
title_short Modelling in economic evaluation of mental health prevention: current status and quality of studies
title_sort modelling in economic evaluation of mental health prevention: current status and quality of studies
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281039/
https://www.ncbi.nlm.nih.gov/pubmed/35831821
http://dx.doi.org/10.1186/s12913-022-08206-9
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