Efficiency of Mental Health Services With Robustness Check of DEA Scores by Income Groups

ABSTRACT The aim of this study is to examine the efficiency of mental health services in different countries based on their economic levels (income groups) and to see how reliable the results are. It also aims to examine whether the efficiency scores of countries vary by region and income groups. Data from 75 countries were used in the analysis. Input factors were the number of mental hospitals, psychiatrists, psychologists, and nurses, while output variables included the prevalence of depression, anxiety, total years lived with disability (YLD) for depression, and YLD for anxiety. To ensure that the decision‐making units in this study are homogeneous, countries were separated into three groups based on their income levels, and then the data envelopment analysis (DEA) (input‐oriented VRS model) was performed individually for each income level. When comparing middle‐income countries (MIC) to low‐income countries (LIC) and high‐income countries (HIC), I found that MIC has lower efficiency scores (0.48). In addition, I found that LIC (0.93) is more efficient than HIC (0.72). This analysis identifies countries' potential improvement gaps in improving the efficiency of mental health services. The findings of this study are intended to guide policymakers and decision‐makers in the field of mental health treatment.

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Journal
Managerial and Decision Economics
Published
2025-11-08
DOI
https://doi.org/10.1002/mde.70043
Primary Topic
Efficiency Analysis Using DEA
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Efficiency of Mental Health Services With Robustness Check of DEA Scores by Income Groups

Gülnur İlgün
Managerial and Decision Economics
Efficiency Analysis Using DEA
article

Efficiency of Mental Health Services With Robustness Check of DEA Scores by Income Groups

Gülnur İlgün
article en

Abstract

ABSTRACT The aim of this study is to examine the efficiency of mental health services in different countries based on their economic levels (income groups) and to see how reliable the results are. It also aims to examine whether the efficiency scores of countries vary by region and income groups. Data from 75 countries were used in the analysis. Input factors were the number of mental hospitals, psychiatrists, psychologists, and nurses, while output variables included the prevalence of depression, anxiety, total years lived with disability (YLD) for depression, and YLD for anxiety. To ensure that the decision‐making units in this study are homogeneous, countries were separated into three groups based on their income levels, and then the data envelopment analysis (DEA) (input‐oriented VRS model) was performed individually for each income level. When comparing middle‐income countries (MIC) to low‐income countries (LIC) and high‐income countries (HIC), I found that MIC has lower efficiency scores (0.48). In addition, I found that LIC (0.93) is more efficient than HIC (0.72). This analysis identifies countries' potential improvement gaps in improving the efficiency of mental health services. The findings of this study are intended to guide policymakers and decision‐makers in the field of mental health treatment.

Managerial and Decision EconomicsVol. 47(2)
Aksaray University (TR)
Openalex Percentile: Top 61%
Efficiency Analysis Using DEA
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Efficiency of Mental Health Services With Robustness Check of DEA Scores by Income Groups — Gülnur İlgün · Managerial and Decision Economics (2025) | TGRS Research Map | TGRS