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. 2024 Apr 2:33:e19.
doi: 10.1017/S204579602400012X.

Alleviating the burden of depression: a simulation study on the impact of mental health services

M Wilhelm  1   2   3 , S Bauer  1   3 , J Feldhege  4 , M Wolf  5 , M Moessner  1
Affiliations

Alleviating the burden of depression: a simulation study on the impact of mental health services

M Wilhelm et al. Epidemiol Psychiatr Sci. .

Abstract

Aims: Depressive disorders are ranked as the single leading cause of disability worldwide. Despite immense efforts, there is no evidence of a global reduction in the disease burden in recent decades. The aim of the study was to determine the public health impact of the current service system (status quo), to quantify its effects on the depression-related disease burden and to identify the most promising strategies for improving healthcare for depression on the population level.

Methods: A Markov model was developed to quantify the impact of current services for depression (including prevention, treatment and aftercare interventions) on the total disease burden and to investigate the potential of alternative scenarios (e.g., improved reach or improved treatment effectiveness). Parameter settings were derived from epidemiological information and treatment data from the literature. Based on the model parameters, 10,000,000 individual lives were simulated for each of the models, based on monthly transition rates between dichotomous health states (healthy vs. diseased). Outcome (depression-related disease burden) was operationalized as the proportion of months spent in depression.

Results: The current healthcare system alleviates about 9.5% (95% confidence interval [CI]: 9.2%-9.7%) of the total disease burden related to depression. Chronic cases cause the majority (83.2%) of depression-related burden. From a public health perspective, improving the reach of services holds the largest potential: Maximum dissemination of prevention (26.9%; CI: 26.7%-27.1%) and treatment (26.5%; CI: 26.3%-26.7%) would result in significant improvements on the population level.

Conclusions: The results confirm an urgent need for action in healthcare for depression. Extending the reach of services is not only more promising but also probably more achievable than increasing their effectiveness. Currently, the system fails to address the prevention and treatment of chronic cases. The large proportion of the disease burden associated with chronic courses highlights the need for improved treatment policies and clinical strategies for this group (e.g., disease management and adaptive or personalized interventions). The model complements the existing literature by providing a new perspective on the depression-related disease burden and the complex interactions between healthcare services and the lifetime course.

Keywords: depression; health service research; mental health; psychotherapy; social and political issues.

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Conflict of interest statement

None.

Figures

Figure 1.
Figure 1.
Simulation results for the alternative models (changes in parameter settings) for absolute 5% increments up to an optimal scenario with 100%. The parameter settings for the current system can be found in Table 1.
Figure 2.
Figure 2.
Selection of simulation results for an increase of 25% and to an optimal scenario with 100%. Error bars represent upper and lower CI limits. The dashed line refers to the disease burden alleviated by the current system.
See this image and copyright information in PMC

References

    1. Andrade LH, Alonso J, Mneimneh Z, Wells JE, Al-Hamzawi A, Borges G, Bromet E, Bruffaerts R, De Girolamo G, De Graaf R, Florescu S, Gureje O, Hinkov HR, Hu C, Huang Y, Hwang I, Jin R, Karam EG, Kovess-Masfety V, Levinson D, Matschinger H, O’neill S, Posada-Villa J, Sagar R, Sampson NA, Sasu C, Stein DJ, Takeshima T, Viana MC, Xavier M and Kessler RC (2014) Barriers to mental health treatment: Results from the WHO World Mental Health surveys. Psychological Medicine 44, 1303–1317. - PMC - PubMed
    1. Bauer S, Okon E, Meermann R and Kordy H (2012) Technology-enhanced maintenance of treatment gains in eating disorders: Efficacy of an intervention delivered via text messaging. Journal of Consulting and Clinical Psychology 80, 700–706. - PubMed
    1. Baumann M, Stargardt T and Frey S (2020) Cost-utility of internet-based cognitive behavioral therapy in unipolar depression: A Markov model simulation. Applied Health Economics and Health Policy 18, 567–578. - PMC - PubMed
    1. Biesheuvel-Leliefeld KE, Kok GD, Bockting CL, Cuijpers P, Hollon SD, van Marwijk HW and Smit F (2015) Effectiveness of psychological interventions in preventing recurrence of depressive disorder: Meta-analysis and meta-regression. Journal of Affective Disorders 174, 400–410. - PubMed
    1. Bockting CL, Hollon SD, Jarrett RB, Kuyken W and Dobson K (2015) A lifetime approach to major depressive disorder: The contributions of psychological interventions in preventing relapse and recurrence. Clinical Psychology Review 41, 16–26. - PubMed