Scaling-up services for psychosis, depression and epilepsy in sub-Saharan Africa and South Asia: development and application of a mental health systems planning tool (OneHealth)

Chisholm, Daniel; Heslin, Margaret; Docrat, Sumaiyah; Nanda, Surabhi; Shidhaye, Rahul; Upadhaya, Nawaraj; Jordans, Mark J. D.; Abdulmalik, Jibril; Olayiwola, Saheed O.; Gureje, Oye; Kizza, Dorothy; Mugisha, James; Kigozi, Fred; Hanlon, Charlotte; Adugna, Molalign B.; Sanders, Rachel; Pretorius, Carel; Thornicroft, Graham; Lund, Crick

doi:10.1017/s2045796016000408

Cited by 51 publications

(71 citation statements)

References 12 publications

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“…Ongoing dialogue and developing collaborations with the aim of providing technical support and increasing capacity over time This tied in with the short courses (see above) in some LMIC partners, for example, in Nepal the short courses were structured across repeated contacts. An example of technical support provided to service planners is training in the OneHealth tool, which is an online platform for human resource and financial planning (Chisholm et al 2016). Four-day modular short course in mental health systems research with three elements:…”

Section: Service Planners and Policymakersmentioning

confidence: 99%

Developing capacity-building activities for mental health system strengthening in low- and middle-income countries for service users and caregivers, service planners, and researchers

Semrau

Alem

Abdulmalik

et al. 2017

Epidemiol Psychiatr Sci

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There is increasing international recognition of the need to build capacity to strengthen mental health systems. This is a fundamental goal of the ‘Emerging mental health systems in low- and middle-income countries’ (Emerald) programme, which is being implemented in six low- and middle-income countries (LMICs) (Ethiopia, India, Nepal, Nigeria, South Africa, Uganda). This paper discusses Emerald's capacity-building approaches and outputs for three target groups in mental health system strengthening: (1) mental health service users and caregivers, (2) service planners and policy-makers, and (3) mental health researchers. When planning the capacity-building activities, the approach taken included a capabilities/skills matrix, needs assessments, a situational analysis, systematic reviews, qualitative interviews and stakeholder meetings, as well as the application of previous theory, evidence and experience. Each of the Emerald LMIC partners was found to have strengths in aspects of mental health system strengthening, which were complementary across the consortium. Furthermore, despite similarities across the countries, capacity-building interventions needed to be tailored to suit the specific needs of individual countries. The capacity-building outputs include three publicly and freely available short courses/workshops in mental health system strengthening for each of the target groups, 27 Masters-level modules (also open access), nine Emerald-linked PhD students, two MSc studentships, mentoring of post-doctoral/mid-level researchers, and ongoing collaboration and dialogue with the three groups. The approach taken by Emerald can provide a potential model for the development of capacity-building activities across the three target groups in LMICs.

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Section: Service Planners and Policymakersmentioning

confidence: 99%

Developing capacity-building activities for mental health system strengthening in low- and middle-income countries for service users and caregivers, service planners, and researchers

Semrau

Alem

Abdulmalik

et al. 2017

Epidemiol Psychiatr Sci

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“…In Nepal, the estimated combined costs of scaling-up services for psychosis, depression and epilepsy are less than $1.30 USD/capita/year. 27 In contrast to the additional $9 USD/year OOP incurred by people in this study for each increment in PHQ-9 score, this is a relatively small investment, which might minimise financial impoverishment, whilst reducing symptoms of depression and hopefully break the link between the two.…”

Section: Mechanisms and Implicationsmentioning

confidence: 91%

“…26 Modelled estimates suggest that this kind of integration could be scaled-up nationally for an investment of $5.55 US dollars per capita, spread over 7 years. 27 The PRIME approach provides a potential model upon which to base integrated services if mental health care were included in UHC. Understanding patterns of healthcare utilization and OOP expenditure by people with depression can help us to predict the likely financial and health service impacts of implementing this policy in Nepal.…”

Section: Introductionmentioning

confidence: 99%

Healthcare Utilization and Out-of-Pocket Expenditures Associated with Depression in Adults: A Cross-Sectional Analysis in Nepal

Rajan

Rathod

Luitel³

et al. 2020

Preprint

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Background: Despite attempts to improve universal health coverage (UHC) in low income countries like Nepal, most healthcare utilization is still financed by out-of-pocket (OOP) payments, with detrimental effects on the poorest and most in need. Evidence from high income countries shows that depression is associated with increased healthcare utilization, which may lead to increased OOP expenditures, placing greater stress on families. To inform policies for integrating mental healthcare into UHC in LMIC, we must understand healthcare utilization and OOP expenditure patterns in people with depression. We examined associations between symptoms of depression and frequency and type of healthcare utilization and OOP expenditure among adults in Chitwan District, Nepal. Methods: We analysed data from a population-based survey of 2040 adults in 2013, who completed the PHQ-9 screening tool for depression and answered questions about healthcare utilization. We examined associations between increasing PHQ-9 score and healthcare utilization frequency and OOP expenditure using negative binomial regression. We also compared utilization of specific outpatient service providers and their related costs among adults with and without probable depression, determined by a PHQ-9 score of 10 or more. Results: We classified 80 (3.6%) participants with probable depression, 70.9% of whom used some form of healthcare in the past year compared to 43.9% of people without probable depression. Mean annual OOP healthcare expenditures were $118 USD in people with probable depression, compared to $110 USD in people without. With each unit increase in PHQ-9 score, there was a 14% increase in total healthcare visits (95% CI 7%-22%, p<0.0001) and $9 USD increase in OOP expenditures (95% CI $2-$17; p<0.0001). People with depression sought most healthcare from pharmacists (30.1%) but reported the greatest expenditure on specialist doctors ($36 USD). Conclusions: In this population-based sample from Central Nepal, we identified dose-dependent increases in healthcare utilization and OOP expenditure with increasing PHQ-9 scores. Future studies should evaluate whether provision of mental health services as an integrated component of UHC can improve overall health and reduce healthcare utilisation and expenditure, thereby alleviating financial pressures on families.

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“…Furthermore, recent years have witnessed a trend towards younger age-of-onset for depression and year-to-year increases in the number of adolescent patients with depression, many of whom also have strong suicidal ideation as well as suicidal behaviors (3,4). Consequently, it is a public health priority to diagnose and treat depression in both children and adults (5).…”

Section: Introductionmentioning

confidence: 99%

Unsupervised Classifications of Depression Levels Based on Machine Learning Algorithms Perform Well as Compared to Traditional Norm-Based Classifications

Yang

Chen

et al. 2020

Front. Psychiatry

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Large-scale screening for depression has been using norms developed based on a given population at a given time. Researchers have attempted to adjust the cutoff scores over time and for different populations, but such efforts are too few and far in between to be sensitive to temporal and regional variations. In this study, we proposed an unsupervised machine learning approach to constructing depression classifications to overcome the limitations of the traditional norm-based method. Data were collected from 8,063 Chinese middle and high school students. Using k-means clustering, we generated four levels of depressive symptoms to match the norm-based classifications. We then evaluated the validity of the classifications by comparing them with the norm-based method (and its variations) in terms of their robustness, model performance (accuracy, AUC, and sensitivity), and convergent construct validity (i.e., associations with known correlates). The results showed that our automatic classification system performed well as compared to the norm-based method.

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Scaling-up services for psychosis, depression and epilepsy in sub-Saharan Africa and South Asia: development and application of a mental health systems planning tool (OneHealth)

Abstract: This newly developed and validated module of OneHealth tool can be used, especially within the context of integrated health planning at the national level, to generate contextualised estimates of the resource needs, costs and health impacts of scaled-up mental health service delivery.

Cited by 51 publications

References 12 publications

Developing capacity-building activities for mental health system strengthening in low- and middle-income countries for service users and caregivers, service planners, and researchers

Developing capacity-building activities for mental health system strengthening in low- and middle-income countries for service users and caregivers, service planners, and researchers

Healthcare Utilization and Out-of-Pocket Expenditures Associated with Depression in Adults: A Cross-Sectional Analysis in Nepal

Unsupervised Classifications of Depression Levels Based on Machine Learning Algorithms Perform Well as Compared to Traditional Norm-Based Classifications

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