Maternal mental health in primary care in five low- and middle-income countries: A situational analysis

BMC Health Services Research, Volume 16, No. 1, Year 2016

Interpretation

Background: The integration of maternal mental health into primary health care has been advocated to reduce the mental health treatment gap in low- and middle-income countries (LMICs). This study reports findings of a cross-country situation analysis on maternal mental health and services available in five LMICs, to inform the development of integrated maternal mental health services integrated into primary health care. Methods: The situation analysis was conducted in five districts in Ethiopia, India, Nepal, South Africa and Uganda, as part of the Programme for Improving Mental Health Care (PRIME). The analysis reports secondary data on the prevalence and impact of priority maternal mental disorders (perinatal depression, alcohol use disorders during pregnancy and puerperal psychosis), existing policies, plans and services for maternal mental health, and other relevant contextual factors, such as explanatory models for mental illness. Results: Limited data were available at the district level, although generalizable data from other sites was identified in most cases. Community and facility-based prevalences ranged widely across PRIME countries for perinatal depression (3-50 %) and alcohol consumption during pregnancy (5-51 %). Maternal mental health was included in mental health policies in South Africa, India and Ethiopia, and a mental health care plan was in the process of being implemented in South Africa. No district reported dedicated maternal mental health services, but referrals to specialised care in psychiatric units or general hospitals were possible. No information was available on coverage for maternal mental health care. Challenges to the provision of maternal mental health care included; limited evidence on feasible detection and treatment strategies for maternal mental disorders, lack of mental health specialists in the public health sector, lack of prescribing guidelines for pregnant and breastfeeding women, and stigmatising attitudes among primary health care staff and the community. Conclusions: It is difficult to anticipate demand for mental health care at district level in the five countries, given the lack of evidence on the prevalence and treatment coverage of women with maternal mental disorders. Limited evidence on effective psychosocial interventions was also noted, and must be addressed for mental health programmes, such as PRIME, to implement feasible and effective services. This cross-sectional situation analysis of maternal mental health reports secondary data from the districts of Sodo (Ethiopia), Chitwan (Nepal), Sehore (India), Dr Kenneth Kaunda (Dr KK; South Africa) and Kamuli (Uganda). The situation analysis relied mostly on information available in the public domain. Sources included health surveillance data, research publications and personal communication with PRIME investigators, who are experts in the field of public health and maternal mental health. The PRIME districts offered different opportunities for the development and implementation of the district plans to integrate mental health into maternal health care, and presented a wide range of geographical, demographic, social and cultural profiles. A comprehensive overview of each district is provided elsewhere [29]. Briefly, district populations differed widely, from 162,000 in Sodo (Ethiopia) to 1,300,000 in Sehore (India). Most of the districts’ population lived in rural areas, besides Dr KK (South Africa), where approximately 85 % lived in highly dense urban settings. Each district was characterised by a diversity of ethnicities, religions and languages. Literacy was particularly low in Ethiopia (21.5 %) and in Uganda (62 %), and ranged between 74 and 88 % in India, Nepal and South Africa. Lack of infrastructure was a problem across districts, especially in Sodo (Ethiopia), with poor access to clean water, sanitation or electricity, though Dr KK (South Africa) was well resourced in comparison to the other districts. The situation analysis focused on the following four domains: Data were collected in three phases. The first consisted of extracting information relevant to maternal mental health, from the data collected between October and December 2011, using the PRIME situation analysis tool. This tool was developed by the PRIME consortium, to collect secondary data, needed for the planning of integrated mental healthcare in the PRIME districts (http://www.prime.uct.ac.za/images/prime/PRIME_Final_Situational_analysis_Tool.pdf). The tool focused on factors required for the implementation of WHO’s mhGAP intervention guide [30], with some items taken from the WHO Assessment Instrument for Mental Health Systems (WHO-AIMS) [31]. It comprised six sections: context, mental health policies and plans, mental health treatment coverage, district level health services, community, and monitoring and evaluation. More information on the development of the tool is provided elsewhere [29]. The situation analysis tool was completed by project coordinators and research staff from the PRIME countries. Data were then collated into four tables, one for each domain. The second phase, conducted from July to September 2014, consisted of asking PRIME research coordinators and officers to update any outdated data. The third and final phase, between October 2014 and February 2015, consisted of complementing any missing information and assessing data accuracy and quality. The evaluation of the trustworthiness of the findings from published paper was carried out using critical appraisal principles. For unpublished data, an attempt was made to ensure correctness by triangulating sources of data and going back to individuals within the PRIME research team with expert knowledge. A pragmatic approach was taken when reporting the data: where available, data from the districts were reported. Alternatively, information from neighbouring districts, regional or national data were provided where the data were thought to be generalizable to the PRIME district. Data from these sources were clearly differentiated when reporting the results. Only data available in the public domain were reported in the situation analysis, and PRIME investigators were consulted within their professional capacity. For this reason, ethical approval was not required for this study. Ethics approval was obtained for the overall PRIME study from the Human Research Ethics Committee at the Faculty of Health Sciences, University of Cape Town (HREC Ref 412/2011).

AI Digest

Study Justification:

– The study aims to address the mental health treatment gap in low- and middle-income countries (LMICs) by integrating maternal mental health into primary health care.
– The study provides a situational analysis of maternal mental health and available services in five LMICs, which can inform the development of integrated maternal mental health services.

Highlights:

– Limited data were available at the district level, but generalizable data from other sites was identified in most cases.
– Prevalence of perinatal depression and alcohol consumption during pregnancy varied widely across the countries.
– Maternal mental health was included in mental health policies in South Africa, India, and Ethiopia, and a mental health care plan was being implemented in South Africa.
– No district reported dedicated maternal mental health services, but referrals to specialized care were possible.
– Challenges to providing maternal mental health care included limited evidence on detection and treatment strategies, lack of mental health specialists, and stigmatizing attitudes among primary health care staff and the community.
– Effective psychosocial interventions for maternal mental health were also lacking.

Recommendations:

– Conduct further research to determine the prevalence and treatment coverage of women with maternal mental disorders at the district level.
– Address the lack of evidence on feasible detection and treatment strategies for maternal mental disorders.
– Increase the availability of mental health specialists in the public health sector.
– Develop prescribing guidelines for pregnant and breastfeeding women.
– Address stigmatizing attitudes among primary health care staff and the community.
– Focus on developing effective psychosocial interventions for maternal mental health.

Key Role Players:

– Researchers and experts in the field of public health and maternal mental health.
– Project coordinators and research staff from the PRIME countries.
– Mental health specialists.
– Primary health care staff.
– Community members and organizations.

Cost Items for Planning Recommendations:

– Research funding for further studies on prevalence and treatment coverage.
– Funding for training and increasing the availability of mental health specialists.
– Development and dissemination of prescribing guidelines.
– Awareness campaigns and training programs to address stigmatizing attitudes.
– Funding for the development and implementation of effective psychosocial interventions.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on secondary data and reports findings from a cross-country situation analysis. The study provides limited data at the district level, but generalizable data from other sites was identified in most cases. The study highlights the prevalence and impact of priority maternal mental disorders, existing policies and services for maternal mental health, and challenges to the provision of care. To improve the strength of the evidence, the study could include more primary data collection at the district level and provide more detailed information on the methodology used. Additionally, the study could consider including a larger sample size and conducting a longitudinal study to assess the effectiveness of integrated maternal mental health services in LMICs.

Abstract

This cross-sectional situation analysis of maternal mental health reports secondary data from the districts of Sodo (Ethiopia), Chitwan (Nepal), Sehore (India), Dr Kenneth Kaunda (Dr KK; South Africa) and Kamuli (Uganda). The situation analysis relied mostly on information available in the public domain. Sources included health surveillance data, research publications and personal communication with PRIME investigators, who are experts in the field of public health and maternal mental health. The PRIME districts offered different opportunities for the development and implementation of the district plans to integrate mental health into maternal health care, and presented a wide range of geographical, demographic, social and cultural profiles. A comprehensive overview of each district is provided elsewhere [29]. Briefly, district populations differed widely, from 162,000 in Sodo (Ethiopia) to 1,300,000 in Sehore (India). Most of the districts’ population lived in rural areas, besides Dr KK (South Africa), where approximately 85 % lived in highly dense urban settings. Each district was characterised by a diversity of ethnicities, religions and languages. Literacy was particularly low in Ethiopia (21.5 %) and in Uganda (62 %), and ranged between 74 and 88 % in India, Nepal and South Africa. Lack of infrastructure was a problem across districts, especially in Sodo (Ethiopia), with poor access to clean water, sanitation or electricity, though Dr KK (South Africa) was well resourced in comparison to the other districts. The situation analysis focused on the following four domains: Data were collected in three phases. The first consisted of extracting information relevant to maternal mental health, from the data collected between October and December 2011, using the PRIME situation analysis tool. This tool was developed by the PRIME consortium, to collect secondary data, needed for the planning of integrated mental healthcare in the PRIME districts (http://www.prime.uct.ac.za/images/prime/PRIME_Final_Situational_analysis_Tool.pdf). The tool focused on factors required for the implementation of WHO’s mhGAP intervention guide [30], with some items taken from the WHO Assessment Instrument for Mental Health Systems (WHO-AIMS) [31]. It comprised six sections: context, mental health policies and plans, mental health treatment coverage, district level health services, community, and monitoring and evaluation. More information on the development of the tool is provided elsewhere [29]. The situation analysis tool was completed by project coordinators and research staff from the PRIME countries. Data were then collated into four tables, one for each domain. The second phase, conducted from July to September 2014, consisted of asking PRIME research coordinators and officers to update any outdated data. The third and final phase, between October 2014 and February 2015, consisted of complementing any missing information and assessing data accuracy and quality. The evaluation of the trustworthiness of the findings from published paper was carried out using critical appraisal principles. For unpublished data, an attempt was made to ensure correctness by triangulating sources of data and going back to individuals within the PRIME research team with expert knowledge. A pragmatic approach was taken when reporting the data: where available, data from the districts were reported. Alternatively, information from neighbouring districts, regional or national data were provided where the data were thought to be generalizable to the PRIME district. Data from these sources were clearly differentiated when reporting the results. Only data available in the public domain were reported in the situation analysis, and PRIME investigators were consulted within their professional capacity. For this reason, ethical approval was not required for this study. Ethics approval was obtained for the overall PRIME study from the Human Research Ethics Committee at the Faculty of Health Sciences, University of Cape Town (HREC Ref 412/2011).

Materials

N/A

Innovations

Based on the provided information, here are some potential innovations that could be recommended to improve access to maternal health:

1. Telemedicine: Implementing telemedicine services can help overcome geographical barriers and improve access to maternal mental health care in remote areas. This technology allows healthcare providers to remotely diagnose and treat patients, reducing the need for in-person visits.

2. Mobile health (mHealth) applications: Developing mobile applications specifically designed for maternal mental health can provide women with easy access to information, resources, and support. These apps can offer self-help tools, educational materials, and connect women with healthcare professionals.

3. Training programs for primary healthcare providers: Implementing comprehensive training programs for primary healthcare providers can help improve their knowledge and skills in identifying and managing maternal mental health disorders. This can lead to earlier detection and appropriate treatment for women in need.

4. Community-based interventions: Establishing community-based interventions, such as support groups or peer counseling programs, can provide women with a safe and supportive environment to discuss their mental health concerns. These interventions can help reduce stigma and increase awareness about maternal mental health.

5. Integration of mental health services into primary healthcare: Integrating mental health services into existing primary healthcare systems can help ensure that women receive comprehensive care that addresses both their physical and mental health needs. This can involve training primary healthcare providers in mental health assessment and treatment, as well as establishing referral pathways to specialized care when needed.

It is important to note that these recommendations are based on the information provided and may need to be tailored to the specific context and resources available in each country.

AI Innovations Description

The recommendation to improve access to maternal health based on the described situation analysis is to develop and implement integrated maternal mental health services within primary health care in low- and middle-income countries (LMICs). This recommendation is supported by the findings that show limited data availability at the district level, wide-ranging prevalence rates of perinatal depression and alcohol consumption during pregnancy, and the lack of dedicated maternal mental health services in the districts studied.

To address these challenges, the development and implementation of integrated maternal mental health services should focus on the following areas:

1. Improve data collection: Enhance data collection efforts at the district level to gather accurate and comprehensive information on the prevalence and treatment coverage of women with maternal mental disorders. This will help in understanding the demand for mental health care and designing appropriate interventions.

2. Develop evidence-based interventions: Conduct research to identify feasible detection and treatment strategies for maternal mental disorders in LMICs. This will provide the evidence needed to implement effective psychosocial interventions and improve mental health programs.

3. Strengthen the mental health workforce: Address the shortage of mental health specialists in the public health sector by investing in training and capacity building programs. This will ensure that primary health care staff are equipped with the necessary skills to provide maternal mental health care.

4. Establish prescribing guidelines: Develop guidelines for prescribing medications to pregnant and breastfeeding women with mental health disorders. This will help healthcare providers make informed decisions and ensure the safe and appropriate use of medications during pregnancy and lactation.

5. Address stigma and attitudes: Implement awareness campaigns and training programs to address stigmatizing attitudes towards mental health among primary health care staff and the community. This will help reduce barriers to seeking and receiving maternal mental health care.

By implementing these recommendations, LMICs can improve access to maternal health by integrating mental health services into primary health care. This will contribute to reducing the mental health treatment gap and improving the overall well-being of mothers and their children.

AI Innovations Methodology

Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Increase awareness and education: Develop and implement public health campaigns to raise awareness about maternal mental health and reduce stigma associated with mental illness. This can include educating communities, healthcare providers, and policymakers about the importance of maternal mental health and the available services.

2. Strengthen primary healthcare systems: Improve the capacity of primary healthcare facilities to provide integrated maternal mental health services. This can be done by training healthcare providers on screening, diagnosis, and treatment of maternal mental disorders, as well as providing necessary resources and support.

3. Enhance collaboration and coordination: Foster collaboration between different stakeholders, including government agencies, non-governmental organizations, and community-based organizations, to ensure a coordinated approach to maternal mental health. This can involve establishing referral networks, sharing best practices, and coordinating efforts to address the barriers to access.

4. Develop and implement evidence-based interventions: Invest in research to identify effective interventions for maternal mental health in low- and middle-income countries. This can include evaluating the feasibility and effectiveness of psychosocial interventions, as well as developing guidelines for the detection and treatment of maternal mental disorders.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the indicators: Identify specific indicators that can measure the access to maternal health, such as the number of women receiving screening for maternal mental disorders, the number of women receiving treatment, or the reduction in stigma associated with mental illness.

2. Collect baseline data: Gather data on the current status of access to maternal health services, including the prevalence of maternal mental disorders, the availability of services, and the barriers to access. This can be done through surveys, interviews, and analysis of existing data sources.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on the access to maternal health. This model should consider factors such as population demographics, healthcare infrastructure, and resource allocation.

4. Run the simulation: Use the simulation model to project the potential impact of the recommendations over a specific time period. This can involve adjusting the input parameters based on the expected changes resulting from the recommendations and running the simulation multiple times to assess different scenarios.

5. Analyze the results: Evaluate the outcomes of the simulation to determine the potential improvements in access to maternal health. This can include analyzing changes in the identified indicators and comparing different scenarios to identify the most effective strategies.

6. Refine and validate the model: Continuously update and refine the simulation model based on new data and insights. Validate the model by comparing the projected outcomes with actual data as the recommendations are implemented.

By following this methodology, policymakers and stakeholders can gain insights into the potential impact of different recommendations on improving access to maternal health and make informed decisions on resource allocation and program implementation.

Author

Dima Health

Statistics:

Citations: 71

Identifiers:

DOI: 10.1186/s12913-016-1291-z

Research Areas:

Community Interventions, Disparities, Environmental, Health System and Policy, Maternal Access, Maternal and Child Health, Mental Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Substance Abuse

Study Countries:

Ethiopia, Multi-Countries, South Africa, Uganda

Study Design:

Cross Sectional Study, randomised-control-trial

Study Approach:

Systematic Review

Participants Gender:

Female