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The MNH eCohort was developed to fill gaps in maternal and newborn health (MNH) care quality measurement. In this paper, we describe the survey development process, recruitment strategy, data collection procedures, survey content and plans for analysis of the data generated by the study. We also compare the survey content to that of existing multi-country tools on MNH care quality. The eCohort is a longitudinal mixed-mode (in-person and phone) survey that will recruit women in health facilities at their first antenatal care (ANC) visit. Women will be followed via phone survey until 10-12 weeks postpartum. User-reported information will be complemented with data from physical health assessments at baseline and endline, extraction from MNH cards, and a brief facility survey. The final MNH eCohort instrument is centered around six key domains of high-quality health systems including competent care (content of ANC, delivery, and postnatal care for the mother and newborn), competent systems (prevention and detection, timely care, continuity, integration), user experience, health outcomes, confidence in the health system, and economic outcomes. The eCohort combines the maternal and newborn experience and, due to its longitudinal nature, will allow for quality assessment according to specific risks that evolve throughout the pregnancy and postpartum period. Detailed information on medical and obstetric history and current health status of respondents and newborns will allow us to determine whether women and newborns at risk are receiving needed care. The MNH eCohort will answer novel questions to guide health system improvements and to fill data gaps in implementing countries.

Abstract Introduction The treatment gap for mental health disorders persists in low‐ and middle‐income countries despite overwhelming evidence of the efficacy of task‐sharing mental health interventions. Key barriers in the uptake of these innovations include the absence of policy to support implementation and diverting of staff from usual routines in health systems that are already overstretched. South Africa enjoys a conducive policy environment; however, strategies for operationalizing the policy ideals are lacking. This paper describes the Mental health INTegration Programme (MhINT), which adopted a health system strengthening approach to embed an evidence‐based task‐sharing care package for depression to integrate mental health care into chronic care at primary health care (PHC). Methods The MhINT care package consisting of psycho‐education talks, nurse‐led mental health assessment, and a structured psychosocial counselling intervention provided by lay counsellors was implemented in Amajuba district in KwaZulu‐Natal over a 2‐year period. A learning health systems approach was adopted, using continuous quality improvement (CQI) strategies to facilitate embedding of the intervention. MhINT was implemented along five phases: the project phase wherein teams to drive implementation were formed; the diagnostic phase where routinely collected data were used to identify system barriers to integrated mental health care; the intervention phase consisting of capacity building and using Plan‐Do‐Study‐Act cycles to address implementation barriers and the impact and sustaining improvement phases entailed assessing the impact of the program and initiation of system‐level interventions to sustain and institutionalize successful change ideas. Results Integrated planning and monitoring were enabled by including key mental health service indicators in weekly meetings designed to track the performance of noncommunicable diseases and human immunovirus clinical programmes. Lack of standardization in mental health screening prompted the validation of a mental health screening tool and testing feasibility of its use in centralized screening stations. A culture of collaborative problem‐solving was promoted through CQI data‐driven learning sessions. The province‐level screening rate increased by 10%, whilst the district screening rate increased by 7% and new patients initiated to mental health treatment increased by 16%. Conclusions The CQI approach holds promise in facilitating the attainment of integrated mental health care in resource‐scarce contexts. A collaborative relationship between researchers and health system stakeholders is an important strategy for facilitating the uptake of evidence‐based innovations. However, the lack of interventions to address healthcare workers' own mental health poses a threat to integrated mental health care at PHC.

Abstract Background During the COVID-19 pandemic, governments and researchers have used routine health data to estimate potential declines in the delivery and uptake of essential health services. This research relies on the data being high quality and, crucially, on the data quality not changing because of the pandemic. In this paper, we investigated those assumptions and assessed data quality before and during COVID-19. Methods We obtained routine health data from the DHIS2 platforms in Ethiopia, Haiti, Lao People’s Democratic Republic, Nepal, and South Africa (KwaZulu-Natal province) for a range of 40 indicators on essential health services and institutional deaths. We extracted data over 24 months (January 2019–December 2020) including pre-pandemic data and the first 9 months of the pandemic. We assessed four dimensions of data quality: reporting completeness, presence of outliers, internal consistency, and external consistency. Results We found high reporting completeness across countries and services and few declines in reporting at the onset of the pandemic. Positive outliers represented fewer than 1% of facility-month observations across services. Assessment of internal consistency across vaccine indicators found similar reporting of vaccines in all countries. Comparing cesarean section rates in the HMIS to those from population-representative surveys, we found high external consistency in all countries analyzed. Conclusions While efforts remain to improve the quality of these data, our results show that several indicators in the HMIS can be reliably used to monitor service provision over time in these five countries.

Background: Poor mental health literacy, misinformation about treatment and stigma result in low demand for mental health services in low-and middle-income countries. Community-based interventions that raise mental health awareness and facilitate detection of mental health conditions, are instrumental in increasing demand through strengthened mental health literacy, as well as supply of available mental health services through strengthened detection and linkage to care. Objective: To assess the feasibility of a Community Mental Health Education and Detection Tool (CMED) for use with household members by community health teams in South Africa. Methods: The feasibility of using the CMED in households was assessed using Bowen et al.‘s framework which informed the study design, interview tools and analysis. The feasibility study involved four phases: (1) observations of the CMED consultation to evaluate the administration of the tool; (2) semi-structured interviews with household member/s after the CMED was administered to explore experiences of the visit; (3) follow-up interviews of household members referred using the CMED tool to assess uptake of referrals; (4) and weekly focus group discussions with the community health team to explore experiences of using the tool. Framework analysis was used to inform a priori themes and allow inductive themes to emerge from the data. Results: The CMED was found to be acceptable by both community health teams and household members, demand for the tool was evident, implementation, practicality and integration within the existing health system were also indicated. Conclusion: The CMED is perceived as feasible by household members and community health teams, suggesting a ‘goodness of fit” within the existing health system.

Abstract COVID-19 has prompted the use of readily available administrative data to track health system performance in times of crisis and to monitor disruptions in essential healthcare services. In this commentary we describe our experience working with these data and lessons learned across countries. Since April 2020, the Quality Evidence for Health System Transformation (QuEST) network has used administrative data and routine health information systems (RHIS) to assess health system performance during COVID-19 in Chile, Ethiopia, Ghana, Haiti, Lao People’s Democratic Republic, Mexico, Nepal, South Africa, Republic of Korea and Thailand. We compiled a large set of indicators related to common health conditions for the purpose of multicountry comparisons. The study compiled 73 indicators. A total of 43% of the indicators compiled pertained to reproductive, maternal, newborn and child health (RMNCH). Only 12% of the indicators were related to hypertension, diabetes or cancer care. We also found few indicators related to mental health services and outcomes within these data systems. Moreover, 72% of the indicators compiled were related to volume of services delivered, 18% to health outcomes and only 10% to the quality of processes of care. While several datasets were complete or near-complete censuses of all health facilities in the country, others excluded some facility types or population groups. In some countries, RHIS did not capture services delivered through non-visit or nonconventional care during COVID-19, such as telemedicine. We propose the following recommendations to improve the analysis of administrative and RHIS data to track health system performance in times of crisis: ensure the scope of health conditions covered is aligned with the burden of disease, increase the number of indicators related to quality of care and health outcomes; incorporate data on nonconventional care such as telehealth; continue improving data quality and expand reporting from private sector facilities; move towards collecting patient-level data through electronic health records to facilitate quality-of-care assessment and equity analyses; implement more resilient and standardized health information technologies; reduce delays and loosen restrictions for researchers to access the data; complement routine data with patient-reported data; and employ mixed methods to better understand the underlying causes of service disruptions.

Abstract Background Screening tools for mental health disorders improve detection at a primary health care (PHC) level. However, many people with mental health conditions do not seek care because of a lack of knowledge about mental health, stigma about mental illness and a lack of awareness of mental health services available at a PHC facility level. Interventions at a community level that raise awareness about mental health and improve detection of mental health conditions, are thus important in increasing demand and optimising the supply of available mental health services. This study sought to evaluate the accuracy of a Community Mental Health Education and Detection (CMED) Tool in identifying mental health conditions using pictorial vignettes. Methods Community Health Workers (CHWs) administered the CMED tool to 198 participants on routine visits to households. Consenting family members provided basic biographical information prior to the administration of the tool. To determine the accuracy of the CMED in identifying individuals in households with possible mental health disorders, we compared the number of individuals identified using the CMED vignettes to the validated Brief Mental Health (BMH) screening tool. Results The CMED performed at an acceptable level with an area under the curve (AUC) of 0.73 (95% CI 0.67–0.79), identifying 79% (sensitivity) of participants as having a possible mental health problem and 67% (specificity) of participants as not having a mental health problem. Overall, the CMED positively identified 55.2% of household members relative to 49.5% on the BMH. Conclusion The CMED is acceptable as a mental health screening tool for use by CHWs at a household level.

Integration of mental health into routine primary health care (PHC) services in low-and middle-income countries is globally accepted to improve health outcomes of other conditions and narrow the mental health treatment gap. Yet implementation remains a challenge. The aim of this study was to identify implementation strategies that improve implementation outcomes of an evidence-based depression care collaborative implementation model integrated with routine PHC clinic services in South Africa. An iterative, quasi-experimental, observational implementation research design, incorporating the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework, was applied to evaluate implementation outcomes of a strengthened package of implementation strategies (stage two) compared with an initial evaluation of the model (stage one). The first stage package was implemented and evaluated in 10 PHC clinics and the second stage strengthened package in 19 PHC clinics (inclusive of the initial 10 clinics) in one resource-scarce district in the province of KwaZulu-Natal, South Africa. Diagnosed service users were more likely to be referred for counselling treatment in the second stage compared with stage one (OR 23.15, SE = 18.03, z = 4.04, 95%CI [5.03-106.49], p < .001). Training in and use of a validated, mandated mental health screening tool, including on-site educational outreach and technical support visits, was an important promoter of nurse-level diagnosis rates (OR 3.75, 95% CI [1.19, 11.80], p = 0.02). Nurses who perceived the integrated care model as acceptable were also more likely to successfully diagnose patients (OR 2.57, 95% CI [1.03-6.40], p = 0.043). Consistent availability of a clinic counsellor was associated with a greater probability of referral (OR 5.9, 95%CI [1.29-27.75], p = 0.022). Treatment uptake among referred service users remained a concern across both stages, with inconsistent co-located counselling services associated with poor uptake. The importance of implementation research for strengthening implementation strategies along the cascade of care for integrating depression care within routine PHC services is highlighted.