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This study sought to validate a combined assessment for major depression and generalized anxiety, administered by health providers in a primary care setting in Mozambique. Patients attending a primary care visit ( N = 502) were enrolled in the study and completed the Patient Health Questionniare–9, the Generalized Anxiety Disorder–7, and six items identified in a global systematic qualitative review of depression that were not captured in existing measures (e.g., social isolation, “thinking too much,” and “heart problems”). A separate trained mental health provider conducted the Mini International Neuropsychiatric Interview 5.0, adapted for Mozambique, to establish clinical diagnoses. Item response theory, factor analysis, and receiver operating characteristics were all used to identify the best screening items. Eight items were identified for the final screener: four items from the Patient Health Questionniare–9, two from the Generalized Anxiety Disorder–7, and two from the global depression literature. A cut-score of 7 was found to consistently increase the diagnostic likelihood of having a particular disorder. Overall, findings indicate good clinical utility of the screener in primary care in Mozambique.

INTRODUCTION: We integrated a transdiagnostic psychological intervention (Common Elements Treatment Approach [CETA]) into routine HIV care in Sofala, Mozambique. This task-shared program screens and treats newly-diagnosed HIV+ patients with comorbid mental health symptoms. METHODS: A mixed-methods evaluation included demographics, intake screening scores, and mental health symptoms, as well as barriers/facilitators to implementation examined by interviews. Multilevel models were used to analyze factors associated with symptom improvement and loss-to-follow-up (LTFU). RESULTS: From March 2019-June 2020, 820 individuals were screened for CETA treatment; 382 (46.6%) showed clinically-significant mental health symptoms and attended 1484 CETA sessions. 71.5% (n = 273/382) of CETA patients had general mental distress, 7.3% (n = 28) had alcohol abuse/dependence, 12.0% (n = 46) had suicidal ideation, 3.7% (n = 14) had other violent ideation, and 66.2% (n = 253) had experienced at least one traumatic event at intake. Mental health symptoms decreased 74.1% (17.0 to 4.4) after 5 CETA sessions, and 37.4% (n = 143) of patients achieved ≥50% symptom reduction from intake. LTFU was 29.1% (n = 111), but 59.5% (n = 66) of LTFU patients achieved ≥50% symptom reduction before LTFU. Facilitators for CETA implementation included readiness for change given the unaddressed burden of mental illness. Barriers included complexity of the intervention and stigma. CONCLUSIONS: Over 45% of newly-diagnosed HIV+ individuals in Mozambique have clinically-significant mental health symptoms at diagnosis. Integrating CETA into routine HIV platforms has in-context feasibility. Future implementation studies can optimize strategies for patient retention and scale-up.

Background: Healthcare systems in low-resource settings need simple, low-cost interventions to improve services and address gaps in care. Though routine data provide opportunities to guide these efforts, frontline healthcare workers (HCW) are rarely engaged in analyzing them for facility-level decision making. The Systems Analysis and Improvement Approach (SAIA) is an evidence-based, multi-component implementation strategy that engages HCW in use of facility-level data to promote systems-level thinking and quality improvement (QI) efforts within multi-step care cascades. SAIA was originally developed to address HIV care in resource-limited settings, but has since been adapted to a variety of clinical care systems including cervical cancer screening, mental health treatment, and hypertension management, among others; and across a variety of settings in sub-Saharan Africa and the United States. We aimed to extend the growing body of SAIA research by defining the core elements of SAIA using established specification approaches, and thus improve reproducibility, guide future adaptations and lay the groundwork to define its mechanism of action. Methods: Specification of the SAIA strategy was undertaken over 12 months by an expert panel of SAIA-researchers, implementing agents and stakeholders using a three-round, modified nominal group technique approach to match core SAIA components to the Expert Recommendations for Implementing Change (ERIC) list of distinct implementation strategies. Core implementation strategies were then specified according to Proctor’s recommendation for specifying and reporting, followed by synthesis of data on related implementation outcomes linked to the SAIA strategy across projects.Results: Based on this review and clarification of the operational definitions of the components of the SAIA, the four components of SAIA were mapped to 13 ERIC strategies. SAIA strategy meetings encompassed external facilitation, organization of provider implementation meetings, and provision of ongoing consultation. Cascade analysis mapped to three ERIC strategies; facilitating relay of clinical data to providers, use of audit and feedback of routine data with healthcare teams, and modelling and simulation of change. Process mapping tied to local needs assessment, local consensus discussions and assessment of readiness and identification of barriers and facilitators. Finally, continuous quality improvement encompassed tailoring strategies, developing a formal implementation blueprint, cyclical tests of change and purposefully re-examining the implementation process.Conclusions: Specifying the components of SAIA provides improved conceptual clarity to enhance reproducibility for other researchers and practitioners interested in applying the SAIA across novel settings.

Background: The Systems Analysis and Improvement Approach (SAIA) is an evidence-based, multi-component implementation strategy that engages service providers in the use of routinely-available service data to optimize service delivery cascades and promote systems-level thinking. SAIA was originally developed to address bottlenecks in HIV care in low-and middle-income countries, but has since been adapted and applied to a variety of care systems including: cervical cancer screening, mental health treatment, hypertension management, family planning, and community-based naloxone distribution. These projects have been implemented across a variety of settings in sub-Saharan Africa and the United States. Given the diversity of implementation experience, our consortium aimed to define the core elements of SAIA, to improve reproducibility, guide future adaptations, and lay the groundwork to evaluate mechanisms of action. Methods: Specification of the SAIA strategy was undertaken over 12 months by an expert panel of SAIA researchers, implementing agents and stakeholders, using a three-round, modified nominal group technique approach to match core SAIA components to the Expert Recommendations for Implementing Change (ERIC) list of distinct implementation strategies. Core implementation strategies were then specified according to Proctor’s recommendation for specifying and reporting, followed by synthesis of data on related implementation outcomes linked to the SAIA strategy across projects.Results: The four components of the SAIA strategy: (1) SAIA strategy meetings; (2) cascade analysis; (3) process mapping; and (4) continuous quality improvement, mapped to 13 distinct ERIC strategies. The SAIA strategy meetings component mapped to external facilitation, organization of provider implementation meetings, and provision of ongoing consultation. Cascade analysis mapped to facilitating relay of clinical data to providers, use of audit and feedback, and modelling and simulation of change. Process mapping tied to local needs assessment, local consensus discussions, and assessment of readiness and identification of barriers and facilitators. Continuous quality improvement encompassed tailoring strategies, developing a formal implementation blueprint, cyclical tests of change and purposefully re-examining the implementation process.Conclusions: Formally specifying the core components of SAIA provides improved conceptual clarity to enhance reproducibility for other researchers and practitioners interested in applying the SAIA across novel settings. Furthermore, this work provides a structured framework to examine potential mechanisms of SAIA and its component implementation strategies.

Background Cascades have been used to characterize sequential steps within a complex health system and are used in diverse disease areas and across prevention, testing, and treatment. Routine data have great potential to inform prioritization within a system, but are often inaccessible to frontline health care workers (HCWs) who may have the greatest opportunity to innovate health system improvement. Methods The cascade analysis tool (CAT) is an Excel-based, simple simulation model with an optimization function. It identifies the step within a cascade that could most improve the system. The original CAT was developed for HIV treatment and the prevention of mother-to-child transmission of HIV. Results CAT has been adapted 7 times: to a mobile application for prevention of mother-to-child transmission; for hypertension screening and management and for mental health outpatient services in Mozambique; for pediatric and adolescent HIV testing and treatment, HIV testing in family planning, and cervical cancer screening and treatment in Kenya; and for naloxone distribution and opioid overdose reversal in the United States. The main domains of adaptation have been technical-estimating denominators and structuring steps to be binary sequential steps-as well as logistical-identifying acceptable approaches for data abstraction and aggregation, and not overburdening HCW. Discussion CAT allows for prompt feedback to HCWs, increases HCW autonomy, and allows managers to allocate resources and time in an equitable manner. CAT is an effective, feasible, and acceptable implementation strategy to prioritize areas most requiring improvement within complex health systems, although adaptations are being currently evaluated.

Background No validated tools exist to screen for substance use or dependence in Mozambique. The aim of this study was to validate the Alcohol Use Disorder Identification Test (AUDIT) for use in primary care settings in Mozambique. Methods The study administered a final adapted Mozambican 10-item AUDIT (AUDIT-10-MZ) to 502 individuals from antenatal, postpartum, and general outpatient consultations in three Ministry of Health primary health care clinics in Sofala Province, Mozambique. The study evaluated the AUDIT-10-MZ against the MINI 5.0-MZ as a gold standard diagnostic tool. Results Using the MINI 5.0-MZ, 16 (3.2%) of the sample tested positive for alcohol dependence and 3 (0.6%) tested positive for harmful alcohol use. The full AUDIT-10-MZ had acceptable internal consistency (α = 0.74); however, the shorter AUDIT-C-MZ had a higher alpha value than the full AUDIT screener (α = 0.79). The AUDIT-10-MZ performed well for screening in primary care, achieving areas under the receiver operating characteristic curves (AUROCs) of 0.94 (95% CI: 0.91, 0.96) for alcohol dependence. The AUDIT-C-MZ also performed well with an AUROC of 0.88 (95% CI: 0.80, 0.96) for alcohol dependence. Using a cut-off of ≥6, the AUDIT-10-MZ achieved a sensitivity of 68.8% and specificity of 92.0% for screening for alcohol dependence; a cut-off of ≥3 for the AUDIT-C-MZ achieved a sensitivity of 56.3% and specificity of 90.7%. Conclusions Both the AUDIT-10-MZ and AUDIT-C-MZ are valid instruments for screening for alcohol dependence in Mozambique. The AUDIT-C-MZ performed particularly well and providers could use it as a brief screener in primary care settings. Optimal cut-points will depend on weighing false positives and false negatives but could be employed at ≥ 6 or ≥ 7 for the AUDIT-10-MZ and at ≥ 2 or ≥ 3 for the AUDIT-C-MZ. Future implementation research is needed to examine how best to integrate screening for substance use or dependence in primary care settings in Mozambique and other similar LMICs.

Substantial investments are being made to scale-up access to mental healthcare in low- and middle-income countries, but less attention has been paid to quality and performance of nascent public-sector mental healthcare systems. This study tested the initial effectiveness of an implementation strategy to optimize routine outpatient mental healthcare cascade performance in Mozambique [the Systems Analysis and Improvement Approach for Mental Health (SAIA-MH)]. This study employed a pre–post design from September 2018 to August 2019 across four Ministry of Health clinics among 810 patients and 3234 outpatient mental health visits. Effectiveness outcomes evaluated progression through the care cascade, including: (1) initial diagnosis and medication selection; (2) enrolling in follow-up care; (3) returning after initial consultation within 60 days; (4) returning for follow-up visits on time; (5) returning for follow-up visits adherent to medication and (6) achieving function improvement. Clustered generalized linear models evaluated odds of completing cascade steps pre- vs post-intervention. Facilities prioritized improvements focused on the follow-up cascade, with 62.5% (10 of 16) monthly system modifications targeting medication adherence. At baseline, only 4.2% of patient visits achieved function improvement; during the 6 months of SAIA-MH implementation, this improved to 13.1% of patient visits. Multilevel logistic regression found increased odds of returning on time and adherent [aOR = 1.53, 95% CI (1.21, 1.94), P = 0.0004] and returning on time, adherent and with function improvement [aOR = 3.68, 95% CI (2.57, 5.44), P

National Institutes of Health (NIH) Background: Depression is one of the leading causes of disability in Mozambique; however, few patients with depression are identified in primary care. To our knowledge, there are no validated tools for depression screening in Mozambique. The aim of this study was to validate the Patient Health Questionnaire-9 (PHQ-9) for use in primary care settings in Mozambique. Methods: The PHQ-9 was adapted using a structured multi-phase process led by a team of bilingual experts followed by a review by lay individuals and pilot-testing including cognitive interviews. The final Mozambican PHQ- 9 (PHQ-9-MZ) was applied among 502 individuals randomly selected from antenatal, postpartum, and general outpatient consultations in three Ministry of Health primary healthcare clinics in Sofala Province, Mozambique. The PHQ-9-MZ was evaluated against the MINI 5.0-MZ as a gold standard diagnostic tool. Results: The majority of participants were female (74%), with a mean age of 28. Using the MINI 5.0-MZ, 43 (9%) of the sample tested positive for major depressive disorder. Items of the PHQ-9-MZ showed good discrimination and factor loadings. One latent factor of depression explained 54% of the variance in scores. Questions 3 (sleep) and 5 (appetite) had the lowest item discrimination and factor loadings. The PHQ-9-MZ showed good internal consistency, with a Cronbach’s alpha of 0.84, and an area under the receiver operating characteristic curve (AUROC) of 0.81 (95% CI: 0.73, 0.89). The PHQ-2-MZ had an AUROC of 0.78 (95% CI: 0.70, 0.85). Using a cut-point of ≥9, the PHQ-9-MZ had a sensitivity of 46.5% and a specificity of 93.5%. Using a cut-point of ≥2, the PHQ-2-MZ had a sensitivity of 74.4% and a specificity of 71.7%. Increasing the cut-point to ≥3, the PHQ-2-MZ has a sensitivity of 32.6% and a specificity of 94.6%. Conclusions: The PHQ-9-MZ and PHQ-2-MZ emerge as two valid alternatives for screening for depression in primary health care settings in Mozambique. Depending on program needs and weighing the value of minimizing false positives and false negatives, the PHQ-9-MZ can be employed with cut-points ranging from ≥8 to ≥11, and the PHQ-2-MZ with cut-points ranging from ≥2 to ≥3. Department of Mental Health, Sofala Provincial Health Directorate, Ministry of Health, Rua Poder Popular n.° 11 – 50. Caixa Postal 583. 4° Andar, Beira, Sofala, Moçambique Faculdade de Medicina, Universidade Eduardo Mondlane, Maputo, Moçambique Health Alliance International, Beira, Mozambique Health Alliance International, Seattle, WA, USA Department of Global Health, University of Washington, Seattle, WA, USA Department of Epidemiology, University of Washington, Seattle, WA, USA Departamento de Psiquiatria, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brazil

Background Hypertension (HTN) is a major risk factor for cardiovascular diseases, and its prevalence has been rising in low- and middle-income countries. The current study describes HTN prevalence in central Mozambique, association between wealth and blood pressure (BP), and HTN monitoring and diagnosis practice among individuals with elevated BP. Methods The study used data from a cross-sectional, representative household survey conducted in Manica and Sofala provinces, Mozambique. There were 4101 respondents, aged ≥20 years. We measured average systolic and diastolic BP (SBP and DBP) from three measurements taken in the household setting. Elevated BP was defined as having either SBP ≥140 or DBP ≥90 mmHg. Results The mean age of the participants was 36.7 years old, 59.9% were women, and 72.5% were from rural areas. Adjusting for complex survey weights, 15.7% (95%CI: 14.0 to 17.4) of women and 16.1% (13.9 to 18.5) of men had elevated BP, and 7.5% (95% CI: 6.4 to 8.7) of the overall population had both SBP ≥140 and DBP ≥90 mmHg. Among participants with elevated BP, proportions of participants who had previous BP measurement and HTN diagnosis were both low (34.9% (95% CI: 30.0 to 40.1) and 12.2% (9.9 to 15.0) respectively). Prior BP measurement and HTN diagnosis were more commonly reported among hypertensive participants with secondary or higher education, from urban areas, and with highest relative wealth. In adjusted models, wealth was positively associated with higher SBP and DBP. Conclusions The current study found evidence of positive association between wealth and BP. The prevalence of elevated BP was lower in Manica and Sofala provinces than the previously estimated national prevalence. Previous BP screening and HTN diagnosis were uncommon in our study population, especially among rural residents, individuals with lower education levels, and those with relatively less wealth. As the epidemiological transition advances in Mozambique, there is a need to develop and implement strategies to increase BP screening and deliver appropriate clinical services, as well as to encourage lifestyle changes among people at risk of developing hypertension in near future.

Background Lack of accurate data on the distribution of sub-national populations in low- and middle-income countries impairs planning, monitoring, and evaluation of interventions. Novel, low-cost methods to develop unbiased survey sampling frames at sub-national, sub-provincial, and even sub-district levels are urgently needed. This article details our experience using remote satellite imagery to develop a provincial-level representative community survey sampling frame to evaluate the effects of a 7-year health system intervention in Sofala Province, Mozambique. Methods Mozambique’s most recent census was conducted in 2007, and no data are readily available to generate enumeration areas for representative health survey sampling frames. To remedy this, we partnered with the Humanitarian OpenStreetMap Team to digitize every building in Sofala and Manica provinces (685,189 Sofala; 925,713 Manica) using up-to-date remote satellite imagery, with final results deposited in the open-source OpenStreetMap database. We then created a probability proportional to size sampling frame by overlaying a grid of 2.106 km resolution (0.02 decimal degrees) across each province, and calculating the number of buildings within each grid square. Squares containing buildings were used as our primary sampling unit with replacement. Study teams navigated to the geographic center of each selected square using geographic positioning system coordinates, and then conducted a standard “random walk” procedure to select 20 households for each time a given square was selected. Based on sample size calculations, we targeted a minimum of 1500 households in each province. We selected 88 grids within each province to reach 1760 households, anticipating ongoing conflict and transport issues could preclude the inclusion of some clusters. Results Civil conflict issues forced the exclusion of 8 of 31 subdistricts in Sofala and 15 of 39 subdistricts in Manica. Using Android tablets, Open Data Kit software, and a remote RedCap data capture system, our final sample included 1549 households in Sofala (4669 adults; 4766 children; 33 missing age) and 1538 households in Manica (4422 adults; 4898 children; 33 missing age). Conclusions Other implementation or evaluation teams may consider employing similar methods to track population distributions for health systems planning or the development of representative sampling frames using remote satellite imagery. Electronic supplementary material The online version of this article (10.1186/s12942-018-0158-4) contains supplementary material, which is available to authorized users.

An amendment to this paper has been published and can be accessed via the original article.