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: 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.

BackgroundLack 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.MethodsMozambique’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.ResultsCivil 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).ConclusionsOther 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 materialThe online version of this article (10.1186/s12942-018-0158-4) contains supplementary material, which is available to authorized users.

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 < 0.0001] after SAIA-MH implementation. No significant differences were observed regarding other cascade steps. The SAIA-MH implementation strategy shows promise for rapidly and significantly improving mental healthcare cascade outcomes, including the ultimate goal of patient function improvement. Given poor baseline mental healthcare cascade performance, there is an urgent need for evidence-based implementation strategies to optimize the performance of mental healthcare cascades in low- and middle-income countries.

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.