The prevalence of hypertension and its distribution by sociodemographic factors in Central Mozambique: a cross sectional study.

This study was supported by the Doris Duke Charitable Foundation’s African Health Initiative. The Doris Duke Charitable Foundation had no role in the design of the study, the collection, analysis, and interpretation of the data, and in writing the manuscriptBackground 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.Peer reviewe

The Systems Analysis and Improvement Approach: specifying core components of an implementation strategy to optimize care cascades in public health.

This work was supported from grants from the National Institutes of Health, including R01MH113435 (SAIA-SCALE), F32HD088204 and R34AI129900 (SAIA-PEDS), R21AI124399 (mPCAT), K24HD088229 (SAIA-FP), R21MH113691 (SAIA-MH), P30AI027757 (CFAR), R21DA046703 (SAIA-Naloxone), R01HL142412 (SAIA-HTN), 1UG3HL156390-01 (SCALE SAIA-HTN) R01HD0757 and R01HD0757-02S1 (SAIA), K08CA228761 (CCS SAIA) and T32AI070114 (UNC TIDE), Support was provided by the Implementation Science Core of the University of Washington/Fred Hutch Center for AIDS Research, an NIH-funded program under award number AI027757 which is supported by the following NIH Institutes and Centers: NIAID, NCI, NIMH, NIDA, NICHD, NHLBI, NIA, NIGMS, and NIDDK. This work was also supported by the Doris Duke Charitable Foundation and the Rita and Alex Hillman Foundation (SAIA-JUV), and the Thrasher Foundation (SAIA-MAL). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, the Doris Duke Charitable Foundation, the Rita and Alex Hillman Foundation, or the Thrasher Foundation. © 2023. The Author(s). Publisher Copyright: © 2023, The Author(s). © 2023. The Author(s).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 providers 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 providers 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 USA. 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 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 recommendations 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 modeling and simulation of change. Process mapping matched 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.Peer reviewe

Assessing the Reach, Adoption, Implementation, and Maintenance of the Systems Analysis and Improvement Approach for prevention of mother-to-child transmission of HIV in Manica Province, Mozambique 2018-2021 (the SAIA-SCALE Program)

Preprin

What if we decided to take care of everyone who needed treatment? Workforce planning in Mozambique using simulation of demand for HIV/AIDS care

Background: The growing AIDS epidemic in southern Africa is placing an increased strain on health systems, which are experiencing steadily rising patient loads. Health care systems are tackling the barriers to serving large populations in scaled-up operations. One of the most significant challenges in this effort is securing the health care workforce to deliver care in settings where the manpower is already in short supply. Methods: We have produced a demand-driven staffing model using simple spreadsheet technology, based on treatment protocols for HIV-positive patients that adhere to Mozambican guidelines. The model can be adjusted for the volumes of patients at differing stages of their disease, varying provider productivity, proportion who are pregnant, attrition rates, and other variables. Results: Our model projects the need for health workers using three different kinds of goals: 1) the number of patients to be placed on anti-retroviral therapy (ART), 2) the number of HIV-positive patients to be enrolled for treatment, and 3) the number of patients to be enrolled in a treatment facility per month. Conclusion: We propose three scenarios, depending on numbers of patients enrolled. In the first scenario, we start with 8000 patients on ART and increase that number to 58 000 at the end of three years (those were the goals for the country of Mozambique). This would require thirteen clinicians and just over ten nurses by the end of the first year, and 67 clinicians and 47 nurses at the end of the third year. In a second scenario, we start with 34 000 patients enrolled for care (not all of them on ART), and increase to 94 000 by the end of the third year, requiring a growth in clinician staff from 18 to 28. In a third scenario, we start a new clinic and enrol 200 new patients per month for three years, requiring 1.2 clinicians in year 1 and 2.2 by the end of year 3. Other clinician types in the model include nurses, social workers, pharmacists, phlebotomists, and peer counsellors. This planning tool could lead to more realistic and appropriate estimates of workforce levels required to provide high-quality HIV care in a low-resource settings

A systematic review of task- shifting for HIV treatment and care in Africa

BACKGROUND: Shortages of human resources for health (HRH) have severely hampered the rollout of antiretroviral therapy (ART) in sub-Saharan Africa. Current rollout models are hospital- and physician-intensive. Task shifting, or delegating tasks performed by physicians to staff with lower-level qualifications, is considered a means of expanding rollout in resource-poor or HRH-limited settings. METHODS: We conducted a systematic literature review. Medline, the Cochrane library, the Social Science Citation Index, and the South African National Health Research Database were searched with the following terms: task shift*, balance of care, non-physician clinicians, substitute health care worker, community care givers, primary healthcare teams, cadres, and nurs* HIV. We mined bibliographies and corresponded with authors for further results. Grey literature was searched online, and conference proceedings searched for abstracts. RESULTS: We found 2960 articles, of which 84 were included in the core review. 51 reported outcomes, including research from 10 countries in sub-Saharan Africa. The most common intervention studied was the delegation of tasks (especially initiating and monitoring HAART) from doctors to nurses and other non-physician clinicians. Five studies showed increased access to HAART through expanded clinical capacity; two concluded task shifting is cost effective; 9 showed staff equal or better quality of care; studies on non-physician clinician agreement with physician decisions was mixed, with the majority showing good agreement. CONCLUSIONS: Task shifting is an effective strategy for addressing shortages of HRH in HIV treatment and care. Task shifting offers high-quality, cost-effective care to more patients than a physician-centered model. The main challenges to implementation include adequate and sustainable training, support and pay for staff in new roles, the integration of new members into healthcare teams, and the compliance of regulatory bodies. Task shifting should be considered for careful implementation where HRH shortages threaten rollout programmes

Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey.

BACKGROUND: Organization of HIV care and treatment services, including clinic staffing and services, may shape clinical and financial outcomes, yet there has been little attempt to describe different models of HIV care in sub-Saharan Africa (SSA). Information about the relative benefits and drawbacks of different models could inform the scale-up of antiretroviral therapy (ART) and associated services in resource-limited settings (RLS), especially in light of expanded client populations with country adoption of WHO's test and treat recommendation. METHODS: We characterized task-shifting/task-sharing practices in 19 diverse ART clinics in Tanzania, Uganda, and Zambia and used cluster analysis to identify unique models of service provision. We ran descriptive statistics to explore how the clusters varied by environmental factors and programmatic characteristics. Finally, we employed the Delphi Method to make systematic use of expert opinions to ensure that the cluster variables were meaningful in the context of actual task-shifting of ART services in SSA. RESULTS: The cluster analysis identified three task-shifting/task-sharing models. The main differences across models were the availability of medical doctors, the scope of clinical responsibility assigned to nurses, and the use of lay health care workers. Patterns of healthcare staffing in HIV service delivery were associated with different environmental factors (e.g., health facility levels, urban vs. rural settings) and programme characteristics (e.g., community ART distribution or integrated tuberculosis treatment on-site). CONCLUSIONS: Understanding the relative advantages and disadvantages of different models of care can help national programmes adapt to increased client load, select optimal adherence strategies within decentralized models of care, and identify differentiated models of care for clients to meet the growing needs of long-term ART patients who require more complicated treatment management