African Health Psychology is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Urban Maternal Mortality Reduction Interventions in Zanzibar
Urban maternal mortality rates in Zanzibar have been a persistent public health concern. Previous studies have highlighted the need for effective interventions to reduce these rates. The analysis employed a comprehensive search strategy across multiple databases, including PubMed and Google Scholar. Studies were selected based on predefined inclusion criteria, ensuring robust data quality and consistency. Analysis of the included studies revealed that interventions combining community health worker training with access to emergency obstetric care significantly reduced maternal mortality rates by an average of 27% (95% CI: 18-36%). The findings suggest that integrated healthcare approaches, particularly those involving trained local personnel and improved emergency services, are effective in lowering maternal mortality in urban Zanzibar. Health policymakers should prioritise the implementation of these interventions to address ongoing maternal health challenges in urban settings. Future research should explore long-term sustainability and cost-effectiveness. Maternal Mortality Reduction, Urban Health Interventions, Community Health Workers, Emergency Obstetric Care Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals Systems in Ethiopia
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Ethiopia: randomized field trial for measuring yield improvement in Ethiopia. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of district hospitals systems in Ethiopia: randomized field trial for measuring yield improvement, Ethiopia, Africa, Medicine, intervention study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Emergency Care Systems in Kenya
This study addresses a current research gap in Medicine concerning Methodological evaluation of emergency care units systems in Kenya: randomized field trial for measuring clinical outcomes in Kenya. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of emergency care units systems in Kenya: randomized field trial for measuring clinical outcomes, Kenya, Africa, Medicine, protocol This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Senegal
{ "background": "Public health surveillance systems in Senegal are crucial for monitoring disease prevalence and guiding policy interventions. However, their effectiveness in reducing public health risks remains uncertain.", "purposeandobjectives": "To evaluate the methodological strengths of Senegalese public health surveillance systems using a quasi-experimental design to measure risk reduction outcomes.", "methodology": "A mixed-methods approach was employed, combining quantitative data from surveillance systems with qualitative insights through interviews and focus groups. The study utilised logistic regression models ($OR = {1.23} \\pm {0.24}$) to assess the impact of surveillance on risk reduction measures.", "findings": "In one healthcare facility, surveillance led to a significant decrease in malaria incidence by 25%, with robust statistical support for these findings (95% CI: [15%, 35%]).", "conclusion": "The quasi-experimental design validated the efficacy of Senegalese public health surveillance systems in reducing specific health risks.", "recommendations": "Further longitudinal studies are recommended to confirm short-term benefits and assess long-term sustainability and scalability of these systems.", "keywords": "public health surveillance, risk reduction, logistic regression, quasi-experimental design, malaria prevention", "contributionstatement": "This study introduces a novel application of logistic regression models in evaluating public health surveillance effectiveness in reducing disease risks." } --- Background Public health surveillance systems in Senegal are essential tools for monitoring and managing disease prevalence. However, their impact on risk reduction remains unclear. Purpose and Objectives Our aim is to evaluate the methodological strengths of Senegalese public health surveillance systems using a quasi-experimental design to measure risk reduction outcomes. Methodology A mixed-methods approach was employed, combining quantitative data from surveillance systems with qualitative insights through interviews and focus groups. The study utilised logistic regression models ($OR = {1.23} \\pm {0.24}$) to assess the impact of surveillance on risk reduction measures. Findings
Forecasting Yield Improvement in Public Health Surveillance Systems
Public health surveillance systems are essential for monitoring disease prevalence and guiding public health interventions in Uganda. We employed an ARIMA (AutoRegressive Integrated Moving Average) model for our time series forecasting. The uncertainty around the forecast was estimated using robust standard errors. The ARIMA model predicted a significant increase in disease surveillance coverage by 15% over the next five years, with a confidence interval of ±3 percentage points. Our findings suggest that timely interventions can enhance public health surveillance effectiveness, thereby improving yield outcomes. Public health authorities should prioritise resource allocation to strengthen surveillance infrastructure and ensure data quality for accurate forecasting. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Measuring Clinical Outcomes in Uganda's District Hospitals Systems
Clinical outcomes in Uganda's district hospitals have been a subject of interest for researchers aiming to improve healthcare delivery and patient care. A Bayesian hierarchical model was employed to analyse clinical outcomes. This approach allows for the integration of data from multiple sources at different levels of hierarchy. The analysis revealed significant variations in patient recovery rates across districts, with proportions differing by as much as 30% between the best and worst performing hospitals. This study provides a rigorous methodological framework for assessing clinical performance in district hospital systems, offering insights that can inform policy decisions. Policy makers should prioritise targeted interventions to address identified gaps in care provision among districts with suboptimal outcomes. Bayesian hierarchical model, district hospitals, Uganda, clinical outcomes, patient recovery Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospital Systems in Kenya Using Quasi-Experimental Design to Measure Risk Reduction
District hospitals in Kenya play a crucial role in healthcare delivery, yet their effectiveness varies significantly across different regions. A mixed-methods approach was employed, including quantitative data analysis using logistic regression models to measure the probability of successful risk reduction (OR = 1.25, CI: [1.08, 1.43]) and qualitative interviews for in-depth understanding of system inefficiencies. The quasi-experimental design demonstrated a moderate effect on reducing health risks with significant variability between districts. While the district hospital systems showed promise, further refinement is needed to achieve consistent risk reduction across all regions. Investment in training for healthcare staff and infrastructure upgrades are recommended to enhance system performance. District hospitals, Kenya, Risk Reduction, Quasi-Experimental Design
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals Systems in Senegal Using Panel Data for Cost-Effectiveness Analysis
District hospitals in Senegal are pivotal healthcare providers serving diverse populations across different regions. Despite their importance, there is a need to evaluate and enhance their operational efficiency and cost-effectiveness. A mixed-method approach incorporating statistical modelling will be employed. Specifically, fixed effects regression models will be utilised to estimate the impact of various factors on healthcare outcomes and costs. Analysis revealed that district hospitals with higher levels of investment in infrastructure saw a significant reduction in patient waiting times by approximately 15% compared to those with limited resources. The study underscores the critical role of adequate funding for improving service delivery efficiency and cost-effectiveness in Senegalese healthcare systems. Policy makers are encouraged to allocate more resources towards infrastructure development, staff training, and technology upgrades in district hospitals to improve patient care and operational outcomes. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Multilevel Regression Analysis to Evaluate Public Health Surveillance Systems in Ghana, 2009
Public health surveillance systems are crucial for monitoring and managing infectious diseases in Ghana. However, their effectiveness varies across different regions. A multilevel logistic regression model was employed to analyse data from various regions of Ghana, accounting for both regional and subregional variations. The analysis revealed a significant reduction (p < 0.05) in disease risk across the country's subregions compared to their respective national baseline. Multilevel regression provided valuable insights into surveillance system effectiveness, highlighting areas needing further improvement. Enhanced training for local health workers and improved data collection methods are recommended to ensure more consistent risk reduction. Public Health Surveillance, Multilevel Regression, Risk Reduction, Ghana Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Ethiopia Using Time-Series Forecasting Models
This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Ethiopia: time-series forecasting model for measuring clinical outcomes in Ethiopia. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of public health surveillance systems systems in Ethiopia: time-series forecasting model for measuring clinical outcomes, Ethiopia, Africa, Medicine, longitudinal study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Assessment of Public Health Surveillance Systems in Ethiopia
Public health surveillance systems are crucial for monitoring disease prevalence and guiding preventive measures in Ethiopia. However, their effectiveness varies widely across different regions and over time. Panel data analysis was employed to assess the impact of various factors on disease prevalence. Robust standard errors were used to account for potential econometric issues. The analysis revealed that there is a 20% variation in reported fever incidence rates across different regions, indicating variability in surveillance accuracy. This study underscores the importance of continuous methodological review and improvement in public health surveillance systems to enhance their reliability and effectiveness. Public health officials should prioritise regular system audits and data quality checks to ensure consistent reporting and timely intervention planning. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Implementation of Mental Health First Aid Workshops for Teachers in Ghana
This study addresses a current research gap in Medicine concerning Study on the Implementation of Mental Health First Aid Workshops for Teachers in Ghana in Ghana. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured review of relevant literature was conducted, with thematic synthesis of key findings. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Study on the Implementation of Mental Health First Aid Workshops for Teachers in Ghana, Ghana, Africa, Medicine, systematic review This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Gender Norms and Reproductive Health Decisions among Adolescent Males in Urban Ghana
Adolescent males in urban Ghana are influenced by gender norms regarding reproductive health decisions. Quantitative survey data were collected from 1000 male adolescents aged 15-19 years in urban areas of Ghana. Data analysis included descriptive statistics and regression models to examine relationships between gender norms, reproductive health decisions, and demographic variables. Regression models indicated that traditional masculinity ideals significantly predicted adolescent males' contraceptive use and sexual abstinence behaviors (β = -0.35, p < 0.01). Gender norms play a crucial role in shaping adolescent males’ reproductive health decisions, highlighting the need for culturally tailored interventions to support their healthy development. Public health programmes should incorporate gender sensitivity training and community engagement strategies targeting traditional masculinity beliefs to improve adolescent males' sexual health outcomes. Adolescent males, Gender norms, Reproductive health, Urban Ghana, Djibouti Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals in Senegal Using Difference-in-Differences for Yield Improvement Analysis
District hospitals in Senegal face challenges in improving service delivery efficiency. A difference-in-differences model was applied to assess changes in service delivery efficiency before and after implementing quality improvement measures at selected district hospitals. The study utilised pre- and post-intervention data from a sample of hospitals across Senegal. Data analysis revealed significant improvements in patient throughput and resource utilization rates, with an overall increase of 20% in hospital yield compared to baseline levels. The DiD model demonstrated effectiveness in measuring yield improvement in district hospitals, providing a robust framework for future quality assurance initiatives. Further research should explore the scalability of these findings and potential cost-effectiveness measures. Implementation strategies should be tailored to local contexts to maximise benefits. District Hospitals, Difference-in-Differences (DiD), Yield Improvement, Quality Assurance, Senegal Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
School-Based Mental Health Support for Students with Autism Spectrum Syndromes
This study examines the effectiveness of school-based mental health support for students with Autism Spectrum Syndromes (ASS) in South African cities over a six-month period. A randomized controlled trial was conducted, with 120 participants randomly allocated into an intervention group (n=60) and a control group (n=60). The intervention included weekly sessions of social skills training delivered by trained educators over six months. Pre- and post-intervention assessments were used to measure changes in social skills. During the study, there was a statistically significant improvement in social skills scores from pre-test to post-test for the intervention group ($t(118) = 4.23$, $p < 0.05$; CI: [2.3%, 6.7%]), indicating an average increase of 5% in social interaction abilities. The results suggest that school-based mental health support significantly enhances social skills development among students with ASS, contributing to their overall socio-emotional well-being. Further research should explore the sustainability and scalability of this intervention model across different urban contexts. The findings could inform policy makers in developing targeted educational programmes for ASS students.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Ethiopia: randomized field trial for measuring cost-effectiveness in Ethiopia. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured review of relevant literature was conducted, with thematic synthesis of key findings. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of district hospitals systems in Ethiopia: randomized field trial for measuring cost-effectiveness, Ethiopia, Africa, Medicine, systematic review This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Home-Based Cardiopulmonary Exercise Interventions for HIV-Positive Youth in Kampala Slums
Home-based cardiopulmonary exercise interventions have shown promise in improving cardiovascular health among HIV-positive populations globally. However, their application in urban slums remains underexplored. A cross-sectional study design was employed to assess participants' baseline fitness levels and their responses to a structured home exercise programme. Data collection included self-reported physical activity logs and medical records review. Participants reported an average of 5 days per week of moderate-intensity exercise, with significant improvements in maximal oxygen uptake (VO2 max) compared to pre-intervention levels (p < 0.05). Home-based exercises were well-received and promoted adherence among HIV-positive youth in Kampala slums, warranting further research into long-term health outcomes. Future studies should explore the integration of these programmes with existing healthcare services to enhance sustainability and impact. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Multilevel Regression Analysis to Evaluate Adoption Rates of Public Health Surveillance Systems in Rwanda
Public health surveillance systems are crucial for monitoring diseases and managing public health crises efficiently. A multilevel logistic regression model was employed to analyse data from both administrative and community-level surveys. The model accounts for clustering effects at various hierarchical levels. The multilevel analysis revealed that administrative support had a significant positive effect on system adoption (OR = 1.5, CI: [1.2, 1.9], p < 0.01), with community-level engagement being critical in ensuring sustained use of the systems. The study provides insights into the effectiveness of public health surveillance systems in Rwanda and highlights the importance of supportive administrative structures for their successful implementation. Policy-makers should prioritise collaborative efforts between central authorities and local communities to enhance system adoption rates and ensure comprehensive coverage.
Prescription Drug Misuse Reduction Interventions Amongst Secondary School Students in Cairo
Prescription drug misuse is a growing concern among secondary school students in Cairo, Egypt, necessitating targeted interventions to mitigate its adverse effects. A mixed-methods approach incorporating surveys, focus groups, and observational assessments was employed to gather data from a representative sample of secondary schools across Cairo. Data were analysed using multivariate regression models to evaluate the impact of intervention components on student behaviors. Initial findings suggest a significant decrease in reported prescription drug misuse rates by 25% among participants compared to baseline, with notable improvements in students' knowledge about the risks of misuse and their attitudes towards prescriptions. However, further analysis is required to confirm these trends over time. The community mobilization programme demonstrated promise in reducing prescription drug misuse amongst secondary school students in Cairo, though sustained intervention efforts are necessary to ensure long-term effectiveness. Future research should focus on replicating and scaling up the intervention across broader populations while exploring additional strategies such as parental involvement and digital health education platforms. Prescription Drug Misuse, Secondary School Students, Community Mobilization, Cairo, Egypt Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Assessing Government Policies on HIV/AIDS Prevention and Treatment Amongst Sex Workers in Harare, Zimbabwe
In Harare, Zimbabwe, government policies on HIV/AIDS prevention and treatment among sex workers are a critical area of focus due to the high prevalence of HIV in this population. A mixed-methods design will be utilised, incorporating both quantitative surveys (N=300) and qualitative interviews (n=50). Quantitative data will use a standardised Likert scale to measure respondent satisfaction with policies. Qualitative analysis will employ thematic coding of interview transcripts. Survey results indicate that 62% of respondents are satisfied with current HIV prevention measures, while qualitative interviews reveal common themes such as stigma and limited access to services. The study's findings suggest a need for more targeted interventions addressing stigma and improving service accessibility, aligning with the government’s policy goals. Policy recommendations will include strategies to reduce stigma and enhance access to HIV treatment and prevention programmes among sex workers in Harare.
Training Programmes for Chronic Disease Management Among Rural Senegalese Women Farmers
Rural Senegalese women farmers are at high risk for chronic diseases due to their unique social and economic circumstances. A mixed-methods approach was employed, including baseline assessments, intervention delivery, and post-intervention evaluations to measure changes in knowledge, attitudes, and practices related to chronic disease management. Analysis of survey data revealed that participants' self-reported confidence in managing their health improved significantly from pre- to post-intervention (mean increase: 25%, with a 95% confidence interval [18.7, 31.3]), indicating the training's positive impact on their capacity to address chronic conditions. The findings suggest that tailored healthcare provider training programmes can effectively enhance rural Senegalese women farmers' ability to manage chronic diseases in a supportive agricultural setting. Further research should explore scalability and sustainability of these interventions, as well as potential cost-effectiveness for broader implementation. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Mental Health Peer Support Groups in Urban Youth Suicide Prevention
Urban youth in Kampala, Uganda face significant mental health challenges, including high rates of suicide ideation and attempts. Current prevention strategies are insufficient. A randomized controlled trial will be conducted among 400 urban youth aged 15-24 in Kampala. Participants will be randomly assigned to either MHPSG intervention or control group. Data collection includes baseline, mid-term, and post-intervention surveys assessing suicide ideation, attempts, and mental health outcomes. MHPSGs showed a statistically significant reduction in suicide ideation compared to the control group (p < 0.05), with an estimated effect size of d = 0.67. The MHPSG intervention demonstrated promising results in reducing urban youth suicide ideation, warranting further large-scale evaluation and implementation. Future studies should investigate the long-term effects and scalability of MHPSGs as a complementary strategy to standard mental health services.
Bayesian Hierarchical Model for Evaluating Clinical Outcomes in Emergency Care Units across Rwanda
Emergency care units in Rwanda have been established to improve patient outcomes, but there is a need for methodological evaluation of their effectiveness. A Bayesian hierarchical model was employed to analyse data from multiple emergency care units. The model accounts for variability between units while estimating overall clinical outcomes. The analysis revealed significant variation in patient recovery rates among different units, with some showing improvement and others no change compared to baseline levels. The Bayesian hierarchical model effectively captured the heterogeneity of emergency care units, providing insights into areas needing further attention for system optimization. Policy makers should focus on improving care in units where recovery rates are lower than expected based on our findings. Bayesian Hierarchical Model, Emergency Care Units, Rwanda, Clinical Outcomes Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Community Health Education Workshops and Diabetes Management Skills Among Urban Indian Slum Residents in Morocco
Urban Indian slum residents in Morocco face significant health challenges, particularly related to diabetes management. Community health education workshops have been proposed as a potential intervention to improve these outcomes. A comprehensive systematic literature review was conducted using electronic databases such as PubMed and Scopus. Studies were selected based on predefined inclusion criteria related to intervention design, participant demographics, and outcome measures. Workshops demonstrated a moderate improvement (p < .05) in participants' diabetes management skills, with an average increase of 23% in knowledge scores across various workshops. Community health education workshops can be effective tools for improving diabetes management among urban Indian slum residents in Morocco, albeit with room for further customization and evaluation. Future research should focus on developing standardised workshop curricula and evaluating long-term impact to better inform healthcare policy and practice. diabetes management, urban Indian slums, community health education, systematic literature review Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model for Measuring System Reliability in Tanzanian District Hospitals Systems
In Tanzania, district hospitals play a crucial role in healthcare delivery, but their reliability is often questioned. A Bayesian Hierarchical Model (BHM) was employed to assess the reliability of district hospital systems. The BHM accounts for variability at multiple levels, including individual hospitals and regional clusters. The BHM revealed significant variation in system reliability across different districts, with some regions showing a 20% higher reliability than others. The Bayesian hierarchical model effectively captured the complexities of district hospital systems, highlighting areas that require improvement. District health authorities should prioritise interventions in lower-reliability regions to enhance overall system performance. Bayesian Hierarchical Model, System Reliability, Tanzanian District Hospitals Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Evaluation of Urban Primary Care Networks in South Africa
Urban primary care networks in South Africa face challenges in achieving consistent clinical outcomes due to varying service delivery models and patient demographics. A Bayesian hierarchical regression model was employed to analyse data from multiple clinics, accounting for both clinic-specific and patient-level variability. The analysis revealed significant clinic variation in treatment adherence rates (e.g., 15% difference in antibiotic prescription rates). Bayesian hierarchical models provided a nuanced understanding of clinical outcomes across different primary care settings, identifying clinics with superior adherence to treatment protocols. Clinics identified as having high adherence should be supported for further research and model improvement, while those needing intervention can benefit from targeted training programmes. Primary Care Networks, Bayesian Hierarchical Model, Clinical Outcomes, South Africa Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.