Pan African Journal of Educational Policy, Research and Practice
Pan African Journal of Educational Policy, Research and Practice is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Bayesian Hierarchical Model Assessment of Community Health Centre Reliability in Rwanda,
Community health centers in Rwanda have been pivotal in addressing healthcare needs across diverse geographic and socioeconomic settings. Despite their importance, there is a need for methodological evaluation to assess the reliability of these systems. A Bayesian hierarchical model was employed to analyse data from multiple community health centers. This approach allowed for the estimation of uncertainty and variability across different sites while accounting for site-specific factors. The analysis revealed significant heterogeneity in service delivery quality among the health centers, with some facilities achieving higher reliability scores than others. The findings suggest that targeted interventions focusing on areas of low reliability could enhance overall system performance and improve patient outcomes. Future research should focus on implementing evidence-based guidelines and training programmes to address identified weaknesses in the less reliable centers. 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) 2010 https://creativecommons.org/licenses/by/4.0/
Multilevel Regression Analysis to Evaluate Emergency Care Units in Ethiopia
Emergency care units (ECUs) play a critical role in healthcare systems, particularly in resource-limited settings such as Ethiopia. A multilevel regression model was applied to analyse data from multiple levels (individual patient, ECU, and regional health facilities) to measure clinical outcomes such as survival rates post-emergency. The multilevel model showed that the presence of a dedicated pediatric ECU significantly improved child survival rates by 15% in rural areas compared to non-pediatric ECUs. This study demonstrated the effectiveness of multilevel regression analysis for evaluating clinical outcomes in emergency care units, providing robust estimates and addressing potential sources of bias. Future research should consider expanding the model to include more variables and regions to enhance generalizability. Emergency Care Units, Multilevel Regression Analysis, Clinical Outcomes, Ethiopia 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 and Efficiency Gains in District Hospitals System in Kenya Using Difference-in-Differences Models
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Kenya: difference-in-differences model for measuring efficiency gains in Kenya. 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 Kenya: difference-in-differences model for measuring efficiency gains, Kenya, 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.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Maternal Care Facilities Systems in South Africa Using Multilevel Regression Analysis for Clinical Outcome Measurement
This study addresses a current research gap in Medicine concerning Methodological evaluation of maternal care facilities systems in South Africa: multilevel regression analysis for measuring clinical outcomes in South Africa. 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 maternal care facilities systems in South Africa: multilevel regression analysis for measuring clinical outcomes, South Africa, 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.
Methodological Evaluation of Community Health Centre Systems in Kenya Using Quasi-Experimental Design to Assess System Reliability
Community health centers in Kenya face challenges related to system reliability and sustainability. A mixed-methods approach combining quantitative data analysis with qualitative interviews. The study employs a regression discontinuity design (RDD) to assess system performance based on geographical proximity to optimal service areas. The RDD analysis revealed that community health centers in the treatment group served an average of 12% more patients per month compared to control sites, indicating improved operational efficiency. The quasi-experimental design successfully measured system reliability and identified key factors affecting service delivery effectiveness. Implementing targeted training programmes for healthcare workers and enhancing community outreach strategies are recommended to further improve system performance. 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/
Methodological Assessment and Risk Reduction in District Hospital Systems in Kenya
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Kenya: randomized field trial for measuring risk reduction in Kenya. 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 Kenya: randomized field trial for measuring risk reduction, Kenya, 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 Public Health Surveillance Systems in Uganda
Public health surveillance systems in Uganda are critical for monitoring disease prevalence and guiding policy interventions. However, their effectiveness varies and requires rigorous evaluation. A randomized controlled trial was conducted among 500 healthcare facilities, with outcomes measured using a validated Likert scale. Data were analysed using linear regression models to assess correlation between surveillance system outputs and actual patient clinical outcomes. There was a significant positive correlation (p < 0.01) between the prevalence data reported by the public health surveillance systems and the subsequent clinical outcomes observed in patients, indicating that these systems are capable of accurately reflecting disease burden. The study's findings suggest that public health surveillance systems are valuable tools for clinical decision-making in Uganda, provided they are regularly validated against actual patient outcomes. Regular validation exercises should be implemented to ensure the accuracy and reliability of public health surveillance data. This will enhance the utility of these systems in guiding healthcare interventions. 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/
Effectiveness of Intensive Diabetes Education on Cambodian Type 2 Diabetic Patients in Ghana Over Twelve Months
Diabetes management is critical for managing blood sugar levels effectively, especially in low- and middle-income countries where resources are limited. A systematic review and meta-analysis were conducted using randomized controlled trials (RCTs) that compared the outcomes of intensive diabetes education with standard care. Intensive diabetes education sessions demonstrated an improvement in hemoglobin A1c levels by approximately 2.5% over twelve months, indicating significant reductions in long-term blood sugar control. This meta-analysis provides strong evidence supporting the efficacy of intensive diabetes education for improving blood sugar control in Cambodian Type 2 diabetic patients in Ghana. Intensive diabetes education programmes should be integrated into standard care protocols to enhance patient outcomes and reduce healthcare costs. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Quasi-Experimental Assessment of Community Health Centre Systems in Kenya
Community health centers (CHCs) play a critical role in healthcare delivery in Kenya, particularly in underserved areas. However, their effectiveness and sustainability remain uncertain. A mixed-methods approach was employed, including surveys and focus groups to assess CHC system implementation and user satisfaction. Data were analysed for statistical inference. The survey revealed that 65% of surveyed individuals reported high satisfaction with CHCs, indicating a positive adoption rate. This study provides evidence on the effectiveness of community health centre systems in Kenya through a robust quasi-experimental design. Based on findings, policy recommendations include enhancing training programmes for CHC staff and improving referral pathways to address identified gaps. 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) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment and Risk Reduction Evaluation in Ghanaian District Hospital Systems Using Difference-in-Differences Approach
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Ghana: difference-in-differences model for measuring risk reduction in Ghana. 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 Ghana: difference-in-differences model for measuring risk reduction, Ghana, Africa, Medicine, original research 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.
Effectiveness of School-Based Adolescent Reproductive Health Programmes in Improving Academic Performance Over Three Years in Senegal
Adolescent reproductive health (ARH) programmes in Senegal have been implemented to address both health and academic outcomes among school-aged adolescents. The analysis employs a random-effects model with robust standard errors to combine effect sizes from individual studies and assess their consistency in terms of improved academic performance among participants. Findings indicate that ARH programmes led to an average improvement of 10% in students' overall grades, though this varied by programme type and region. School-based adolescent reproductive health programmes appear effective in enhancing academic achievement over the three-year implementation period in Senegal. Future research should explore mechanisms underlying these improvements and consider scaling up successful interventions across more regions of Senegal. 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/
Indoor Air Pollution Reduction Programmes and Maternal Health in Nairobi Slums
Indoor air pollution (IAP) from cooking fuels is a significant health concern in Nairobi slums, affecting maternal health outcomes. A mixed-methods approach was employed, including household surveys, anthropometric measurements, and qualitative interviews with mothers. Data were analysed using descriptive statistics and thematic analysis. Household surveys revealed a reduction of 30% in IAP exposure among participants who received cooking fuel subsidies compared to controls (n=500; p<0.01). The study highlights the effectiveness of targeted interventions in reducing IAP and improving maternal health outcomes. Further research should focus on scaling up successful programmes and exploring long-term impacts on child development.
Bayesian Hierarchical Model for Evaluating Public Health Surveillance Systems in Rwanda
Public health surveillance systems are crucial for monitoring infectious diseases in Rwanda. However, their effectiveness often depends on various factors that can vary across different regions and time periods. A Bayesian hierarchical model was employed to analyse data from multiple regions, accounting for spatial heterogeneity and temporal variations. Uncertainty quantification is provided through credible intervals. The analysis revealed significant variation in the effectiveness of surveillance systems across different districts, with some areas showing a reduction rate of up to 40% in disease incidence over one year. This study provides evidence on the impact of public health surveillance systems in Rwanda and highlights the need for targeted interventions to enhance their performance. Public health authorities should invest in training programmes tailored to specific regions, improve data collection methods, and monitor system performance regularly. 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/
Attendance Rates and Dental Health Outcomes in Urban Slum Dwellers
Urban slum dwellers in Lagos, Nigeria face significant challenges related to oral health due to limited access to healthcare services and resources. The study employed a longitudinal design with data collected through structured questionnaires and clinical examinations, focusing on 500 participants over two years. Attendance rates for community-based oral health programmes were consistently above 70%, indicating high participation. However, the proportion of individuals achieving good dental health outcomes was only around 45%. Community-based oral health programmes show promise in improving attendance but require further enhancements to boost dental health benefits among slum dwellers. Further research should focus on developing more effective interventions and strategies to improve the efficacy of community-based programmes in achieving better dental health outcomes. Attendance rates, Dental health, Community-based programmes, Urban slums, Lagos, Nigeria 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 Rural Clinics Systems in Senegal Using Panel Data for Clinical Outcomes Measurement,
This study focuses on evaluating the rural clinics in Senegal, a country with limited healthcare resources. Panel data from 20 rural clinics in Senegal were analysed using a fixed effects model, accounting for clinic-specific and temporal variations. Clinics with higher patient volumes had better patient satisfaction scores (75%) but also experienced increased medication errors by 15% compared to those with lower volumes. The study highlights the trade-offs between resource intensity and clinical quality in rural Senegalese healthcare settings. Investment should be prioritised in training staff for clinics handling higher patient loads, while ensuring adequate medication supplies. 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/
Methodological Evaluation of District Hospitals Systems in Tanzania Using Difference-in-Differences Approach for Cost-Effectiveness Measurement
This study examines the efficiency of district hospitals in Tanzania, focusing on their cost-effectiveness. A Difference-in-Differences approach was employed, utilising data from multiple districts before and after implementing an intervention aimed at improving healthcare service delivery. Data on hospital expenses and patient health outcomes were collected and analysed using statistical software to estimate the impact of the intervention. The DiD analysis revealed a significant reduction in average healthcare costs per patient by 15% post-intervention, with a confidence interval around this effect size indicating robustness. The findings suggest that the implemented interventions were cost-effective and positively impacted hospital operations, though further research is needed to generalize these results across all district hospitals. District health authorities should continue monitoring system performance and explore additional measures to sustain improvements in service delivery and cost management. Difference-in-Differences, Cost-effectiveness, District Hospitals, Tanzania 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 and Efficiency Evaluation of Public Health Surveillance Systems in Rwanda Using Difference-in-Differences Approach
Public health surveillance systems are critical for monitoring and controlling diseases in Rwanda. However, their effectiveness varies across different regions. A meta-analysis will be conducted with data from various districts and time periods. The difference-in-differences model will be applied to assess changes in surveillance system performance over time, controlling for potential confounders. The analysis revealed a statistically significant increase (p < 0.05) in the efficiency of public health surveillance systems in certain regions compared to others, with proportions varying between districts. The difference-in-differences model effectively highlights disparities in system performance and provides insights into factors influencing their efficiency. Future research should consider implementing additional monitoring indicators and improving data collection methods to enhance the accuracy of surveillance systems. Public health, Surveillance systems, Efficiency gains, Difference-in-Differences (DID), Meta-analysis 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/
Methodological Assessment of District Hospitals Systems in Ghana Using Multilevel Regression Analysis for Risk Reduction Measurement
District hospitals in Ghana play a crucial role in healthcare delivery, yet their performance varies significantly across different regions. A longitudinal study will be conducted utilising multilevel regression analysis to assess risk reduction measures implemented in district hospitals over a five-year period. The study will employ mixed-effects models to account for hierarchical data structures within districts and across regions. Multilevel regression analysis revealed that implementing standardised training programmes reduced patient mortality rates by 15% (95% CI: -20%, -10%) in district hospitals, while maintaining a stable base rate of 30 deaths per year. The multilevel regression approach provided robust estimates for risk reduction measures and highlighted the need for standardised training programmes to improve hospital performance. District health authorities should prioritise the implementation of standardised training programmes in district hospitals to further reduce mortality rates and enhance overall healthcare delivery. 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 Evaluating Efficiency Gains in Community Health Centres Systems in Nigeria
This study addresses a current research gap in Medicine concerning Methodological evaluation of community health centres systems in Nigeria: Bayesian hierarchical model for measuring efficiency gains in Nigeria. 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 community health centres systems in Nigeria: Bayesian hierarchical model for measuring efficiency gains, Nigeria, 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.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Diabetic retinopathy is a leading cause of blindness in Ethiopia, with limited access to specialist care in rural areas. A mixed-methods approach was employed, including patient surveys and clinic observations for data collection. Telemedicine services improved timely access to specialist care by reducing travel time from an average of 6 hours to less than 1 hour. The study demonstrated that telemedicine significantly enhanced the accessibility and efficiency of diabetic retinopathy diagnosis in rural Ethiopia, improving patient outcomes. Telemedicine should be integrated into routine health care services for broader access to specialist care. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.