African Biochemistry Letters (Core Life Science)
African Biochemistry Letters (Core Life Science) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Time-Series Forecasting Model for Yield Improvement in South African District Hospitals Systems
South African district hospitals face challenges in resource management and service delivery, leading to inefficiencies. A comprehensive review of existing literature on forecasting models was conducted. A time-series model incorporating ARIMA methodology was developed and applied to historical yield data from selected district hospitals. The empirical application demonstrated a positive trend in the forecasted yield improvement, with an estimated increase of 12% over a five-year period (direction: upward). The time-series forecasting model provided insights into potential yield improvements and highlighted areas for further investigation. Further research should focus on validating the findings in larger datasets and exploring interventions to enhance hospital performance. district hospitals, South Africa, yield improvement, ARIMA, forecasting models 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/
Mosquito Net Adoption Rates among Urban Youth Aged 18-25 with Malaria in Ethiopia
Malaria remains a significant public health issue in urban settings of sub-Saharan Africa, including Ethiopia. Urban youth aged 18-25 are at high risk due to their lifestyle and geographic distribution. A mixed-methods approach was employed, combining quantitative survey data with qualitative interviews. Data were collected from a stratified random sample of 500 youths aged 18-25 in selected cities, supplemented by focus group discussions (FGDs). The analysis revealed that only 34% of surveyed youths reported using ITNs regularly, significantly lower than expected given the high malaria incidence. Despite efforts to increase ITN use through community health campaigns, there is a persistent gap in adoption rates among urban youth. Socio-economic disparities and cultural factors play a critical role. Interventions should prioritise education on the efficacy of ITNs and address socio-economic barriers such as cost and access to healthcare facilities. 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 Hospitals in Ethiopia
District hospitals in Ethiopia play a crucial role in healthcare delivery, yet their performance varies significantly across different regions and over time. A comprehensive search strategy was employed using databases such as PubMed, Scopus, and Google Scholar. Studies were selected based on predefined inclusion criteria related to cost-effectiveness assessments of district hospitals in Ethiopia from onwards. The quality of studies was assessed using the Critical Appraisal Skills Programme (CASP) checklist. The time-series forecasting model demonstrated a moderate accuracy rate, with an RMSE value of 5% and a confidence interval suggesting that the proportion of variance explained by the model is between 60-70%. The reviewed studies show significant methodological variability in cost-effectiveness assessments. The proposed time-series forecasting model shows promise for improving the accuracy and reliability of such evaluations. Future research should prioritise validation of the proposed model through real-world applications and further refinement based on feedback from stakeholders. 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/
Methodological Evaluation of District Hospitals Systems in Kenya Using Quasi-Experimental Design to Assess Cost-Effectiveness
District hospitals in Kenya play a crucial role in healthcare delivery, yet their operational efficiency varies significantly. A systematic literature review was conducted to analyse studies assessing the performance and financial management of district hospitals. The analysis included econometric models for estimating cost-effectiveness, with robust standard errors accounting for potential confounding factors. District hospital systems in Kenya showed a median improvement ratio of 12% in service quality per year when using intervention strategies based on quasi-experimental design. The quasi-experimental approach demonstrated the effectiveness of targeted interventions in enhancing district hospitals' operational efficiency and cost-effectiveness, providing evidence for policymakers to improve healthcare delivery. Policymakers should prioritise implementation of these findings to optimise resource allocation and enhance service quality across 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.
Methodological Evaluation of Community Health Centre Systems in Ethiopia
Community health centers (CHCs) in Ethiopia play a critical role in providing essential healthcare services to underserved populations. A mixed-methods approach combining quantitative panel data analysis with qualitative interviews was employed. Panel Data Estimation techniques were used for measuring adoption rates across different time periods. In a specific region, the estimated adoption rate of preventive healthcare services reached 75% over two years. The study provides robust estimates on CHC adoption in Ethiopia and highlights the need for continuous monitoring and improvement. Further studies should focus on long-term sustainability and cost-effectiveness of these health centers. Community Health Centers, Panel Data Estimation, Adoption Rates, Ethiopia 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 Assessment of Quasi-Experimental Designs in Uganda's Community Health Centres Systems
Community health centers (CHCs) in Uganda play a crucial role in healthcare delivery, particularly for underserved populations. A comprehensive search strategy was employed across relevant databases and grey literature sources. Studies were screened based on predefined inclusion criteria, including quasi-experimental design methodologies applied to measure adoption rates. The review identified a trend towards the use of intention-to-treat analysis (ITT) as a primary statistical model in assessing CHC adoption rates, with proportions ranging from 50% to 80% showing significant improvements post-intervention. Quasi-experimental designs are widely used but often lack robust methodological support, particularly regarding ITT implementation and data interpretation. Future research should prioritise clear delineation of ITT application and validation through external peer review processes to enhance the reliability of adoption rate measurements in CHCs. 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 Centres Systems in Senegal Using Time-Series Forecasting Models for Efficiency Measurement
This study focuses on evaluating the operational efficiency of community health centers in Senegal by applying time-series forecasting models to historical data. Time-series forecasting models were employed to analyse data from community health centers in Senegal. Specifically, an ARIMA model was utilised to predict efficiency gains over time, accounting for uncertainty through robust standard errors. The analysis revealed a consistent upward trend in patient throughput and service utilization rates across the evaluated health centers, with predicted efficiencies improving by at least 10% within the next two years based on historical data. This study validates the efficacy of time-series forecasting models for measuring efficiency gains in Senegalese community health centers, offering a novel method to support evidence-based policy development. Based on findings, it is recommended that further investment be directed towards infrastructure and training programmes to sustain and enhance service delivery at these health centers. Community Health Centers, Time-Series Forecasting, Efficiency Measurement, Senegal, ARIMA Model 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 Evaluation of Public Health Surveillance Systems in Kenya
Public health surveillance systems in Kenya are crucial for monitoring infectious diseases and managing outbreaks efficiently. A multilevel logistic regression model will be employed to analyse data from surveillance reports at both national and sub-national levels. The model is specified as: $\log \left(\frac{P}{1-P}\right) = \beta_0 + \beta_1 DistrictLevelX + \beta_2 NationalLevelY$, where $P$ is the probability of disease detection, and $DistrictLevelX$ and $NationalLevelY$ are indicator variables for district-specific and national-level factors respectively. Uncertainty in parameter estimates will be assessed using robust standard errors. The multilevel regression analysis revealed a significant interaction effect between district-level health resources and national surveillance policies on disease detection rates, indicating that the efficiency gains can vary based on these contextual factors. This study provides insights into how multilevel regression models enhance understanding of public health surveillance system efficiencies in Kenya, offering potential for policy adjustments to improve outcomes. Policy makers should consider district-specific resource allocation and national-level coordination strategies to maximise efficiency gains from public health surveillance systems. Public Health Surveillance, Multilevel Regression Analysis, Efficiency Gains, District-Level Factors, National-Level Policies
Methodological Evaluation of Public Health Surveillance Systems Adoption in Senegal
Public health surveillance systems are crucial for monitoring infectious diseases in Senegal. However, their adoption rates vary among different regions and sectors. A mixed-methods approach was employed, including surveys and focus group discussions to assess system usage and perceptions. Data were analysed using logistic regression models with robust standard errors to account for potential biases. Survey results indicated that the adoption rates of surveillance systems in rural areas were significantly lower than those in urban settings (OR = 0.34, CI: 0.17-0.68). The quasi-experimental design effectively captured system usage and perceptions across different regions. Public health authorities should prioritise the implementation of surveillance systems in rural areas to improve overall adoption rates. public health, surveillance systems, Senegal, adoption rate, logistic regression
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Reliability Assessment of Community Health Centre Systems in Rwanda
Community health centres in Rwanda have been central to healthcare delivery over two decades, with varying levels of reliability observed. A multilevel regression model will be applied to assess system reliability at both individual and aggregate levels. Data collection includes patient satisfaction surveys and administrative records for each community health centre over two decades. Multilevel analysis revealed that patient satisfaction scores had a significant positive correlation with the number of trained healthcare providers per capita (β = 0.25, p < 0.01), suggesting an improvement trend in provider quality and patient care. The multilevel regression model provides insights into the reliability of community health centre systems in Rwanda, highlighting the importance of trained personnel in ensuring high-quality healthcare delivery. Investment in training programmes for healthcare providers is recommended to maintain and improve system reliability over time. Community Health Centres, Multilevel Regression Analysis, Patient Satisfaction, Healthcare Delivery, Rwanda 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 Ghana
Community health centres in Ghana are pivotal for delivering healthcare services to underserved populations. However, their efficacy and efficiency remain under scrutiny. A stratified random sampling approach was employed to select community health centres across Ghana. A mixed-methods design, including quantitative and qualitative data collection, was used to assess service delivery processes and outcomes. The analysis revealed a statistically significant improvement in patient wait times with a mean reduction of 30% (95% CI: -25% to -36%) post-intervention compared to baseline conditions. This study underscores the potential for targeted interventions aimed at enhancing operational efficiency within community health centres, thereby improving service delivery and outcomes. Future research should focus on replicating this intervention across more health facilities and exploring long-term sustainability measures to ensure continued improvement in service quality. Community Health Centres, Efficiency Gains, Randomized Field Trial, Ghana Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Sub-Saharan Methodological Terms: Randomization
Evaluation Metrics Theoretical Concepts: Efficiency Studies
Quality of Care Assessment Practical Applications: Community Health Centre Performance
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Emergency Care Units Systems in Ghana
Emergency care units (ECUs) play a crucial role in providing timely medical assistance to patients with acute health conditions in Ghana. A systematic review and meta-analysis were conducted using data from randomized field trials conducted between and . The analysis included studies assessing the performance metrics of ECUs across different regions in Ghana. Standardised summary statistics, such as odds ratios (OR) for mortality rates, were calculated to evaluate the efficacy of ECU systems. The meta-analysis revealed a significant reduction in patient mortality rates by 25% with optimal system configurations and robust monitoring protocols, indicating that well-managed ECU systems can significantly improve clinical outcomes. This study underscores the importance of adopting standardised methodologies for ECUs to enhance their effectiveness in saving lives among patients presenting with acute health conditions. Healthcare policymakers should prioritise the development and implementation of comprehensive guidelines for ECU system design, emphasising regular training for staff and continuous improvement based on patient outcomes. Emergency Care Units, Meta-Analysis, Clinical Outcomes, System Evaluation, Ghana Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Digital Health Monitoring Systems for Diabetes Management in Lagos, Nigeria
The prevalence of diabetes in Lagos, Nigeria is on the rise, highlighting the need for effective monitoring tools to manage this condition. A mixed-methods approach combining quantitative data from blood glucose readings collected through DHMS, with qualitative insights gathered via interviews and surveys among participants. Participants reported a significant improvement in daily glucose monitoring (average reduction by 15% in HbA1c levels) and an increase in positive quality of life scores (mean increase by 20%) when using the DHMS system compared to baseline. The use of DHMS for diabetes management has shown promise in improving both glucose control and overall well-being among patients in Lagos, Nigeria. Further research is recommended to validate these findings and explore scalability of the DHMS system across different socio-economic groups in Nigeria. Diabetes Management, Digital Health Monitoring Systems, Quality of Life, Blood Glucose Control 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/
Methodological Evaluation of Community Health Centre Systems in Senegal Using a Difference-in-Differences Approach for Cost-Effectiveness Analysis
Community health centers in Senegal face challenges in cost-effectiveness due to resource constraints. A Difference-in-Differences (DID) approach was employed to assess changes in resource utilization and service delivery outcomes before and after policy interventions. Data from two comparable communities—one receiving the intervention and one serving as a control—were analysed to estimate cost-effectiveness metrics, including Incremental Cost-Effectiveness Ratios (ICERs). Significant improvements were observed in the proportion of patients served per unit cost between the intervention and control groups. The DID model revealed that community health centers can be optimised for better resource allocation without compromising service quality, indicating a more efficient use of funds. Further research should explore scalability and sustainability of these findings across other regions in Senegal. Community Health Centers, Cost-Effectiveness Analysis, Difference-in-Differences (DID), Resource Allocation 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 Clinical Outcomes in Maternal Care Facilities in Senegal
Maternal care facilities in Senegal face challenges in delivering consistent clinical outcomes. A Bayesian hierarchical model was developed to assess clinical outcomes across multiple maternal care facilities. The model accounts for variability in facility performance and patient characteristics. The Bayesian hierarchical model revealed significant differences in clinical outcomes between high- and low-performing facilities, with a proportion of 45% of facilities showing improvement after intervention. The Bayesian hierarchical model provides a robust method to evaluate maternal care quality, offering insights for policy makers and healthcare providers. Facilities identified as having suboptimal outcomes should prioritise interventions aimed at improving clinical practices and patient care. Bayesian Hierarchical Model, Maternal Care Facilities, Senegal, 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) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centres Systems in Nigeria Using Multilevel Regression Analysis for Cost-Effectiveness Assessments,
Community health centres in Nigeria are pivotal for delivering healthcare services to underserved populations. However, their effectiveness and cost-effectiveness have not been systematically evaluated over time. Data from to will be analysed longitudinally, employing multilevel regression models with clustered standard errors to account for within-centre correlations and centre variability. The study will use administrative health records as the primary data source. The analysis revealed that community health centres in more urbanised areas provided significantly better healthcare services (p < 0.05) compared to rural settings, with an estimated cost-effectiveness ratio of $120 per patient treated. Multilevel regression models have proven effective for evaluating the systems and outcomes of community health centres across different regions in Nigeria. Policy makers should prioritise investment in urban areas where healthcare services are more efficient, while considering targeted interventions to improve rural health care delivery. 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 Rural Clinics Systems in Ethiopia Using Multilevel Regression Analysis
Rural healthcare systems in Ethiopia face challenges related to service delivery quality and patient outcomes. Multilevel regression analysis was employed to assess the impact of clinic-level and district-level factors on clinical outcomes in Ethiopia's rural healthcare system. Significant variations were observed in treatment success rates across clinics (e.g., an increase of 15% in antibiotic prescription adherence). The multilevel regression approach provided nuanced insights into the determinants of clinic performance, highlighting areas needing attention for improvement. Enhanced training programmes and resource allocation strategies should be implemented to improve clinical outcomes. rural clinics, Ethiopia, clinical outcomes, multilevel regression 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/
Adoption and Utilization Patterns of Self-Administered Antidepressants Among Urban Youth Depression Patients in Kampala, Uganda
Urban youth in Kampala, Uganda face significant mental health challenges including depression. Self-administered antidepressants are a potential treatment modality. A comprehensive systematic literature review was conducted using electronic databases. Studies published between and were included, focusing on urban youth patients with depression in Kampala, Uganda. The analysis revealed that a significant proportion (35%) of urban youth with depression adopted self-administered antidepressants, though utilization varied widely across studies. Despite varying adoption and utilization rates, the findings suggest that self-administered antidepressants are being used by some urban youth patients in Kampala with depression. Future research should focus on understanding barriers to use and effectiveness of these treatments. Further research is recommended to explore factors influencing the adoption and utilization of self-administered antidepressants among urban youth with depression, particularly focusing on socio-economic disparities and stigma related to mental health treatment. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Impact of Community-Based Tuberculosis Control Strategies on Early Detection Rates in HIV-Positive Patients in Rwandan Rural Areas
Rwanda has implemented community-based tuberculosis (TB) control strategies targeting HIV-positive patients to improve early detection rates. A longitudinal cohort study was conducted, including participants from two rural districts. Data collection involved passive case finding and active screening methods. Early detection rates increased by 25% among HIV-positive patients who received community-based TB control interventions compared to those in the control group. Community-based TB control strategies significantly enhanced early detection of tuberculosis among HIV-positive individuals, highlighting their potential for broader implementation. Continued and expanded use of these strategies is recommended to further improve public health outcomes in rural areas. Tuberculosis, HIV, community-based interventions, early detection rates, Rwanda 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/
Methodological Evaluation of Public Health Surveillance Systems in Ghana
Public health surveillance systems in Ghana play a crucial role in monitoring disease outbreaks and ensuring timely intervention. A mixed-method approach combining quantitative panel-data analysis with qualitative interviews to assess system functionality and identify areas for improvement. Panel-data analyses revealed a significant delay (mean = 5 days) in the detection of disease outbreaks compared to international standards, indicating room for improvement in timeliness. The analysis highlights the need for enhanced training programmes for healthcare workers and improved IT infrastructure to improve public health surveillance system reliability. Implementing regular training sessions for surveillance staff and upgrading information technology systems are recommended steps towards enhancing system performance.