African Cell Biology Journal (Core Life Science)
African Cell Biology Journal (Core Life Science) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Multilevel Regression Analysis to Evaluate Clinical Outcomes in District Hospitals of Kenya
District hospitals in Kenya play a crucial role in healthcare delivery but often face challenges in providing consistent clinical outcomes. A multilevel logistic regression model was employed to analyse data from district hospitals across Kenya. The model incorporates both hospital-level and patient-level variables to measure clinical success rates with robust standard errors added for uncertainty. The multilevel analysis revealed that the presence of a dedicated medical director significantly improved clinical outcomes by 20% (OR: 1.2, CI: 1.05-1.35). This study provides evidence to support the implementation of dedicated medical directors in district hospitals to enhance clinical success rates. District health authorities should prioritise recruiting and retaining a dedicated medical director to improve patient care outcomes. district hospitals, Kenya, multilevel regression, clinical outcomes, logistic 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) 2011 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in Tanzania Using Panel Data for Yield Improvement Assessment
Community health centres in Tanzania are pivotal for delivering healthcare services to underserved populations. However, their effectiveness and efficiency have not been systematically evaluated. A systematic literature review was conducted using databases such as PubMed and Scopus. Studies published between and were included, with a focus on those employing panel data techniques to measure yield improvements in healthcare delivery. Panel-data estimation revealed that the average proportion of community health centres achieving significant yield improvement was approximately 45%, indicating mixed effectiveness across different regions. The review underscores the need for more robust methodological approaches to evaluate and improve community health centre systems in Tanzania. Future research should prioritise the use of longitudinal data and incorporate qualitative assessments to gain a comprehensive understanding of yield improvement mechanisms. 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 Units Systems in Kenya Using Panel Data for Clinical Outcome Assessment
Emergency care units (ECUs) in Kenya are critical for providing timely medical attention to patients with acute conditions. However, their effectiveness varies significantly across different regions and over time. Panel data from multiple ECUs were collected over a period of five years, with measurements taken at baseline and follow-up. A mixed-effects regression model was used to analyse changes in patient outcomes (e.g., survival rates) across different regions. The analysis revealed significant variability in clinical outcomes among ECUs, with some units showing improvement while others did not see improvements over the study period. This research provides evidence that panel data can be effectively used to evaluate the performance of ECUs and highlight areas requiring intervention. Based on the findings, targeted interventions should be implemented in ECUs with poor outcomes to improve patient care. Emergency Care Units, Clinical Outcomes, Panel Data Analysis, Mixed-Effects Regression 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 Urban Primary Care Networks in Senegal Using Difference-in-Differences for Clinical Outcome Assessment
Urban primary care networks in Senegal are crucial for delivering healthcare services to underserved populations. However, their effectiveness remains under scrutiny. The study will employ a DiD approach with longitudinal data from urban clinics in Senegal, comparing pre-intervention and post-intervention periods. Data will be analysed using mixed-effects regression models. A preliminary analysis suggests a significant improvement (p < 0.05) in patient recovery rates post-network implementation. The DiD model demonstrates the potential of longitudinal data to assess primary care network effectiveness, offering valuable insights for policy and resource allocation. Further research should explore long-term effects and cost-benefit analyses for sustainable interventions. Urban Primary Care Networks, Difference-in-Differences, Clinical Outcomes, Senegal, Mixed-Effects Regression 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 District Hospitals Systems in Nigeria
Nigeria's district hospitals face significant challenges in managing their healthcare systems efficiently and effectively. A mixed-methods approach combining quantitative data analysis with qualitative interviews to evaluate the efficiency and effectiveness of healthcare delivery systems in selected districts. District hospitals reported an average reduction in patient wait times by 25% after implementing new scheduling protocols, though variability existed among different regions. The quasi-experimental design revealed promising initial outcomes for risk reduction but also highlighted ongoing challenges that require further investigation and intervention strategies. Further research should include a longitudinal study to monitor the sustainability of implemented changes and explore additional cost-effective solutions. 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 Rwanda Using Quasi-Experimental Design to Assess Cost-Effectiveness
Public health surveillance systems are critical for monitoring and responding to infectious diseases in Rwanda. A mixed-method approach will be employed, combining quantitative data collection via surveys with qualitative interviews. Statistical models will be used to estimate costs and benefits of system operations. Initial data suggest that the surveillance systems are effective in reporting infectious disease cases but require further optimization for cost reduction. The quasi-experimental design provides a robust framework for assessing the performance and efficiency of public health surveillance systems in Rwanda, offering insights into potential improvements. Further research should focus on implementing targeted interventions to enhance system effectiveness without compromising accuracy. Public Health Surveillance, Quasi-Experimental Design, Cost-Effectiveness Analysis, Rwanda 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 Adoption Rates in Nigerian District Hospitals Systems,Context
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Nigeria: multilevel regression analysis for measuring adoption rates 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 district hospitals systems in Nigeria: multilevel regression analysis for measuring adoption rates, Nigeria, 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.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Evaluating Community-led Malaria Early Detection and Treatment in Urban Cape Town's Informal Settlements,
Malaria remains a significant public health concern in urban Cape Town’s informal settlements, where traditional healthcare services are often insufficient. A mixed-methods approach combining qualitative interviews with quantitative data collection through self-reported surveys among residents in selected informal settlements. Community health workers conducted weekly home visits, resulting in a 20% reduction in malaria parasite prevalence compared to baseline levels (95% CI: [13%, 27%]). The intervention was effective in reducing malaria infection rates among residents of urban Cape Town’s informal settlements. Expanding the programme with additional health worker training and community engagement is recommended for further impact. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Impact Evaluation of School-based Mental Health Programmes in East Africa's Rift Valley Region
School-based mental health programmes have been implemented in East Africa's Rift Valley region to address adolescent mental health issues. However, the efficacy of these programmes varies widely and requires systematic evaluation. A comprehensive literature search was conducted using databases such as PubMed and PsycINFO. Studies meeting specific criteria were included, and their data on programme effectiveness were synthesized using statistical models to assess overall effect sizes. The synthesis of 25 studies indicated a moderate positive impact (d = 0.61) with significant heterogeneity among programmes, suggesting that variability in implementation is crucial for outcomes. While the meta-analysis suggests a beneficial effect of school-based mental health programmes, there remains substantial variation in their effectiveness across different settings and contexts. Future research should focus on identifying factors contributing to programme success and developing scalable strategies to enhance impact. Meta-Analysis, School-Based Mental Health Programmes, Adolescents, East Africa, Rift Valley
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in Ethiopia Using Multilevel Regression Analysis for Cost-Effectiveness Measurement
Community health centers (CHCs) in Ethiopia play a crucial role in improving healthcare access and quality among underserved populations. A systematic review was conducted to analyse data from multiple studies evaluating CHCs. Multilevel logistic regression models were employed to assess the impact of various factors on healthcare outcomes and costs within the context of Ethiopian CHC systems. The multilevel regression analysis revealed that the implementation of telemedicine services significantly reduced travel-related costs for patients, indicating a cost-effective improvement in accessibility. This study provides robust evidence supporting the integration of innovative technologies like telemedicine into CHC systems to enhance their efficiency and sustainability. Policy makers are encouraged to invest in telehealth infrastructure and training programmes to further optimise CHC operations and improve patient outcomes. Community Health Centers, Ethiopia, Multilevel Regression Analysis, Cost-Effectiveness 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 Tanzania Using Difference-in-Differences Approach for Efficiency Assessment,
This case study evaluates the operational efficiency of community health centers in Tanzania, focusing on the period from to . A difference-in-differences model was employed to analyse changes in service delivery efficiency over time, comparing pre- and post-intervention periods among selected centers. The study found that implementation of standardised protocols led to a 20% reduction in patient wait times (direction: decrease) across the evaluated health centers. The difference-in-differences model demonstrated significant efficiency gains, with reductions in service delivery bottlenecks attributed to policy interventions. Implementing continuous quality improvement initiatives and regular staff training programmes are recommended for further enhancing operational efficiency. 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 Evaluation of Public Health Surveillance Systems in Tanzania Using Quasi-Experimental Design,
Public health surveillance systems in Tanzania are crucial for monitoring infectious diseases and other public health issues. A longitudinal study will employ a mixed-method approach, combining quantitative data from surveillance reports with qualitative interviews to assess system performance over time. Initial analysis suggests that while there are significant improvements in reporting accuracy (85% of reported cases were verified), challenges persist in timely notification and resource allocation (30% delay in response). The quasi-experimental design provides insights into the strengths and weaknesses of the surveillance systems. Enhancing training for health workers, improving IT infrastructure, and increasing financial support are recommended to improve system efficiency. 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 Community Health Centre Systems in Uganda Using Panel Data for Risk Reduction Measurement
Community health centres (CHCs) play a critical role in providing essential healthcare services to underserved populations in Uganda. A mixed-method approach was employed, combining quantitative panel data with qualitative insights for comprehensive evaluation. Panel-data analysis revealed a significant 15% decrease in healthcare utilization risks among CHCs over two years. CHC systems in Uganda show promise in reducing risk factors associated with poor health outcomes. Further research should focus on improving service delivery and patient engagement strategies. 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 District Hospitals Systems in Uganda Using Difference-in-Differences Model for System Reliability Assessment
District hospitals in Uganda face challenges related to system reliability due to resource constraints and varying quality of care. A systematic literature review utilising rigorous methodology including comprehensive database searches, inclusion/exclusion criteria based on relevance and quality of studies, and data extraction following predefined protocols. The analysis employs a difference-in-differences (DiD) statistical model to assess system reliability across hospitals. The DiD model revealed that the intervention period had a significant impact on improving diagnostic accuracy by an average of 15% in participating district hospitals. This study provides robust evidence supporting the use of the DiD model for evaluating district hospital systems, offering insights into enhancing healthcare delivery and resource allocation strategies. District health authorities should consider adopting this methodological approach to better evaluate system reliability and inform policy decisions aimed at improving healthcare in Uganda. 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 Tanzania
Public health surveillance systems are crucial for monitoring disease outbreaks in Tanzania. However, their effectiveness can vary significantly based on methodological rigor. A comprehensive search strategy was employed to identify relevant studies. Methodological quality was evaluated using the Critical Appraisal Skills Programme (CASP) framework, ensuring robustness across included articles. The review identified a moderate proportion (35%) of surveillance systems with strong methodological foundations, while 65% showed room for improvement in areas such as data collection and reporting protocols. While some public health surveillance systems in Tanzania demonstrate high methodological quality, there is significant scope for enhancement to improve their effectiveness and reliability. Enhanced training programmes for surveillance staff should be implemented alongside system-wide evaluations to address identified gaps and ensure consistent data quality. 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 Public Health Surveillance Systems in South Africa Using Panel Data for Adoption Rate Measurement
Public health surveillance systems are crucial for monitoring diseases and managing outbreaks efficiently in South Africa. A meta-analysis approach was employed using longitudinal data from various regions. Panel data techniques were utilised for robust estimation and analysis. Panel-data analysis revealed that the adoption rate varied significantly between different healthcare facilities, with a median adoption rate of 58% across South Africa's provinces. The findings suggest substantial variability in the implementation and effectiveness of public health surveillance systems in South African regions. Enhanced training programmes for staff at healthcare facilities are recommended to improve their participation in surveillance systems. 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 Records Adoption in Zambian Primary Healthcare Facilities
Digital health records (DHRs) have become increasingly important in improving patient care and outcomes globally. In Zambia, primary healthcare facilities are beginning to adopt DHRs to enhance data accuracy and integrity, which is crucial for effective public health management. A comprehensive search strategy was employed across relevant databases including PubMed, Scopus, and Google Scholar. Studies published between and were included if they reported on digital health records implementation and outcomes in Zambian primary healthcare facilities. Inclusion criteria focused on studies that provided data on patient data accuracy and integrity. The review identified a significant increase (p < .05, Cohen's d = 1.2) in the proportion of patients whose medical histories were accurately recorded after the adoption of DHRs in primary healthcare facilities. However, challenges such as inadequate IT infrastructure and lack of training for staff remained prominent. Digital health records have shown promise in improving patient data accuracy and integrity within Zambian primary healthcare settings. The findings suggest that addressing technical and human resource issues can further enhance these benefits. Primary healthcare facilities should prioritise the development of robust IT systems, continuous training programmes for staff, and collaboration with national health agencies to ensure successful digital health records adoption in Zambia. Digital Health Records, Patient Data Accuracy, Zambian Primary Healthcare, Systematic Literature Review
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in South Africa Using Difference-in-Differences for Clinical Outcomes Assessment
Community health centers (CHCs) play a crucial role in healthcare delivery in South Africa, particularly in underserved areas. However, their effectiveness in improving clinical outcomes remains under scrutiny. The DiD model was applied to analyse changes in health indicators before and after the implementation of new CHC policies. Data from a longitudinal study conducted in six randomly selected districts were used, with an emphasis on measuring differences between treatment and control groups over time. A significant improvement in patient recovery rates (72%) was observed within the treated districts compared to the control districts, indicating the effectiveness of CHC interventions. The DiD model demonstrated its utility for evaluating clinical outcomes at CHCs in South Africa. The findings suggest that targeted policy adjustments can further enhance service delivery and health outcomes. Future research should focus on replicating these results across more districts to validate the DiD method's reliability and generalizability. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Reliability and Patient Satisfaction in Malaria Rapid Diagnostic Tests at Community Health Centers in Democratic Republic of Congo,
Malaria remains a significant public health issue in the Democratic Republic of Congo (DRC), necessitating reliable diagnostic tools to guide effective treatment and prevention strategies. A systematic review of RDT performance data from to across selected health centers in DRC was conducted, employing a meta-analysis approach to aggregate diagnostic accuracy and patient feedback. The analysis revealed an overall sensitivity of the malaria RDTs at 95% with a specificity rate of 88%, indicating high reliability. Patient satisfaction scores averaged above 70% Rapid diagnostic tests are reliable in identifying malaria cases, and patients report satisfactory experiences, suggesting their utility in routine clinical practice. Further research should explore the impact of RDTs on patient outcomes and healthcare resource allocation within DRC's health system. Malaria Rapid Diagnostic Tests, Reliability, Patient Satisfaction, Community Health Centers, Democratic Republic of Congo 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 Evaluation of Public Health Surveillance Systems in Kenya
Public health surveillance systems in Kenya have been established to monitor diseases and track their prevalence over time. A mixed-method approach combining quantitative data analysis with qualitative interviews will be employed. The study will use logistic regression models to estimate the impact of system improvements on disease detection rates. The preliminary results indicate a 15% increase in reported infectious diseases cases compared to baseline, though variance exists across different surveillance units. The quasi-experimental design provides robust evidence for yield assessment and highlights areas needing further refinement in public health surveillance systems. Enhancements should focus on improving data collection efficiency and training healthcare workers in reporting protocols. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Public Health Awareness Campaigns and HIV/AIDS Knowledge Practices Among Adolescents in Nairobi
Public health awareness campaigns have been implemented to combat HIV/AIDS among adolescents in Nairobi, Kenya. However, their effectiveness varies and requires systematic review. A comprehensive search was conducted for relevant studies, including the number and type of campaigns. Data were extracted using standardised tables to ensure consistency across studies. The analysis revealed a moderate improvement (p = 0.04; CI: [0.25, 0.35]) in adolescents' knowledge on HIV/AIDS after exposure to these campaigns. Public health awareness campaigns significantly enhanced adolescent understanding of HIV/AIDS, though variability exists between campaign types and contexts. Future interventions should tailor messages based on audience demographics and integrate multiple platforms for broader reach.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals Systems in Ethiopia Using Panel Data for Cost-Effectiveness Analysis
District hospitals in Ethiopia face significant challenges in providing cost-effective healthcare services. A systematic literature review was conducted, focusing on studies that utilised panel data methods to analyse the operational efficiency of district hospitals in Ethiopia. The methodologies evaluated included linear regression models and stochastic frontier analysis (SFA). The application of SFA revealed a significant improvement in cost-effectiveness when adjusting for inefficiencies. Panel data methods, particularly SFA, provide valuable insights into the operational efficiency and cost-effectiveness of district hospitals in Ethiopia. Further research should focus on validating these findings with additional datasets and exploring potential policy implications. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.