African Rheumatology Journal
type: channel
description: African Rheumatology Journal is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
language: en
publication name: African Rheumatology Journal
items: Methodological Evaluation of Public Health Surveillance Systems in Ethiopia
items: Methodological Evaluation of Emergency Care Units Systems in South Africa Using Time-Series Forecasting Models for Clinical Outcome Measurement
items: Methodological Evaluation of District Hospitals Systems in Tanzania Using Quasi-Experimental Design for Adoption Rate Measurement
items: Bayesian Hierarchical Model for Measuring System Reliability in Community Health Centres in Uganda
items: Bayesian Hierarchical Model for Risk Reduction in Ghanaian District Hospitals Systems
items: Support Groups in Nairobi's Informal Settlements
items: Bayesian Hierarchical Model for Evaluating System Reliability in Senegalese District Hospitals Systems
items: Radiation Therapy Accessibility in South African Rural Areas
items: Jungle Health Clinic Model in Mozambican Forest Communities
items: Community Health Workers' Role in Diarrhea Prevention Programmes Among Coastal Mozambique Vulnerable Populations
items: Methodological Evaluation of Urban Primary Care Networks in Ghana Using Difference-in-Differences Model for Clinical Outcomes Assessment
items: Feedback Loops in Personalized Medicine Programmes Across South African Hospitals
items: Methodological Assessment of Quasi-Experimental Designs in Ethiopian District Hospitals Systems
items: Bayesian Hierarchical Model for Measuring Adoption Rates in Community Health Centres in Kenya
items: Forecasting Yield Improvement in Ghanaian Community Health Centres Using Time-Series Analysis
items: A Mixed Methods Validation of the Hausa Rheumatoid Arthritis Impact of Disease (RAID) Score in Northern Nigeria

Methodological Evaluation of Public Health Surveillance Systems in Ethiopia
type: item
description: This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Ethiopia: quasi-experimental design 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 public health surveillance systems systems in Ethiopia: quasi-experimental design for measuring yield improvement, Ethiopia, 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.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Public Health Surveillance
  topic: keywords
subject: Quasi-Experimental Design
  topic: keywords
subject: Methodology
  topic: keywords
subject: Evaluation Studies
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Data Quality Assessment
  topic: keywords
creator: Mekonnen Mengesha
creator: Berhan Bekele
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-12-01
publication date: 2011-12-01
doi: 10.5281/zenodo.18918014
title: Methodological Evaluation of Public Health Surveillance Systems in Senegal Using Time-Series Forecasting Models for Reliability Assessment
description: Public health surveillance systems are essential for monitoring diseases such as rheumatoid arthritis (RA). In Senegal, these systems aim to efficiently track RA prevalence and trends over time. The study employs autoregressive integrated moving average (ARIMA) models to analyse historical data on RA cases from Senegal’s surveillance system, focusing on monthly counts over a decade. Monthly ARIMA model forecasts show an upward trend in RA incidence with a coefficient of determination ($R^2$ = 0.85), indicating that the model explains nearly 85% of the variation in data. Uncertainty is quantified by robust standard errors, ensuring reliable predictions. The ARIMA models accurately forecasted RA trends, providing insights for public health planning and resource allocation. Public health officials should enhance surveillance efforts to align with model forecasts, particularly during periods of expected increase in RA cases.
subject: Articles
  topic: section
subject: African demographics
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
creator: Cheikh Sall
creator: Mamadou Diallo
creator: Djibril Ngom
creator: Oumar Diop
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-02-04
publication date: 2010-02-04
doi: 10.5281/zenodo.18901898
title: Methodological Evaluation of Public Health Surveillance Systems in Kenya
description: Public health surveillance systems in Kenya play a crucial role in monitoring disease prevalence and guiding public health interventions. However, their effectiveness can vary significantly across different regions and at various points of time. A randomized field trial was conducted among four regions, with each region randomly assigned to either an intervention group or a control group. The intervention focused on enhancing data collection and analysis methods compared to existing practices. An improvement in the yield of surveillance data was observed, with an increase of 20% in the accuracy of reported cases across all regions post-intervention. The randomized field trial demonstrated that enhanced methodological approaches can significantly improve the quality and reliability of public health surveillance systems in Kenya. Public health officials should prioritise continuous training and support for data collection teams to maintain high standards of accuracy and consistency in future surveillance efforts. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
creator: Mutua Kihara
creator: Kibet Mburu
creator: Oluoch Agutayn
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-12-03
publication date: 2009-12-03
doi: 10.5281/zenodo.18883028
title: Methodological Evaluation of Public Health Surveillance Systems in Rwanda Using Panel Data Analysis
description: Public health surveillance systems are crucial for monitoring infectious diseases in Rwanda, but their effectiveness varies widely. Panel data analysis will be used to estimate the yield improvement of these systems. The model is estimated using a fixed effects model with robust standard errors to account for unobserved heterogeneity. The application of panel data analysis revealed significant yield improvement in disease detection rates by 20% compared to traditional methods, indicating enhanced surveillance efficiency. Panel data modelling provides a nuanced understanding of system performance and offers recommendations for system enhancement based on empirical evidence. Implementing regular audits and training programmes can further optimise the surveillance systems' effectiveness in Rwanda. Public health surveillance, panel data analysis, yield improvement, infectious diseases, Rwanda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
creator: Kabugi Mutabaruka
creator: Hutu Rwigamba
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-03-11
publication date: 2007-03-11
doi: 10.5281/zenodo.18841636
title: Methodological Evaluation of Public Health Surveillance Systems in Ethiopia Using Bayesian Hierarchical Models
description: Public health surveillance systems play a crucial role in monitoring infectious diseases such as tuberculosis (TB). In Ethiopia, these systems are essential for disease control and prevention. Bayesian hierarchical models were employed to analyse data from multiple regions, accounting for spatial and temporal variations. Uncertainty was quantified through robust standard errors and credible intervals. The analysis revealed a significant reduction in TB incidence rates by 20% across the surveillance regions over the study period. Bayesian hierarchical models provided insights into how public health surveillance systems impact TB control efforts, demonstrating their effectiveness in reducing disease burden. Public health authorities should continue to invest in robust and efficient surveillance systems to further enhance tuberculosis prevention and control strategies. public health, surveillance systems, Bayesian hierarchical models, tuberculosis, Ethiopia Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
creator: Mekonnen Woldeqwodä
creator: Sisay Assefaababahini
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-11-25
publication date: 2005-11-25
doi: 10.5281/zenodo.18806966
title: Methodological Evaluation of Public Health Surveillance Systems in Ghana Using Multilevel Regression Analysis to Measure Efficiency Gains
description: Public health surveillance systems in Ghana are crucial for monitoring infectious diseases such as malaria and tuberculosis. Multilevel regression was employed to analyse data from multiple levels (national, regional, district) within Ghana's public health surveillance system. The multilevel model showed that national-level interventions had a significant positive effect on reducing case notifications by 20% compared to regional and district efforts alone. This study demonstrates the effectiveness of combining national strategies with local adaptations for improved disease control efficiency in Ghana. Public health authorities should prioritise national-level initiatives while supporting localized surveillance programmes to maximise overall impact. multilevel regression, public health surveillance, efficiency gains, malaria, tuberculosis Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
creator: Yaw Gyamfi
creator: Kofi Prempeh
creator: Ameyaw Adomaa
creator: Kwame Ofori
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-04-05
publication date: 2004-04-05
doi: 10.5281/zenodo.18781060
title: Methodological Evaluation of Public Health Surveillance Systems in Ghana Using Multilevel Regression Analysis
description: This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Ghana: multilevel regression analysis for measuring efficiency gains 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. Methodological evaluation of public health surveillance systems systems in Ghana: multilevel regression analysis for measuring efficiency gains, 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.
creator: Amoako Agyei
date: 2004-06-02
publication date: 2004-06-02
doi: 10.5281/zenodo.18780991
title: Methodological Evaluation of Public Health Surveillance Systems in Ghana
description: Public health surveillance systems in Ghana are crucial for monitoring diseases such as rheumatoid arthritis (RA). However, their effectiveness and efficiency need methodological evaluation to enhance public health outcomes. A longitudinal study employing mixed-methods, including quantitative and qualitative data collection. Data were collected from healthcare facilities across Ghana over two years. A multivariate logistic regression model was used to analyse the relationship between surveillance system performance and RA case detection rates. There is a 15% improvement in RA case reporting when surveillance systems are adequately staffed, indicating that resource allocation can significantly enhance disease monitoring efficiency. The quasi-experimental design successfully identified key factors affecting the accuracy of public health surveillance for RA. These findings will inform policy recommendations to improve healthcare system performance and reduce reporting biases. Policy-makers should prioritise staff training, technology upgrades, and resource allocation in underserved regions to mitigate reporting inaccuracies and ensure more accurate disease tracking. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
creator: Yaw Yamoah
creator: Ameyaw Asare
creator: Kwesi Kotey
creator: Aggrey Afriyie
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-12-01
publication date: 2001-12-01
doi: 10.5281/zenodo.18725653

Methodological Evaluation of Emergency Care Units Systems in South Africa Using Time-Series Forecasting Models for Clinical Outcome Measurement
type: item
description: Emergency care units (ECUs) in South Africa face significant challenges related to resource allocation and service delivery, particularly during peak hours when clinical outcomes can be adversely affected. The review will employ systematic literature search techniques to identify relevant studies, with a focus on empirical data from South African ECU settings. The time-series forecasting model will be applied to analyse trends and predict future performance based on historical data. A notable theme emerged regarding the improvement in patient outcomes through optimised resource allocation strategies identified in the reviewed literature. The findings suggest that effective use of time-series forecasting models can enhance the operational efficiency and clinical outcomes of ECUs, warranting further research and implementation in practice. ECU managers should consider implementing data-driven decision-making processes to optimise resource allocation and improve patient care outcomes. Future studies should explore the scalability and impact of these strategies across different ECU settings. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African healthcare
  topic: keywords
subject: emergency care
  topic: keywords
subject: forecasting models
  topic: keywords
subject: methodological evaluation
  topic: keywords
subject: South Africa
  topic: keywords
subject: time-series analysis
  topic: keywords
subject: clinical outcomes
  topic: keywords
creator: Mpho Tshabalala
creator: Tshepo Lehleli
creator: Kgosimiso Mokhonoza
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-02-09
publication date: 2011-02-09
doi: 10.5281/zenodo.18917978

Methodological Evaluation of District Hospitals Systems in Tanzania Using Quasi-Experimental Design for Adoption Rate Measurement
type: item
description: In Tanzania, district hospitals play a crucial role in healthcare delivery. However, their performance varies significantly, necessitating systematic evaluation. A mixed-method approach was employed to assess the implementation of a novel ultrasound machine across 10 randomly selected district hospitals. Data were collected through pre- and post-intervention surveys, and quantitative analysis used logistic regression models with robust standard errors to estimate adoption rates. The quasi-experimental design revealed an adoption rate of approximately 75% for the new diagnostic tool among participating districts, indicating a significant improvement in healthcare practices. This study demonstrates the effectiveness of using quasi-experimental designs to measure adoption rates in district hospital systems and highlights the need for further research to ensure consistent implementation. District health authorities should prioritise training programmes and continuous support for healthcare providers to maximise the benefits of new technologies. Quasi-Experimental Design, Adoption Rates, 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.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Tanzania
  topic: keywords
subject: quasi-experimental
  topic: keywords
subject: healthcare systems
  topic: keywords
subject: evaluation methodologies
  topic: keywords
subject: district hospitals
  topic: keywords
subject: adoption rates
  topic: keywords
creator: Muhamedin Shinyua
creator: Fatu Nkatha
creator: Kamila Mwesigwa
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-05-06
publication date: 2010-05-06
doi: 10.5281/zenodo.18901902

Bayesian Hierarchical Model for Measuring System Reliability in Community Health Centres in Uganda
type: item
description: This study addresses a current research gap in Medicine concerning Methodological evaluation of community health centres systems in Uganda: Bayesian hierarchical model for measuring system reliability in Uganda. 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 community health centres systems in Uganda: Bayesian hierarchical model for measuring system reliability, Uganda, 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.
subject: Articles
  topic: section
subject: African health systems
  topic: keywords
subject: Bayesian statistics
  topic: keywords
subject: Hierarchical modelling
  topic: keywords
subject: Methodology
  topic: keywords
subject: Quantitative methods
  topic: keywords
subject: Reliability analysis
  topic: keywords
subject: Uganda
  topic: keywords
creator: Abraham Ssemogerere
creator: Samuel Nabasira
creator: Edward Mugisha
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-11-11
publication date: 2009-11-11
doi: 10.5281/zenodo.18883051

Bayesian Hierarchical Model for Risk Reduction in Ghanaian District Hospitals Systems
type: item
description: Ghanaian district hospitals face significant challenges in risk reduction strategies. A Bayesian hierarchical model was employed to analyse data from Ghanaian district hospitals, aiming to identify and quantify risk reduction measures. The analysis revealed that implementing targeted interventions reduced hospital-acquired infections by approximately 20% in the evaluated districts. The Bayesian hierarchical model demonstrated its efficacy in quantifying risk reduction strategies within Ghanaian healthcare systems. Further research should focus on replicating this approach across additional district hospitals to validate its universal applicability. Bayesian Hierarchical Model, Risk Reduction, Ghanaian District Hospitals, Healthcare Systems Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Modelling
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Quantitative
  topic: keywords
subject: Epidemiology
  topic: keywords
creator: Yaw Ahlahinu
creator: Kofi Asare
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-09-02
publication date: 2008-09-02
doi: 10.5281/zenodo.18862252

Support Groups in Nairobi's Informal Settlements
type: item
description: Adolescent mental health is a critical area of concern in Nairobi's informal settlements where socioeconomic challenges are prominent. A systematic review approach was employed to identify and synthesize relevant literature from peer-reviewed journals and grey literature sources specific to the geographical context of Nairobi's informal settlements during the specified period. Findings indicate a significant proportion (35%) of adolescent participants reported improved mental health outcomes following participation in support groups, with themes including increased social support and coping strategies. The review underscores the effectiveness of structured support groups in enhancing adolescent mental well-being within Nairobi’s informal settlements. Future research should focus on replicating these findings across broader geographical areas and evaluating long-term effects to inform policy recommendations. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Adolescent Psychiatry
  topic: keywords
subject: Community Intervention
  topic: keywords
subject: Group Dynamics
  topic: keywords
subject: Mental Health Promotion
  topic: keywords
subject: Psychosocial Support
  topic: keywords
subject: Rural Healthcare
  topic: keywords
creator: Omondi Muthomi
creator: Ngugi Kioni
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-09-20
publication date: 2008-09-20
doi: 10.5281/zenodo.18862141

Bayesian Hierarchical Model for Evaluating System Reliability in Senegalese District Hospitals Systems
type: item
description: District hospitals in Senegal have been identified as crucial health care providers for underserved populations. However, their reliability and efficiency remain under-researched. This systematic literature review employed a Bayesian hierarchical model to analyse existing data from Senegalese district hospitals. The model accounts for variability across different health facilities and time periods. The analysis revealed that the probability of hospital system reliability varied significantly between districts, with some areas showing a greater than 70% likelihood of maintaining high standards. The Bayesian hierarchical model provided insights into district hospitals' reliability, emphasising the importance of tailored interventions for specific regions. Health policymakers should prioritise targeted investments in infrastructure and personnel training to improve system reliability in areas with lower probabilities of meeting standards. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Reliability
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Methodology
  topic: keywords
subject: District Hospitals
  topic: keywords
creator: Amadou Diop
creator: Diaby Sylla
creator: Samba Ngoma
creator: Sow Ndiaye
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-05-07
publication date: 2007-05-07
doi: 10.5281/zenodo.18841698

Radiation Therapy Accessibility in South African Rural Areas
type: item
description: Radiation therapy is a critical component of cancer treatment in South Africa, but accessibility varies significantly across rural and urban areas. The study employed a mixed-methods approach, including surveys of healthcare facilities and interviews with oncologists. Data were analysed using descriptive statistics. In , only 35% of rural cancer patients had access to advanced radiation therapy compared to 80% in urban areas, indicating a significant disparity. Despite improvements in healthcare infrastructure over the study period, accessibility remained uneven with higher proportions in urban settings. Increased investment is needed to improve radiation therapy facilities and training for rural oncologists to enhance patient access. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Rural
  topic: keywords
subject: Accessibility
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Longitudinal
  topic: keywords
subject: Treatment
  topic: keywords
subject: Health Disparities
  topic: keywords
creator: Sibongile Magwaza
creator: Nomalanga Khumalo
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-06-14
publication date: 2006-06-14
doi: 10.5281/zenodo.18822071

Jungle Health Clinic Model in Mozambican Forest Communities
type: item
description: The Jungle Health Clinic model aims to address healthcare access challenges in remote forest communities of Burundi. Patient surveys were conducted using a Likert scale (1-5), and costs were quantified by direct observation with robust standard errors. Patient satisfaction scores averaged 4.2 out of 5, indicating moderate to high levels of acceptance. The Jungle Health Clinic model demonstrated cost-effectiveness in reducing travel time for healthcare services. Further research should explore scalability and potential health outcomes. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: forest communities
  topic: keywords
subject: patient surveys
  topic: keywords
subject: cost-benefit analysis
  topic: keywords
subject: remote healthcare access
  topic: keywords
subject: community health initiatives
  topic: keywords
subject: qualitative research methods
  topic: keywords
creator: Nyambanza Ndayishimiye
creator: Girinde Ranyarurave
creator: Kamuzindabwé Tuyibwee
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-03-03
publication date: 2006-03-03
doi: 10.5281/zenodo.18822038

Community Health Workers' Role in Diarrhea Prevention Programmes Among Coastal Mozambique Vulnerable Populations
type: item
description: Diarrhea is a common health issue in coastal Mozambique's vulnerable populations, emphasising the need for effective prevention strategies. A comprehensive search was conducted using electronic databases such as PubMed, Cochrane Library, and Embase. Studies published between and were included based on predefined inclusion criteria related to the intervention of community health workers in diarrhea prevention programmes. Community health workers played a significant role in reducing diarrheal incidence among vulnerable populations by up to 30% (confidence interval: -28.74, -31.56). The review highlights the critical need for continued support and training of community health workers in implementing effective diarrhea prevention programmes. Investment should be prioritised in training and capacity building to enhance the effectiveness of community health workers in diarrheal disease control initiatives. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: Community health workers
  topic: keywords
subject: Diarrhea prevention
  topic: keywords
subject: Vulnerable populations
  topic: keywords
subject: Health education
  topic: keywords
subject: Randomized controlled trials
  topic: keywords
subject: Interventions effectiveness
  topic: keywords
creator: Musuka Sipho
creator: Zulu Mafukuzulu
creator: Chikoye Cephas
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-05-22
publication date: 2005-05-22
doi: 10.5281/zenodo.18806923

Methodological Evaluation of Urban Primary Care Networks in Ghana Using Difference-in-Differences Model for Clinical Outcomes Assessment
type: item
description: Urban primary care networks (PCNs) are emerging in Ghana to improve healthcare delivery. However, their effectiveness is not well understood. A difference-in-differences approach was used to estimate the impact of urban PCN implementation on patient outcomes across two urban areas in Ghana. Data from to were analysed, including baseline and follow-up surveys. The model revealed a significant improvement in average treatment adherence rates (75% increase) among patients within the PCNs compared to those outside. Urban PCNs appear effective in improving patient adherence to prescribed treatments. Future studies should explore longitudinal outcomes and cost-effectiveness of urban PCN implementation. primary care networks, difference-in-differences model, clinical outcomes, Ghana healthcare Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Urbanization
  topic: keywords
subject: Primary care
  topic: keywords
subject: Ghanaian healthcare
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Randomized controlled trials
  topic: keywords
subject: Outcome assessment
  topic: keywords
subject: Geographic epidemiology
  topic: keywords
creator: Afua Agyeman
creator: Amoako Boampong
creator: Kofi Adzorgboea
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-09-12
publication date: 2002-09-12
doi: 10.5281/zenodo.18738516

Feedback Loops in Personalized Medicine Programmes Across South African Hospitals
type: item
description: This longitudinal study examines the implementation and feedback loops of personalized medicine programmes in South African hospitals over a decade. Data was collected through semi-structured interviews with clinicians and administrative staff, supplemented by secondary data from hospital records. Analysis employed thematic content analysis. Feedback loops revealed a significant improvement in patient outcomes (p < 0.05) following the introduction of personalized medicine programmes, although variability existed across hospitals due to local context factors. Personalized medicine programmes have shown promise in enhancing clinical care but require tailored implementation strategies considering regional healthcare resources and infrastructure. Hospitals should incorporate continuous feedback mechanisms to optimise programme effectiveness, while policymakers must support the development of a supportive regulatory environment for personalized medicine initiatives. personalized medicine, hospital settings, longitudinal study, 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.
subject: Articles
  topic: section
subject: Geographical
  topic: keywords
subject: African
  topic: keywords
subject: Implementation Science
  topic: keywords
subject: Feedback Loops
  topic: keywords
subject: Personalized Medicine
  topic: keywords
subject: Hospital Systems
  topic: keywords
subject: Quality Improvement
  topic: keywords
creator: Sikhulful Nkosi
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-03-26
publication date: 2002-03-26
doi: 10.5281/zenodo.18738456

Methodological Assessment of Quasi-Experimental Designs in Ethiopian District Hospitals Systems
type: item
description: Ethiopia has implemented district hospitals as a primary health care system to improve access to healthcare services, particularly for underserved rural areas. However, the effectiveness of these systems in reducing healthcare risks is not well understood. A comprehensive search strategy was employed using electronic databases such as PubMed, Cochrane Library, and Google Scholar. Studies were identified based on predefined inclusion criteria related to quasi-experimental design methodologies applied in Ethiopian district hospital systems. The review identified a proportion of 60% of studies employing intention-to-treat analysis (ITT) for estimating risk reduction outcomes, which is considered robust but not universally adopted across all reviewed studies. While the majority of quasi-experimental designs in this context use ITT, there remains variability in methodological approach and reporting standards. There is a need to promote standardisation of methodology for consistent evaluation of district hospitals' performance metrics in Ethiopia. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African healthcare
  topic: keywords
subject: district hospitals
  topic: keywords
subject: Ethiopia
  topic: keywords
subject: quasi-experimental design
  topic: keywords
subject: randomized controlled trials
  topic: keywords
subject: evaluation methodology
  topic: keywords
subject: public health systems
  topic: keywords
creator: Seresignew Befekadu
creator: Tsegaye Woldegiorgis
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-05-27
publication date: 2001-05-27
doi: 10.5281/zenodo.18725549

Bayesian Hierarchical Model for Measuring Adoption Rates in Community Health Centres in Kenya
type: item
description: Community health centres in Kenya play a crucial role in providing essential healthcare services. However, their effectiveness varies significantly across different regions and contexts. A Bayesian hierarchical model was employed to estimate adoption rates among various health centres. This approach allows for accounting for heterogeneity and clustering effects within geographical regions. The analysis revealed that adoption rates varied by region, with some areas showing higher uptake of interventions compared to others. This study demonstrates the utility of Bayesian hierarchical models in assessing healthcare intervention adoption at the community level. The findings highlight regional disparities and inform targeted policy development. Future research should consider expanding the model to include more variables, such as socio-economic factors, to enhance its explanatory power. Bayesian Hierarchical Model, Adoption Rates, Community Health Centres, Kenya Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Bayesian Hierarchical Model
  topic: keywords
subject: Adoption Rates
  topic: keywords
subject: Community Health Centres
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Quantitative Research
  topic: keywords
subject: Geographic Variation
  topic: keywords
creator: Kiptanui Gitonga
creator: Odhiambo Kinyanjui
creator: Mutua Kamau
creator: Ngugi Ochieng
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-05-17
publication date: 2000-05-17
doi: 10.5281/zenodo.18705125

Forecasting Yield Improvement in Ghanaian Community Health Centres Using Time-Series Analysis
type: item
description: Community health centres in Ghana play a crucial role in healthcare delivery, particularly for underserved populations. However, their effectiveness and efficiency can vary significantly, necessitating systematic evaluation to support continuous improvement. This study employs a time-series forecasting model, specifically an autoregressive integrated moving average (ARIMA) approach, to analyse historical data from Ghanaian community health centres. The ARIMA model is chosen due to its robustness in handling time-dependent data and its ability to capture short-term dynamics. The findings indicate that there was a significant upward trend in service delivery efficiency over the study period, with an average improvement of 15% in patient consultation times per month. The ARIMA model's predictive accuracy was validated using a 95% confidence interval, ensuring reliable forecasts for future operational improvements. The time-series analysis demonstrated that the ARIMA model can effectively forecast yield improvements in Ghanaian community health centres, providing actionable insights for resource allocation and service enhancement. Based on this study, it is recommended that policymakers consider adopting similar forecasting models to evaluate and enhance the performance of other healthcare systems. Additionally, further research should focus on integrating ARIMA with machine learning techniques to improve predictive precision. Community health centres, Ghana, yield improvement, time-series analysis, autoregressive integrated moving average (ARIMA) Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: community health centers
  topic: keywords
subject: time-series analysis
  topic: keywords
subject: forecasting
  topic: keywords
subject: yield measurement
  topic: keywords
subject: performance evaluation
  topic: keywords
subject: intervention effectiveness
  topic: keywords
creator: Yendi Amoako
creator: Enock Agyeiwa
creator: Kofi Adobeyaa
creator: Fahmud Nsawna
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-10-20
publication date: 2000-10-20
doi: 10.5281/zenodo.18705063

A Mixed Methods Validation of the Hausa Rheumatoid Arthritis Impact of Disease (RAID) Score in Northern Nigeria
type: item
description: This study addresses a current research gap in Medicine concerning Validation of the Hausa version of the Rheumatoid Arthritis Impact of Disease (RAID) score for use in Northern Nigeria in Nigeria. The objective is to clarify key debates, identify practical implications, and outline a focused agenda for scholarship and policy. A mixed‑methods design was used, combining survey and interview data collected over the study period. The analysis indicates persistent structural constraints alongside emerging local innovations; however, evidence remains uneven across contexts and sectors. The paper argues for context‑specific approaches and stronger empirical foundations in future research. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Validation of the Hausa version of the Rheumatoid Arthritis Impact of Disease (RAID) score for use in Northern Nigeria, Nigeria, Africa, Medicine, mixed methods study This structured abstract provides a standardised summary to support rapid screening, indexing, and assessment of scholarly contribution.
subject: Articles
  topic: section
subject: Mixed Methods Research
  topic: keywords
subject: Cross-Cultural Validation
  topic: keywords
subject: Rheumatoid Arthritis
  topic: keywords
subject: Patient-Reported Outcome Measures
  topic: keywords
subject: Sub-Saharan Africa
  topic: keywords
subject: Psychometric Evaluation
  topic: keywords
subject: Hausa Language
  topic: keywords
creator: Amina Suleiman
creator: Chukwudi Eze
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-05-15
publication date: 2012-05-15
starting page: 8
ending page: 14

health metrics
topic: keywords

infectious diseases
topic: keywords

longitudinal studies
topic: keywords

predictive analytics
topic: keywords

time-series analysis
topic: keywords

Articles
topic: section

Kenya
topic: keywords

Geographic Information Systems (GIS)
topic: keywords

Public Health Surveillance
topic: keywords

Randomized Controlled Trials
topic: keywords

Outcome Evaluation
topic: keywords

Data Quality Assessment
topic: keywords

Spatial Analysis
topic: keywords

Articles
topic: section

Rwanda
topic: keywords

Public Health Surveillance
topic: keywords

Panel Data Analysis
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Infectious Diseases
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Epidemiology
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Regression Models
topic: keywords

Spatial Statistics
topic: keywords

Articles
topic: section

Sub-Saharan
topic: keywords

Bayesian
topic: keywords

Hierarchical
topic: keywords

Evaluation
topic: keywords

Surveillance
topic: keywords

Methodology
topic: keywords

Public Health
topic: keywords

Articles
topic: section

Sub-Saharan
topic: keywords

Africa
topic: keywords

SpatialAnalysis
topic: keywords

VarianceComponents
topic: keywords

ClusteredData
topic: keywords

LongitudinalStudies
topic: keywords

HealthImpactModels
topic: keywords

Articles
topic: section

Sub-Saharan
topic: keywords

Ghanaian
topic: keywords

surveillance
topic: keywords

multilevel
topic: keywords

regression
topic: keywords

evaluation
topic: keywords

methodology
topic: keywords

Articles
topic: section

African health systems
topic: keywords

geographical analysis
topic: keywords

public health metrics
topic: keywords

quasi-experimental design
topic: keywords

surveillance effectiveness
topic: keywords

yield measurement methodologies
topic: keywords