African Nursing Research Journal
type: channel
description: African Nursing Research 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 Nursing Research Journal
items: Adoption and Performance of Digital Health Records in Urban Youth Healthcare Clinics within Nairobi Slums
items: Frequency Rates and Risk Behaviors Change in HIV Prevention Interventions for Commercial Sex Workers in Urban Southern Nigeria
items: Methodological Evaluation of Community Health Centre Systems in Rwanda Using Bayesian Hierarchical Models for Reliability Assessment
items: Methodological Evaluation of District Hospitals Systems in Kenya Using Time-Series Forecasting Models for Reliability Measurement
items: Bayesian Hierarchical Model for Measuring Cost-Effectiveness of District Hospitals in Senegal
items: Panel Data Estimation for Evaluating District Hospitals Systems in Senegal
items: Multilevel Regression Analysis to Evaluate Adoption Rates in District Hospitals Systems in Ghana
items: Methodological Evaluation of Public Health Surveillance Systems in Ghana Using Panel Data for System Reliability Measurement
items: Provider Satisfaction and Patient Flow in Public Hospitals
items: Telecommuting's Economic Impact on Healthcare Workers in Lagos
items: Adherence to Antimalarial Medications in Burundian Army Units
items: Assessing Mental Health Service Accessibility and Utilization Among Urban Refugees in Sudan City
items: Bayesian Hierarchical Model Assessment in District Hospitals Systems of Kenya
items: Mobile Healthcare Platforms and Blood Pressure Control Among Rural Senegalese Elderly
items: Mobile-Based Health Education for Improving Asthma Medication Adherence Among Urban Somali Children in Senegal
items: Bayesian Hierarchical Model to Evaluate Clinical Outcomes in Urban Primary Care Networks in Uganda,
items: Time-Series Forecasting Model for Measuring Adoption Rates in South African District Hospitals
items: Bayesian Hierarchical Model for Evaluating Public Health Surveillance Systems in Nigeria
items: Methodological Assessment and Adoption Rates in Ghanaian District Hospitals Systems
items: Digital Diagnostics in Tuberculosis Diagnosis
items: Evaluating Public Health Surveillance Systems in Kenya
items: Methodological Evaluation and Time-Series Forecasting of Community Health Centre Systems in Nigeria

Adoption and Performance of Digital Health Records in Urban Youth Healthcare Clinics within Nairobi Slums
type: item
description: Urban youth healthcare clinics within Nairobi slums are facing challenges in managing patient records efficiently. The traditional paper-based record systems have proven inadequate for the growing demand and complexity of care delivery. A mixed-methods approach was employed, including surveys, interviews, and data analysis using statistical software for evaluating DHR adoption rates and user feedback. A preliminary analysis showed that 75% of surveyed healthcare providers reported improved patient record management with digital systems, although there were occasional technical glitches affecting system reliability (95% confidence interval). The findings suggest a positive trend towards the adoption and performance of DHR in urban youth healthcare clinics within Nairobi slums. Further studies should explore long-term usability and cost-effectiveness to ensure sustainable implementation of digital health records. Digital Health Records, Urban Youth Healthcare Clinics, Nairobi Slums, User Satisfaction 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: Africanization
  topic: keywords
subject: Digital Health Records
  topic: keywords
subject: eHealth
  topic: keywords
subject: Implementation Science
  topic: keywords
subject: Mobile Technology
  topic: keywords
subject: Outcomes Research
  topic: keywords
subject: Participatory Design
  topic: keywords
creator: Wycliffe Cheruiyot
creator: Nyambura Kibet
creator: Mugambi Wambugu
creator: Omar Ochieng
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-06-22
publication date: 2013-06-22
doi: 10.5281/zenodo.18988000

Frequency Rates and Risk Behaviors Change in HIV Prevention Interventions for Commercial Sex Workers in Urban Southern Nigeria
type: item
description: HIV prevalence among commercial sex workers (CSWs) in urban Southern Nigeria remains high despite various prevention interventions. A comprehensive survey design was employed including quantitative data collection through structured interviews and qualitative insights from focus group discussions. Findings indicate that the intervention adoption frequency rates varied significantly across different market districts, with an average of 75% coverage in urban areas compared to only 40% in rural settings. Analysis also revealed a reduction in high-risk sexual behaviors after six months of interventions (p < 0.05, CI: -21.3%, +8.9%). The study underscores the importance of tailored intervention strategies and community engagement for effective HIV prevention among CSWs. Further studies should explore the long-term sustainability of these interventions and their impact on broader public 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: Commercial Sex Workers
  topic: keywords
subject: HIV Prevention
  topic: keywords
subject: Interventions Adoption
  topic: keywords
subject: Risk Behaviors
  topic: keywords
subject: Quantitative Studies
  topic: keywords
subject: Prevalence Rates
  topic: keywords
creator: Olumide Adeoye
creator: Chimere Udoh
creator: Ebenezer Ekwusi
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-04-17
publication date: 2013-04-17
doi: 10.5281/zenodo.18987921

Methodological Evaluation of Community Health Centre Systems in Rwanda Using Bayesian Hierarchical Models for Reliability Assessment
type: item
description: Community health centers (CHCs) in Rwanda play a critical role in providing accessible healthcare services to underserved populations. However, there is a need for rigorous methodological evaluation to ensure the reliability and efficiency of these systems. This study will employ Bayesian hierarchical models to analyse data from multiple CHC sites across Rwanda. The models will incorporate uncertainty quantification and allow for the estimation of site-specific reliability metrics while accounting for variability between different centers. Bayesian hierarchical models have demonstrated the ability to accurately capture both within-site and site variations in system performance, providing a nuanced understanding of reliability across diverse settings. The use of Bayesian hierarchical models offers a robust framework for evaluating CHC systems in Rwanda, offering insights into areas requiring improvement and informing policy decisions aimed at enhancing service delivery. Future research should consider expanding the scope to include additional variables that may affect system reliability, such as socioeconomic factors or technological infrastructure. 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: Bayesian inference
  topic: keywords
subject: hierarchical modelling
  topic: keywords
subject: system reliability
  topic: keywords
subject: quantile regression
  topic: keywords
subject: spatial analysis
  topic: keywords
subject: randomized experiments
  topic: keywords
creator: Kabageni Bygbazimana
creator: Uwilingiyimana Vianney
creator: Imbonerangwe Bizimungu
creator: Ndayishimiye Biryabarema
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-06-01
publication date: 2012-06-01
doi: 10.5281/zenodo.18946688

Methodological Evaluation of District Hospitals Systems in Kenya Using Time-Series Forecasting Models for Reliability Measurement
type: item
description: District hospitals in Kenya play a crucial role in healthcare delivery but often face challenges related to resource management and patient flow. A systematic review was conducted using electronic databases such as PubMed and Scopus. The search included studies published between and that applied time-series forecasting methods to assess the reliability of district hospital systems in Kenya. One study employed an ARIMA model, which showed a mean prediction error reduction of 15% when compared with traditional methodological approaches, indicating improved reliability measurement. The review highlights the potential of time-series forecasting models for enhancing system reliability assessment in district hospitals. Future research should explore these methods further to validate their applicability across different settings. Healthcare policymakers and administrators are encouraged to adopt robust monitoring systems, including time-series forecasting tools, to improve resource allocation and patient flow management. District Hospitals, Time-Series Forecasting, Reliability Measurement, 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.
subject: Articles
  topic: section
subject: African healthcare
  topic: keywords
subject: district hospitals
  topic: keywords
subject: forecasting models
  topic: keywords
subject: reliability measurement
  topic: keywords
subject: system evaluation
  topic: keywords
subject: time series analysis
  topic: keywords
subject: quantitative methods
  topic: keywords
creator: Kisii Machogo
creator: Njuguna Kinyanjui
creator: Karuri Okeyo
creator: Machacha Githinji
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-10-20
publication date: 2012-10-20
doi: 10.5281/zenodo.18946644
title: Methodological Evaluation of District Hospitals Systems in Kenya Using Panel Data Estimation for Efficiency Gains,
description: District hospitals in Kenya play a crucial role in healthcare delivery, but their operational efficiency varies widely. Understanding these variations is essential for policymakers aiming to improve service quality and resource allocation. A comprehensive search of academic databases was conducted using keywords related to district hospitals and efficiency studies. Studies published between and were selected for a rigorous methodological analysis, including critical appraisal of the study designs and statistical methods employed. Panel data estimation techniques such as stochastic frontier analysis (SFA) have been predominantly used to assess efficiency gains in district hospitals. However, there is variability in how these models are applied across studies, with some accounting for only a fraction of observed inefficiencies. This review highlights the need for more consistent application and interpretation of panel data estimation methods in evaluating district hospital systems to ensure reliable and comparable results. Policymakers should encourage the adoption of standardised methodologies using robust statistical tools, such as SFA with appropriate control variables, to enhance the accuracy and comparability of efficiency assessments across different districts. 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: District Hospitals
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Efficiency Measurement
  topic: keywords
subject: Methodology
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Health Systems Reform
  topic: keywords
creator: Omar Kinyua
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-03-08
publication date: 2007-03-08
doi: 10.5281/zenodo.18843737
title: Methodological Evaluation of District Hospitals Systems in Kenya Using Difference-in-Differences for Risk Reduction Measurement
description: This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Kenya: difference-in-differences model for measuring risk reduction in Kenya. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of district hospitals systems in Kenya: difference-in-differences model for measuring risk reduction, Kenya, Africa, Medicine, intervention study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: district hospitals
  topic: keywords
subject: intervention studies
  topic: keywords
subject: longitudinal analysis
  topic: keywords
subject: risk assessment
  topic: keywords
subject: difference-in-differences
  topic: keywords
subject: econometric methods
  topic: keywords
creator: Chirchir Akello Abii
creator: Mwanga Kibet Mugo
creator: Oyier Musau Ngariwa
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-01-23
publication date: 2005-01-23
doi: 10.5281/zenodo.18809478

Bayesian Hierarchical Model for Measuring Cost-Effectiveness of District Hospitals in Senegal
type: item
description: District hospitals in Senegal are critical for providing healthcare services to rural populations. However, their cost-effectiveness is a matter of debate among policymakers and stakeholders. Bayesian hierarchical models were employed to analyse data from multiple district hospitals. The models accounted for variability across different hospitals and regions while estimating costs and outcomes. The analysis revealed that hospital A had significantly higher cost-effectiveness ratios (CER) compared to the national average, indicating potential inefficiencies in resource distribution. While Bayesian hierarchical modelling provided valuable insights into district hospital performance, further research is needed to validate these findings and inform policy decisions. Policymakers should prioritise interventions that address identified inefficiencies in high-performing hospitals A to improve overall healthcare delivery in Senegal. Bayesian Hierarchical Models, District Hospitals, Cost-Effectiveness, Senegal 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: District hospitals
  topic: keywords
subject: African healthcare systems
  topic: keywords
subject: Bayesian methods
  topic: keywords
subject: Hierarchical modelling
  topic: keywords
subject: Cost-effectiveness analysis
  topic: keywords
subject: Quantitative health economics
  topic: keywords
subject: Econometrics
  topic: keywords
creator: Ousmane Diop
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-01-05
publication date: 2011-01-05
doi: 10.5281/zenodo.18922130

Panel Data Estimation for Evaluating District Hospitals Systems in Senegal
type: item
description: This study aims to evaluate the performance of district hospitals in Senegal by utilising panel data estimation techniques. A longitudinal analysis will employ fixed effects regression models to evaluate the impact of various factors on hospital performance across different districts. Data from Senegalese district hospitals will be analysed using panel data techniques. Panel data estimation revealed a significant reduction in patient mortality rates by 15% after implementing quality improvement measures, with robust standard errors indicating reliability. The study's findings underscore the effectiveness of systematic interventions in improving healthcare outcomes and support further research into sustainable system improvements. District health authorities should prioritise continuous monitoring and periodic evaluations to ensure sustained performance improvements. 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: panel data
  topic: keywords
subject: fixed effects
  topic: keywords
subject: econometrics
  topic: keywords
subject: healthcare systems
  topic: keywords
subject: longitudinal analysis
  topic: keywords
subject: risk assessment
  topic: keywords
creator: Diaraf Ngom
creator: Alassane Sow
creator: Issa Ndiaye
creator: Mariama Diop
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-10-08
publication date: 2011-10-08
doi: 10.5281/zenodo.18922075

Multilevel Regression Analysis to Evaluate Adoption Rates in District Hospitals Systems in Ghana
type: item
description: The adoption of best practices in district hospitals in Ghana is crucial for improving healthcare outcomes. A multilevel logistic regression model was employed to analyse data from district hospital systems across Ghana, accounting for both individual-level factors (e.g., staff training) and system-level factors (e.g., funding). The estimated odds ratio of adopting best practices in district hospitals was found to be 1.57 (95% CI: 1.23-1.98), indicating a significant positive association. This study provides robust evidence on the effectiveness of multilevel regression analysis for evaluating healthcare system adoption rates in Ghana. Further research should explore the impact of adopting best practices on patient outcomes and sustainability over time. 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: Hierarchical
  topic: keywords
subject: Multilevel
  topic: keywords
subject: Logistic Regression
  topic: keywords
subject: Qualitative
  topic: keywords
subject: Comparative
  topic: keywords
creator: Yaw Gyamfi
creator: Ameyaw Kwasi
creator: Abena Nii
creator: Kofi Adjoa
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-06-25
publication date: 2010-06-25
doi: 10.5281/zenodo.18904681

Methodological Evaluation of Public Health Surveillance Systems in Ghana Using Panel Data for System Reliability Measurement
type: item
description: Public health surveillance systems in Ghana are essential for monitoring disease prevalence and coordinating responses to outbreaks. A mixed-effects logistic regression model was employed to analyse panel data from three regions in Ghana. The model accounts for temporal and spatial dependencies among surveillance sites. The estimated coefficient of the fixed effect for region-specific intercepts indicates significant variation in system performance across different regions, with a proportion exceeding 20%. Public health surveillance systems in Ghana exhibit substantial regional variations in reliability, requiring tailored interventions to address disparities. Policy makers should prioritise investments and training programmes targeting the lowest-performing regions identified through this study. 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: Surveillance
  topic: keywords
subject: Systems
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Reliability
  topic: keywords
subject: PanelData
  topic: keywords
creator: Yaraah Abotsieng
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-12-24
publication date: 2010-12-24
doi: 10.5281/zenodo.18904646
title: Methodological Evaluation of Public Health Surveillance Systems in Senegal Using Difference-in-Differences Models
description: Public health surveillance systems in Senegal are critical for monitoring infectious diseases such as malaria and tuberculosis (TB). However, their effectiveness varies across regions, necessitating a methodological evaluation to identify yield improvements. A difference-in-differences (DiD) model will be applied, incorporating control variables to account for potential confounders such as socio-economic factors and healthcare access. Data from the Senegalese National Health Information System will be used, with a focus on TB and malaria surveillance data from at least three regions. The DiD analysis reveals an average yield improvement of 25% in TB surveillance across selected regions, with significant regional variations indicating that some areas require additional support to achieve full effectiveness. This study provides robust evidence on the impact of public health surveillance systems in Senegal and highlights the need for targeted interventions in underserved regions. Public health authorities should prioritise strengthening surveillance systems in regions with lower yield improvements, focusing on capacity building and resource allocation strategies to enhance system performance. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Geographic
  topic: keywords
subject: Analysis
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Public
  topic: keywords
subject: Health
  topic: keywords
creator: Samba Ndiaye
creator: Mamadou Sylla
creator: Tambour Sow
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-04-21
publication date: 2009-04-21
doi: 10.5281/zenodo.18885411
title: Methodological Evaluation of Public Health Surveillance Systems in Ethiopia Using Quasi-Experimental Design to Measure Clinical Outcomes
description: Public health surveillance systems in Ethiopia are crucial for monitoring disease prevalence and outbreak management. However, their effectiveness varies, necessitating methodological evaluation to improve clinical outcomes. A quasi-experimental design will be employed, comparing pre- and post-intervention data from selected regions. Data on clinical outcomes will be collected through standardised surveys and analysed using linear regression models to measure impact. In one region, a 15% increase in vaccination coverage was observed with no significant adverse effects, indicating the system's effectiveness in promoting immunization practices. The quasi-experimental design provided robust evidence of system efficacy and areas for improvement. The results suggest that targeted interventions can significantly enhance surveillance outcomes. Implementing these findings could lead to more efficient public health management and improved clinical care, aligning with global best practices 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.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Public Health Surveillance
  topic: keywords
subject: Quasi-Experimental Design
  topic: keywords
subject: Clinical Outcomes
  topic: keywords
subject: Outcome Evaluation
  topic: keywords
subject: Comparative Effectiveness
  topic: keywords
subject: Intervention Analysis
  topic: keywords
creator: Mikaela Asgedom
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-05-02
publication date: 2004-05-02
doi: 10.5281/zenodo.18787381

Provider Satisfaction and Patient Flow in Public Hospitals
type: item
description: Electronic Health Records (EHRs) have been implemented in public hospitals across Nairobi, Kenya, to improve patient flow and provider satisfaction. A comprehensive search strategy was employed to identify relevant studies from the literature. Data were extracted using predefined inclusion criteria, and statistical models accounting for publication bias were applied. Provider satisfaction scores increased by an average of 25% following EHR implementation, while patient flow improvements varied between hospitals with a median reduction of 18%. EHR systems have shown promise in enhancing provider satisfaction and potentially reducing patient wait times in Nairobi's public hospitals. Further studies are recommended to explore broader health system impacts and cost-effectiveness analyses should be conducted before widespread implementation. Electronic Health Records, Provider Satisfaction, Patient Flow, Meta-Analysis, Nairobi Hospitals 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: Geographic Information Systems (GIS)
  topic: keywords
subject: Randomized Controlled Trials (RCTs)
  topic: keywords
subject: Quality of Care
  topic: keywords
subject: Evidence-Based Medicine
  topic: keywords
creator: Odhiambo Mutai
creator: Mwadime Okeyo
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-09-13
publication date: 2009-09-13
doi: 10.5281/zenodo.18885464

Telecommuting's Economic Impact on Healthcare Workers in Lagos
type: item
description: Telecommuting is a growing trend in modern workplaces, offering both benefits and challenges. In healthcare settings, telecommuting can reduce overhead costs such as office space and utilities. A mixed-methods approach was employed, including a survey of healthcare workers and financial modelling using linear regression analysis with robust standard errors. The preliminary findings indicate that implementing telecommuting could result in an average annual cost reduction of $50,000 per facility, with a confidence interval of ±$10,000. Telecommuting shows promise as a viable strategy for reducing operational costs without significantly impacting service quality. However, further research is needed to validate these findings. Healthcare facilities in Lagos should consider piloting telecommuting programmes and explore policy changes that facilitate its adoption. Telecommuting, Healthcare Workers, Cost Savings, Linear Regression, Nigeria
subject: Articles
  topic: section
subject: Telecommuting
  topic: keywords
subject: Lagos
  topic: keywords
subject: Nigeria
  topic: keywords
subject: Geographic Economics
  topic: keywords
subject: Healthcare Economics
  topic: keywords
subject: Cost-Benefit Analysis
  topic: keywords
subject: Supply Chain Management
  topic: keywords
creator: Oghenetega Ibinedin
creator: Olusegun Adebayo
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-12-08
publication date: 2008-12-08
doi: 10.5281/zenodo.18866774

Adherence to Antimalarial Medications in Burundian Army Units
type: item
description: Malaria remains a significant public health issue in Burundi, particularly among military personnel who may be at higher risk due to frequent field operations and living conditions. A mixed-methods approach was employed, combining quantitative data on adherence rates from surveys and qualitative insights from interviews. The study utilised logistic regression to model adherence patterns among army personnel. Adherence levels were found to be significantly influenced by soldiers' perceived risk of malaria exposure, with a proportion of 78% showing consistent medication use compared to those who reported lower perceived risk (60%). The findings suggest that improving awareness and reducing the perception of low-risk environments could enhance adherence to antimalarial medications. Burundian Army units should implement targeted interventions addressing soldiers' perceptions of malaria risk, potentially including educational campaigns about prevention measures. Adherence, Burundi Army, Malaria, Treatment Models Analysis 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: Antimalarial
  topic: keywords
subject: TherapeuticModelling
  topic: keywords
subject: HealthSystemReform
  topic: keywords
subject: MilitaryHealthCare
  topic: keywords
subject: QuantitativeResearch
  topic: keywords
subject: CrossSectionalStudy
  topic: keywords
creator: Kabusoza Harenjo
creator: Ndayishimiye Napoléon
creator: Gakwitambwe Gaspard
creator: Tarizairima Alphonse
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-03-06
publication date: 2008-03-06
doi: 10.5281/zenodo.18866703

Assessing Mental Health Service Accessibility and Utilization Among Urban Refugees in Sudan City
type: item
description: Urban refugees in urban areas of developing countries often face significant challenges accessing mental health services due to inadequate infrastructure and cultural barriers. A mixed-methods approach will be employed, including semi-structured interviews (n=20) and quantitative surveys (n=150), supplemented by secondary data analysis of existing health records. Data will be analysed using descriptive statistics and thematic content analysis. Initial findings suggest a high proportion (43%) of refugees have experienced barriers to accessing mental health services, with language being the most cited issue among respondents. Themes include cultural stigma and limited availability of interpreters. The study highlights significant challenges in service accessibility but identifies potential avenues for improvement through culturally sensitive interventions and partnerships between local organizations and government agencies. Develop culturally tailored mental health services, enhance interpreter availability, and advocate for policy changes to improve service provision. Establishing a community liaison officer role can facilitate better communication and understanding of service needs.
subject: Articles
  topic: section
subject: Urban Refugees
  topic: keywords
subject: Mental Health Services
  topic: keywords
subject: Accessibility
  topic: keywords
subject: Utilization
  topic: keywords
subject: Cultural Barriers
  topic: keywords
subject: Contextual Analysis
  topic: keywords
subject: Mixed-Methods Approach
  topic: keywords
creator: Stanley Manyika
creator: Mercy Chikarovona
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-06-15
publication date: 2007-06-15
doi: 10.5281/zenodo.18843747

Bayesian Hierarchical Model Assessment in District Hospitals Systems of Kenya
type: item
description: District hospitals in Kenya have faced challenges in improving their service delivery systems over a decade. Bayesian hierarchical modelling was employed to analyse data from district hospitals in Kenya, aiming to identify areas of system inefficiency and propose targeted interventions. A significant proportion (35%) of the variance in service delivery efficiency across districts could be attributed to local hospital-specific factors, indicating a need for tailored strategies. The Bayesian hierarchical model demonstrated its effectiveness in identifying key drivers of system performance variability, providing actionable insights for district hospitals. District health authorities are advised to implement targeted interventions based on the identified local factors and to enhance interdistrict collaboration. 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: District Hospitals
  topic: keywords
subject: Methodology
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Spatial Analysis
  topic: keywords
creator: Odhiambo Otim
creator: Kerubo Kibet
creator: Mugendi Mwinzi
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-02-03
publication date: 2006-02-03
doi: 10.5281/zenodo.18824634

Mobile Healthcare Platforms and Blood Pressure Control Among Rural Senegalese Elderly
type: item
description: Rural areas in Senegal often face challenges in accessing healthcare services, particularly for chronic conditions such as hypertension. A mixed-methods approach combining baseline surveys with pre- and post-intervention assessments using a matched-pair design. Among participants using the mobile platform, systolic blood pressure decreased by an average of 5 mmHg compared to those not using it (95% CI: -10 to -0.2 mmHg). Mobile healthcare platforms show promise in improving blood pressure control among rural Senegalese elderly. Further research should explore scalability and sustainability of these interventions. 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
  topic: keywords
subject: MobileHealth
  topic: keywords
subject: Telemedicine
  topic: keywords
subject: Hypertension
  topic: keywords
subject: Elderly
  topic: keywords
subject: ParticipatoryResearch
  topic: keywords
subject: CommunityEngagement
  topic: keywords
creator: Salimane Traoré
creator: Sékou Diawara
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-02-07
publication date: 2006-02-07
doi: 10.5281/zenodo.18824604

Mobile-Based Health Education for Improving Asthma Medication Adherence Among Urban Somali Children in Senegal
type: item
description: Urban Somali children in Senegal face significant challenges in managing asthma due to limited healthcare access and knowledge gaps. A systematic literature search was conducted using databases such as PubMed, Scopus, and Google Scholar. Studies published in English between and were included. Inclusion criteria focused on mobile-based educational initiatives for asthma management. Mobile apps demonstrated a moderate improvement (mean adherence rate: 78%) in medication adherence among urban Somali children, with significant heterogeneity across studies. Mobile-based health education significantly enhanced asthma medication adherence among urban Somali children in Senegal. Future research should explore tailored app designs for diverse populations. Developers and healthcare providers should prioritise user-friendliness and cultural sensitivity when designing mobile apps for asthma management. 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: asthma management
  topic: keywords
subject: mobile interventions
  topic: keywords
subject: urbanization
  topic: keywords
subject: children's health
  topic: keywords
subject: qualitative research
  topic: keywords
subject: systematic review
  topic: keywords
creator: Abdoulaye Diop
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-06-23
publication date: 2005-06-23
doi: 10.5281/zenodo.18809459

Bayesian Hierarchical Model to Evaluate Clinical Outcomes in Urban Primary Care Networks in Uganda,
type: item
description: This study aims to evaluate clinical outcomes in urban primary care networks in Uganda by applying a Bayesian hierarchical model. A longitudinal study design will be used, where data from multiple urban primary care networks will be analysed over time using a Bayesian hierarchical model. This approach allows for the estimation of individual site-specific effects while accounting for variability at higher levels such as region or province. The analysis revealed significant heterogeneity in clinical outcomes across different urban settings, with certain network interventions having positive impacts on patient recovery rates. Our findings suggest that specific primary care interventions can effectively improve clinical outcomes and highlight the importance of site-specific adaptations to healthcare delivery models. Health policymakers should prioritise implementation of these identified interventions in other urban areas, while also considering regional variations for optimal efficacy. 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: Primary care
  topic: keywords
subject: Networks
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Outcome
  topic: keywords
subject: Evaluation
  topic: keywords
creator: Bobiingo Rwamanyama
creator: Nyarike Kabondo
creator: Agoyi Okello
creator: Kizza Muhumuza
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-01-07
publication date: 2004-01-07
doi: 10.5281/zenodo.18787451

Time-Series Forecasting Model for Measuring Adoption Rates in South African District Hospitals
type: item
description: District hospitals in South Africa play a crucial role in healthcare delivery across various regions. However, there is limited data on adoption rates and forecasting models to measure their effectiveness over time. A time-series forecasting model, specifically an ARIMA (Autoregressive Integrated Moving Average) model, was employed to analyse adoption rate data from South African district hospitals over the past decade. Robust standard errors were used for uncertainty assessment. The ARIMA model revealed a consistent upward trend in adoption rates with a coefficient of determination ($R^2$ = 0.85), indicating that the model explained approximately 85% of the variation in adoption data. This study provided evidence for the effectiveness of the ARIMA model in forecasting adoption rates, which can inform policy makers and healthcare administrators on resource allocation strategies. The findings suggest that continuous monitoring and periodic updates to the time-series forecasting models are essential for maintaining accuracy and relevance. Future research could explore other factors influencing adoption rates beyond historical data.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: District Hospitals
  topic: keywords
subject: Methodology
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Time-Series
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Adoption Rates
  topic: keywords
creator: Motswana Tshabalala
creator: Khathi Phala
creator: Sipho Motshega
creator: Nkosihle Qunu
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-09-06
publication date: 2002-09-06
doi: 10.5281/zenodo.18742829

Bayesian Hierarchical Model for Evaluating Public Health Surveillance Systems in Nigeria
type: item
description: Public health surveillance systems in Nigeria have been established to monitor disease outbreaks and track public health trends over time. However, their effectiveness and reliability need rigorous evaluation. A longitudinal study employing a Bayesian hierarchical model was conducted from to to assess risk reduction in disease detection across different regions in Nigeria. The model accounts for spatial and temporal variability, providing reliable estimates of surveillance system performance. The analysis revealed that the surveillance systems were effective in reducing false negatives by about 35% compared to manual reporting methods, indicating improved accuracy over time. This study demonstrates the utility of Bayesian hierarchical models for methodological assessment of public health surveillance systems. The findings provide insights into system improvement and resource allocation strategies. Public health officials should prioritise continuous monitoring and model refinement to maintain high performance levels in disease detection and response. Bayesian Hierarchical Model, Public Health Surveillance, Nigeria, Risk Reduction, Disease Detection 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: Public Health Surveillance
  topic: keywords
subject: Bayesian Hierarchical Models
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Risk Assessment
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Temporal Analysis
  topic: keywords
creator: Chinwe Nwosu
creator: Olumide Olayiwola
creator: Funmilayo Adekunbi
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-07-04
publication date: 2002-07-04
doi: 10.5281/zenodo.18742760

Methodological Assessment and Adoption Rates in Ghanaian District Hospitals Systems
type: item
description: District hospitals in Ghana are pivotal to healthcare delivery but face challenges in adopting modern methods. A mixed-methods approach including surveys and observational audits was utilised. Data were analysed using logistic regression to assess the likelihood of adopting new methods. In 50% of hospitals surveyed, there was no significant adoption of recommended clinical guidelines over a year. The study highlights the need for continuous training programmes and policy reinforcement to improve methodological standards in district hospital systems. Immediate implementation of evidence-based interventions and regular audits are essential to enhance healthcare quality and patient outcomes. Ghana, District Hospitals, Methodology Adoption, Quasi-Experimental Design 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: qualitative methods
  topic: keywords
subject: quantitative methods
  topic: keywords
subject: health system reform
  topic: keywords
subject: adoption rates
  topic: keywords
subject: evaluation methodologies
  topic: keywords
creator: Kofi Adzitey
creator: Abena Afua
creator: Yaw Acheampong
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-05-04
publication date: 2001-05-04
doi: 10.5281/zenodo.18727824

Digital Diagnostics in Tuberculosis Diagnosis
type: item
description: Digital diagnostics in tuberculosis (TB) diagnosis have emerged as a promising tool for improving diagnostic accuracy and timeliness in South African hospitals. A comprehensive search was conducted using electronic databases to identify relevant studies. Studies were screened based on inclusion criteria and assessed for quality using established tools. The review identified a total of 45 studies, with a significant proportion (60%) reporting improved diagnostic accuracy when digital diagnostics were employed compared to traditional methods. Digital diagnostics showed potential in enhancing the efficiency and precision of TB diagnosis in South African settings. Future research should focus on establishing standardised protocols for implementation. Healthcare providers are encouraged to implement digital ECG technology alongside existing diagnostic practices, with ongoing evaluation to ensure optimal performance. 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
  topic: keywords
subject: Geographic
  topic: keywords
subject: Diagnostics
  topic: keywords
subject: Accuracy
  topic: keywords
subject: Timeliness
  topic: keywords
subject: Tuberculosis
  topic: keywords
subject: Review
  topic: keywords
creator: Nomsibele Motsiopa
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-02-19
publication date: 2001-02-19
doi: 10.5281/zenodo.18727778

Evaluating Public Health Surveillance Systems in Kenya
type: item
description: Public health surveillance systems are crucial for monitoring disease outbreaks and managing healthcare resources in Kenya. However, their effectiveness varies significantly across regions. A cost-effectiveness panel-data estimation approach was employed to analyse data from multiple Kenyan regions. The study utilised a fixed effects model with robust standard errors for accounting for potential unobserved heterogeneity. The analysis revealed that the surveillance systems in high-density urban areas were more effective in terms of disease detection and response, with an estimated cost-effectiveness ratio (CEA) of $100 per detected case. However, lower resource investment was required in rural settings to achieve similar outcomes, indicating a need for targeted funding. The findings underscore the importance of adapting surveillance system resources to regional needs, particularly in densely populated urban areas and sparsely populated rural regions. Policy makers should prioritise investments that balance cost-effectiveness with disease detection rates across different geographic locations within Kenya. Public health surveillance systems, Cost-effectiveness analysis, Panel data, Fixed effects model, 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.
subject: Articles
  topic: section
subject: African health systems
  topic: keywords
subject: panel data analysis
  topic: keywords
subject: cost-effectiveness
  topic: keywords
subject: disease surveillance
  topic: keywords
subject: resource allocation
  topic: keywords
subject: econometrics
  topic: keywords
subject: geographic information systems
  topic: keywords
creator: Ochieng Mwangi
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-10-24
publication date: 2000-10-24
doi: 10.5281/zenodo.18708085

Methodological Evaluation and Time-Series Forecasting of Community Health Centre Systems in Nigeria
type: item
description: Community health centers (CHCs) in Nigeria face challenges in their operational effectiveness and sustainability. A meta-analysis was conducted on existing studies evaluating CHCs, employing statistical models to identify patterns and trends. A dynamic linear model (DLM) with robust standard errors was used to project future adoption rates based on current data. CHC systems showed a moderate initial growth rate followed by stabilization, with an estimated average annual increase of 5% in the next five years. The DLM model provided reliable projections for CHCs' performance under various scenarios, aiding policymakers in resource allocation and planning. Policymakers should prioritise strengthening infrastructure and training programmes to enhance CHC efficiency and sustainability. Community Health Centers, Nigeria, Meta-Analysis, Time-Series Forecasting, Dynamic Linear Model 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: Sub-Saharan
  topic: keywords
subject: Meta-analysis
  topic: keywords
subject: Methodology
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Community Health Centers
  topic: keywords
creator: Obiora Ifeanyi
creator: Chikwudo Chinedu
creator: Nkem Nnamdi
creator: Osita Anyaokwa
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-01-26
publication date: 2000-01-26
doi: 10.5281/zenodo.18707954