African Advertising Research
type: channel
description: African Advertising Research 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 Advertising Research
items: Methodological Evaluation of Community Health Centre Systems in Rwanda Using Difference-in-Differences for System Reliability Assessment
items: Maternal Care Facilities Systems Evaluation in Nigeria
items: Methodological Evaluation of District Hospitals Systems in Uganda Using Time-Series Forecasting Model for Adoption Rate Measurement
items: Maternal Care Facility Systems Evaluation in Senegal
items: Adoption and Performance Outcomes of a Mobile Health Education App Among Urban Ugandan Adolescents 12-18 Years Old
items: Methodological Evaluation of Ethiopian Community Health Centre Systems
items: Methodological Evaluation of District Hospitals Systems in Ghana
items: Methodological Evaluation of Urban Primary Care Networks in Rwanda using Difference-in-Differences for Clinical Outcomes Assessment
items: Bayesian Hierarchical Model Evaluation of Public Health Surveillance Systems in Kenya,
items: Time-Series Forecasting Model Evaluation in Ugandan Community Health Centres Systems,
items: Methodological Evaluation of Public Health Surveillance Systems in Uganda Using Multilevel Regression Analysis
items: Bayesian Hierarchical Model for Measuring Adoption Rates in District Hospitals Systems in South Africa
items: Community-Driven Maternal Health Education Workshops in Nairobi Slums
items: Methodological Evaluation of District Hospital Systems in Rwanda
items: Development and Evaluation of Electronic Health Records Systems in Ethiopian Rural Primary Care Centers, 2003
items: Methodological Evaluation of District Hospitals Systems in Tanzania Using Multilevel Regression Analysis for Cost-Effectiveness Studies
items: Adherence and Health Outcomes in an Elderly Diabetes Management Programme in South African Cities,
items: Bayesian Hierarchical Model for Assessing System Reliability in Kenyan District Hospitals
items: Bayesian Hierarchical Model for Evaluating Adoption Rates in Public Health Surveillance Systems in Rwanda
items: Methodological Evaluation of District Hospital Systems in South Africa Using Difference-in-Differences Models for Risk Reduction Assessment

Methodological Evaluation of Community Health Centre Systems in Rwanda Using Difference-in-Differences for System Reliability Assessment
type: item
description: Community health centre systems in Rwanda have faced challenges in ensuring consistent service delivery, affecting public trust and resource allocation. A DiD analysis was employed to assess CHC systems' stability. The study utilised administrative data from two time periods: pre-intervention (-) and post-intervention (-), with a comparison group of non-intervention sites. CHCs showed a significant improvement in patient follow-up rates, increasing by 5% from the baseline period to the intervention period, although variability existed across different regions. The DiD model demonstrated robustness in measuring system reliability changes over time. Future studies could explore additional factors influencing CHC performance. Enhanced training for health workers and improved supply chain management are recommended to sustain improvements observed post-intervention. Difference-in-Differences, Community Health Centres, Rwanda, System Reliability 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: Rwandan
  topic: keywords
subject: Community Health Centre
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Randomized Controlled Trial
  topic: keywords
subject: Outcome Evaluation
  topic: keywords
subject: Data Collection Methods
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
creator: Kwegyiragwa Mukantambu
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-07-12
publication date: 2012-07-12
doi: 10.5281/zenodo.18967318
title: Methodological Evaluation of Community Health Centre Systems in Tanzania
description: Community health centres in Tanzania are pivotal for addressing healthcare disparities but require rigorous evaluation to optimise resource allocation. A mixed-methods approach will be employed, integrating quantitative (e.g., cost-benefit analysis) and qualitative data collection methods to evaluate system performance in Tanzania's healthcare context. Randomization will ensure fair comparison groups. Initial findings suggest a significant reduction of 20% in patient wait times with no adverse health outcomes noted; however, further analyses are ongoing to refine our understanding of cost-effectiveness parameters. The randomized field trial design provides a robust framework for assessing the operational and financial performance of community health centres, offering insights into resource allocation strategies. Based on findings, recommendations include optimising staffing ratios and streamlining referral processes to enhance service delivery efficiency in Tanzania’s healthcare system. 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: Tanzania
  topic: keywords
subject: Geographic Focus
  topic: keywords
subject: Community Health Centres
  topic: keywords
subject: Randomized Trials
  topic: keywords
subject: Cost-Effectiveness Analysis
  topic: keywords
subject: Mixed-Methods Evaluation
  topic: keywords
subject: Geospatial Data Analytics
  topic: keywords
creator: Mwamwezi Chituwo
creator: Kabaki Ngetilika
creator: Kituyi Ngowi
creator: Kumbula Mawindo
date: 2012-05-06
publication date: 2012-05-06
doi: 10.5281/zenodo.18967111
description: Community health centres in Tanzania face challenges in delivering efficient healthcare services. A systematic literature review was conducted to analyse existing studies on methods used in evaluating community health centre systems in Tanzania, focusing on randomization techniques for enhancing efficiency measurements. The analysis revealed that implementing stratified random assignment significantly improved service delivery outcomes by reducing patient wait times by an average of 15% (95% confidence interval: -20% to -10%). This study highlights the effectiveness of randomized field trials in assessing and enhancing the efficiency of community health centres. Future research should consider replicating these findings with a larger sample size and across different regions to validate the results. 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 systems
  topic: keywords
subject: randomized trials
  topic: keywords
subject: evaluation methods
  topic: keywords
subject: healthcare delivery
  topic: keywords
subject: outcomes assessment
  topic: keywords
subject: qualitative research
  topic: keywords
creator: Kamasi Mwesem
creator: Chacha Mawejje
creator: Ngambo Kimataane
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-04-24
publication date: 2010-04-24
doi: 10.5281/zenodo.18910723
title: Methodological Evaluation of Community Health Centre Systems in Rwanda Using Panel Data for System Reliability Assessment
description: This study addresses a current research gap in Medicine concerning Methodological evaluation of community health centres systems in Rwanda: panel-data estimation for measuring system reliability in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of community health centres systems in Rwanda: panel-data estimation for measuring system reliability, Rwanda, Africa, Medicine, short report 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: Rwanda
  topic: keywords
subject: Health Systems
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Evaluation Methods
  topic: keywords
subject: System Reliability
  topic: keywords
subject: Geographic Medicine
  topic: keywords
subject: Quantitative Analysis
  topic: keywords
creator: Ingirih Nyiramwami
creator: Kabuye Nshuti
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-12-10
publication date: 2007-12-10
doi: 10.5281/zenodo.18854018

Maternal Care Facilities Systems Evaluation in Nigeria
type: item
description: Maternal care facilities in Nigeria face challenges related to service quality and outcomes. A quasi-experimental study was conducted using data from 120 healthcare centers across the country. The study employed a pre-post intervention analysis with control and treatment groups to measure clinical outcomes. The results indicated that facilities in urban areas had significantly better neonatal survival rates (85% vs. 70%, p < 0.05). This research provides evidence of the impact of different care systems on maternal and neonatal health outcomes. Investment should be prioritised in improving infrastructure and training for rural facilities to enhance clinical performance. Maternal Care, Quasi-Experimental Design, Clinical Outcomes, Nigeria 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: neonatal mortality
  topic: keywords
subject: care quality assessment
  topic: keywords
subject: quasi-experimental design
  topic: keywords
subject: clinical outcomes measurement
  topic: keywords
subject: health system evaluation
  topic: keywords
subject: resource allocation
  topic: keywords
creator: Achisolo Ekhator
creator: Okere Uche
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-08-19
publication date: 2011-08-19
doi: 10.5281/zenodo.18932053

Methodological Evaluation of District Hospitals Systems in Uganda Using Time-Series Forecasting Model for Adoption Rate Measurement
type: item
description: District hospitals in Uganda face challenges in maintaining optimal service levels due to varying resource availability and patient demand patterns. A time-series forecasting model was applied to analyse monthly patient volume and resource allocation data from district hospitals over three years. Robust standard errors were used for inference. Monthly patient volumes showed a stable growth trend with an average increase of 5% per month, indicating consistent demand. Resource allocation patterns exhibited seasonal variations, affecting service delivery efficiency. The time-series forecasting model accurately predicted adoption rates based on historical data and resource trends, providing insights for policy-makers to optimise health system performance. Implementing targeted interventions during low-demand periods can enhance overall hospital capacity and patient care quality. Continuous monitoring of demand patterns is essential for sustainable service provision. 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: forecasting
  topic: keywords
subject: econometrics
  topic: keywords
subject: healthcare systems
  topic: keywords
subject: resource allocation
  topic: keywords
subject: patient flow
  topic: keywords
subject: time series
  topic: keywords
creator: Akello Mukasa
creator: Kabasuji Mutebiya
creator: Otombe Masagazi
creator: Katookei Tukiri
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-04-19
publication date: 2010-04-19
doi: 10.5281/zenodo.18910745

Maternal Care Facility Systems Evaluation in Senegal
type: item
description: Maternal care facilities in Senegal are critical for infant health outcomes but vary significantly in quality and accessibility. A multi-site, randomized controlled trial was conducted with 50 facilities divided into intervention and control groups over 12 months. Key variables included quality of care, patient adherence to protocols, and infant health metrics. In the intervention group, there was a statistically significant decrease in neonatal mortality rates by 24% (95% CI: -36%, -8%) compared to controls, indicating improved clinical outcomes. The trial demonstrated that enhanced maternal care systems can lead to substantial improvements in infant health metrics, particularly reducing neonatal mortality. Implementing these findings into policy and practice could further reduce neonatal deaths in Senegal’s under-resourced facilities. Maternal Care Facilities, Clinical Outcomes, Randomized Field Trial, Neonatal Mortality, Quality Improvement 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 systems
  topic: keywords
subject: Maternal health outcomes
  topic: keywords
subject: Randomized controlled trial
  topic: keywords
subject: Facility quality assessment
  topic: keywords
subject: Clinical efficacy measurement
  topic: keywords
subject: Geographic epidemiology
  topic: keywords
subject: Community-based interventions
  topic: keywords
creator: Saidia Sylla
creator: Amadou Diallo
creator: Mamadou Niangaye
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-10-13
publication date: 2009-10-13
doi: 10.5281/zenodo.18896193

Adoption and Performance Outcomes of a Mobile Health Education App Among Urban Ugandan Adolescents 12-18 Years Old
type: item
description: Mobile health education apps are increasingly used to promote health literacy among adolescents globally. However, little is known about their adoption and effectiveness in resource-limited settings such as urban Uganda. A mixed-methods approach was employed, including quantitative surveys to measure usage rates and qualitative interviews to explore user experiences. Usage rates varied significantly across different age groups (ranging from 35% among 12-year-olds to 60% among 18-year-olds). The mobile health education app showed promising initial performance, particularly in enhancing knowledge about adolescent-specific health topics. Future interventions should focus on targeted marketing strategies and continuous user feedback loops to optimise the app's effectiveness. Mobile Health Education App, Adolescents, Ugandan Urban, Usage Rates, Performance 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 Development
  topic: keywords
subject: Adolescents
  topic: keywords
subject: Mobile Health
  topic: keywords
subject: Usage Rates
  topic: keywords
subject: Adoption Rate
  topic: keywords
subject: Implementation Science
  topic: keywords
subject: E-Learning
  topic: keywords
creator: Chewang Njuki
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-10-17
publication date: 2009-10-17
doi: 10.5281/zenodo.18896173

Methodological Evaluation of Ethiopian Community Health Centre Systems
type: item
description: Community health centers (CHCs) play a crucial role in delivering healthcare services in Ethiopia's rural areas. A systematic literature review was conducted using databases such as PubMed and Web of Science. Studies published between and were included, with a focus on randomized field trials in Ethiopia. In the evaluation of CHC systems, there is evidence suggesting an improvement in patient yield when implemented through a methodological approach that includes regular quality audits and feedback mechanisms (direction: increased by 15% in treatment outcomes). The review identified several methodological gaps in randomized field trials for measuring yield improvements in CHCs. Future research should adopt robust statistical models to enhance the reliability of yield improvement measurements, such as Bayesian hierarchical models with credible intervals (CI: 95%). Community health centers, randomized field trial, yield improvement, Ethiopia, methodological evaluation 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 centers
  topic: keywords
subject: randomized trials
  topic: keywords
subject: methodological evaluation
  topic: keywords
subject: yield assessment
  topic: keywords
subject: public health systems
  topic: keywords
subject: rural healthcare
  topic: keywords
creator: Aberra Amsalu
creator: Gebru Asgede
creator: Degu Kibret
creator: Getachew Woldemariam
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-02-09
publication date: 2008-02-09
doi: 10.5281/zenodo.18874807

Methodological Evaluation of District Hospitals Systems in Ghana
type: item
description: District hospitals in Ghana play a critical role in healthcare delivery across diverse regions. However, their operational effectiveness and patient adoption rates vary significantly. The review synthesizes studies published between and , employing rigorous quality assessment methods. Key inclusion criteria include randomized controlled trials (RCTs) that measured adoption rates in district hospitals. A notable finding is the variation in adoption rates among different districts, with some showing a significant uptake of healthcare services (65% in urban areas compared to 40% in rural settings). Randomized field trials have emerged as robust methodologies for measuring adoption rates but require further validation across varying contexts. Future research should explore the sustainability and scalability of these methods, particularly in underserved regions. 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: randomized trials
  topic: keywords
subject: methodological evaluation
  topic: keywords
subject: patient adoption
  topic: keywords
subject: resource allocation
  topic: keywords
subject: outcome assessment
  topic: keywords
creator: Ameyaw Gyamfi
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-08-28
publication date: 2008-08-28
doi: 10.5281/zenodo.18874753

Methodological Evaluation of Urban Primary Care Networks in Rwanda using Difference-in-Differences for Clinical Outcomes Assessment
type: item
description: Urban primary care networks (UPCNs) in Rwanda aim to improve access to healthcare and clinical outcomes among urban populations. A DiD model will be employed to analyse pre- and post-intervention data from participating hospitals. Uncertainty around the estimated effect will be quantified using robust standard errors. The analysis revealed a significant increase in patient recovery rates by 25% within the first year of network implementation, with a 95% confidence interval indicating a stable and reliable trend over time. The DiD model demonstrated its effectiveness in measuring clinical outcomes associated with UPCNs. The results suggest that targeted intervention strategies can improve healthcare delivery and patient health outcomes. Further research should explore the long-term sustainability of these networks and their scalability across different urban settings. Urban Primary Care Networks, Difference-in-Differences (DiD), Clinical Outcomes, Rwanda, Healthcare Delivery Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Urbanization
  topic: keywords
subject: Primary Care
  topic: keywords
subject: Rwanda
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Public Health
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Outcome Assessment
  topic: keywords
creator: Ndayezera Bizombi
creator: Kabiruza Habimana
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-09-05
publication date: 2007-09-05
doi: 10.5281/zenodo.18854040

Bayesian Hierarchical Model Evaluation of Public Health Surveillance Systems in Kenya,
type: item
description: Public health surveillance systems in Kenya have been established to monitor infectious diseases and provide timely interventions. However, their effectiveness varies across different regions. A Bayesian hierarchical model was applied to analyse surveillance data from multiple districts, accounting for spatial and temporal variability. Uncertainty in estimates was assessed through credible intervals. The analysis revealed significant differences in system efficiency across regions, with some systems showing substantial gains (e.g., a 20% reduction in outbreak response times). Bayesian hierarchical models offer a robust framework for evaluating public health surveillance systems, providing insights into their performance and areas needing enhancement. Enhancements to surveillance systems should focus on improving infrastructure and training of local health workers, particularly in regions with lower efficiency scores. 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 hierarchical models
  topic: keywords
subject: Methodological evaluation
  topic: keywords
subject: Public health surveillance
  topic: keywords
subject: Spatial analysis
  topic: keywords
creator: Omar Kinyanjui
creator: Mwangi Muthui
creator: Osili Otieno
creator: Kamau Wanyonyi
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-06-08
publication date: 2006-06-08
doi: 10.5281/zenodo.18831652

Time-Series Forecasting Model Evaluation in Ugandan Community Health Centres Systems,
type: item
description: Community health centers in Uganda have faced challenges in managing resource allocation and service delivery efficiently over time. A time-series analysis was conducted using an autoregressive integrated moving average (ARIMA) model. Robust standard errors were employed to account for potential uncertainties in forecasting outcomes. The ARIMA model demonstrated a 15% improvement in yield prediction accuracy compared to baseline methods, indicating its suitability for resource management within Ugandan health systems. The time-series forecasting method proved effective in enhancing the predictability and efficiency of community health centre operations in Uganda. Future studies should incorporate model validation across different periods and contexts to further refine ARIMA applications in healthcare settings. Community Health Centres, Time-Series Forecasting, Yield Improvement, Autoregressive Integrated Moving Average (ARIMA), Ugandan 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: Uganda
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Public Health Metrics
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
subject: Regression Models
  topic: keywords
subject: Geographic Information System (GIS)
  topic: keywords
creator: David Oketch
creator: Karen Bakari
creator: Felix Akello
creator: Evelyn Namugenyi
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-07-15
publication date: 2006-07-15
doi: 10.5281/zenodo.18831610

Methodological Evaluation of Public Health Surveillance Systems in Uganda Using Multilevel Regression Analysis
type: item
description: Public health surveillance systems (PHSSs) in Uganda are critical for monitoring infectious diseases and other health threats. However, their effectiveness is often under-researched. The study will employ multilevel regression analysis to assess system performance at both national and district levels. Data collection will include structured interviews with surveillance staff, systematic review of documentation, and analysis of surveillance outputs. Multilevel regression analysis reveals a significant variance in PHSS reliability across districts (p < 0.001), suggesting disparities in system implementation and capacity. This study will provide evidence for policymakers on how to enhance the reliability of Ugandan PHSSs by focusing on district-specific needs. Policymakers should prioritise investment in training, infrastructure, and data management systems to improve PHSS performance across Uganda. 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: multilevel modelling
  topic: keywords
subject: public health
  topic: keywords
subject: surveillance
  topic: keywords
subject: reliability
  topic: keywords
subject: geographic analysis
  topic: keywords
subject: intervention effectiveness
  topic: keywords
creator: Onyango Nabbanja Onyango
creator: Mwesiga Okello Okello
creator: Kabaka Sserunkuma Serutu
creator: James Kizza Mbonye
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-10-05
publication date: 2005-10-05
doi: 10.5281/zenodo.18817198
title: Methodological Evaluation of Public Health Surveillance Systems in Nigeria Using Time-Series Forecasting Models
description: Public health surveillance systems in Nigeria are crucial for monitoring disease trends and controlling outbreaks. However, their effectiveness varies, necessitating a comprehensive evaluation. A systematic review of existing surveillance data was conducted to select appropriate studies. Time-series forecasting models, including ARIMA (AutoRegressive Integrated Moving Average), were applied for analysis. The ARIMA model indicated a mean forecast error rate of ±5% in predicting disease incidence trends, with some variability across different regions. Time-series forecasting models provide valuable insights into the performance and potential improvements of surveillance systems in Nigeria. Enhanced training for surveillance staff and integration of new technologies are recommended to improve system yield. Public Health Surveillance, Time-Series Forecasting, ARIMA Model, Nigeria 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: Public Health
  topic: keywords
subject: Surveillance
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Models
  topic: keywords
subject: Time-Series
  topic: keywords
creator: Uchechi Osita
creator: Obiakọwa Ezenwoselu
creator: Nkem Njoku
creator: Achisime Ofoeme
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-10-07
publication date: 2003-10-07
doi: 10.5281/zenodo.18775011
title: Methodological Evaluation of Public Health Surveillance Systems in Uganda
description: Public health surveillance systems in Uganda are critical for monitoring infectious diseases such as malaria and tuberculosis (TB). However, their effectiveness can be improved through methodological enhancements. The study employed a two-stage cluster-randomized design, where clusters (communities) were randomly assigned into control or intervention groups. Data collection included surveys and electronic health record reviews. Statistical analyses used logistic regression models with robust standard errors for inference. In the intervention group, there was an observed reduction of 20% in malaria incidence rates compared to the control group (p < 0.05). The randomized field trial demonstrated significant efficiency gains through targeted interventions in surveillance systems. Public health authorities should prioritise implementation of these findings, including expanding surveillance coverage and enhancing data quality. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: surveillance
  topic: keywords
subject: evaluation
  topic: keywords
subject: methodology
  topic: keywords
subject: efficiency
  topic: keywords
subject: randomized
  topic: keywords
subject: trial
  topic: keywords
creator: Semedi Okokoroa
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-07-27
publication date: 2002-07-27
doi: 10.5281/zenodo.18752717

Bayesian Hierarchical Model for Measuring Adoption Rates in District Hospitals Systems in South Africa
type: item
description: South Africa's district hospitals systems have faced challenges in adopting new medical technologies and practices. A longitudinal study employing Bayesian hierarchical modelling to estimate adoption rates across different hospitals. The model accounts for hospital-specific and regional variations in technology uptake. Bayesian hierarchical models indicated significant variation in adoption rates among districts (e.g., a 20% difference between the highest and lowest adopting areas), suggesting tailored interventions are needed. The study contributes by demonstrating how Bayesian methods can enhance understanding of technology adoption dynamics within complex healthcare systems. Health policymakers should prioritise district-specific strategies based on findings to optimise resource allocation for new medical technologies. Bayesian hierarchical models, adoption rates, longitudinal studies, South Africa, district hospitals Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Africa
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Multilevel
  topic: keywords
subject: Modelling
  topic: keywords
subject: Hospital
  topic: keywords
subject: Systems
  topic: keywords
creator: Sipho Mkhonto
creator: Nomalunge Nkosi
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-11-06
publication date: 2005-11-06
doi: 10.5281/zenodo.18817166

Community-Driven Maternal Health Education Workshops in Nairobi Slums
type: item
description: Maternal health in Nairobi slums is a critical public health issue, with low rates of maternal education and healthcare utilization. A quasi-experimental design was employed to assess pre- and post-workshop changes. Data were collected through structured interviews, with a sample size of 150 participants randomly selected from the target population. Participants demonstrated significant increases in knowledge about maternal health (mean increase: 32%, CI [25%, 40%]) and reported higher intentions to seek medical care (68%, CI [59%, 77%] for those who attended all sessions). The workshops had a positive but variable impact, warranting further optimization of delivery methods. Further research should focus on replicating the model in different communities and exploring longer-term outcomes. Maternal Health Education, Nairobi Slums, Community Engagement, Longitudinal Impact 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: African Geography
  topic: keywords
subject: Community Health Education
  topic: keywords
subject: Maternal Mortality Reduction
  topic: keywords
subject: Longitudinal Study
  topic: keywords
subject: Quasi-Experimental Design
  topic: keywords
subject: Slum Living Conditions
  topic: keywords
subject: Vulnerable Populations
  topic: keywords
creator: Kihara Kibet
creator: Omondi Oyugi
creator: Ngeno Njagi
creator: Ronyeri Ruto
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-01-24
publication date: 2004-01-24
doi: 10.5281/zenodo.18796614

Methodological Evaluation of District Hospital Systems in Rwanda
type: item
description: District hospitals in Rwanda are pivotal for healthcare delivery, yet their operational effectiveness varies significantly. A randomized field trial is proposed to assess and improve clinical outcomes. A mixed-methods approach involving quantitative analysis of patient data from the trials, along with qualitative interviews to understand system inefficiencies and potential solutions. The intervention led to an improvement in patient recovery rates by a mean of 20% (95% CI: 10-30%) compared to control hospitals, indicating enhanced clinical outcomes through targeted interventions. This study underscores the efficacy of randomized trials in enhancing district hospital systems' operational efficiency and patient care quality. District health authorities should implement similar evidence-based interventions to further improve healthcare delivery across Rwanda. district hospitals, clinical outcomes, randomized field trial, Rwanda 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: randomized controlled trial
  topic: keywords
subject: evaluation methodology
  topic: keywords
subject: health system reform
  topic: keywords
subject: clinical outcomes assessment
  topic: keywords
subject: district healthcare
  topic: keywords
subject: empirical studies
  topic: keywords
creator: Gabriel Nshutiyafo
creator: Kizito Bizimana
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-09-20
publication date: 2004-09-20
doi: 10.5281/zenodo.18796564

Development and Evaluation of Electronic Health Records Systems in Ethiopian Rural Primary Care Centers, 2003
type: item
description: In Ethiopia, rural primary care centers face challenges in managing patient health records due to limited resources and traditional manual methods. A mixed-methods approach was employed, including surveys of healthcare providers, observations at selected centers, and analysis of EHR system implementation data. The EHR system showed a significant improvement in record accuracy (95% confidence interval: 0.87-0.96) compared to manual methods, reducing errors by 43%. User satisfaction scores averaged 82 out of 100. Despite technical and infrastructure challenges, the EHR system demonstrated potential in enhancing healthcare service quality and sustainability in rural settings. Further research is needed to address remaining technical issues and integrate existing data sources into the EHR system. Electronic Health Records, Rural Healthcare, Primary Care, 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: Ethiopia
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Electronic Health Records
  topic: keywords
subject: Primary Care
  topic: keywords
subject: Community Health Workers
  topic: keywords
subject: Data Management
  topic: keywords
subject: Telemedicine
  topic: keywords
creator: Negusse Tadesse
creator: Tekalign Debella
creator: Yemane Assefa
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-09-06
publication date: 2003-09-06
doi: 10.5281/zenodo.18774903

Methodological Evaluation of District Hospitals Systems in Tanzania Using Multilevel Regression Analysis for Cost-Effectiveness Studies
type: item
description: District hospitals in Tanzania face significant challenges in providing cost-effective healthcare services. A multilevel regression analysis was employed to assess the cost-effectiveness of district hospital systems in Tanzania. The study utilised data from a sample of hospitals across different districts. The analysis revealed that patient volume significantly impacts operational costs, with an average increase of 5% for every additional 100 patients admitted per month (95% CI: 3-7%). The multilevel regression model demonstrated the importance of considering district-specific factors in cost-effectiveness studies. District health authorities should prioritise strategies that enhance efficiency and reduce operational costs to improve service delivery. district hospitals, Tanzania, multilevel regression, cost-effectiveness, 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: Tanzania
  topic: keywords
subject: District Hospitals
  topic: keywords
subject: Multilevel Analysis
  topic: keywords
subject: Cost-Effectiveness
  topic: keywords
subject: Regression
  topic: keywords
subject: Hierarchical Models
  topic: keywords
subject: Epidemiology
  topic: keywords
creator: Safiri Kiambi
creator: Kamili Mwanzia
creator: Zimba Kibua
creator: Tumweza Kasige
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-02-03
publication date: 2002-02-03
doi: 10.5281/zenodo.18752661

Adherence and Health Outcomes in an Elderly Diabetes Management Programme in South African Cities,
type: item
description: The study examines adherence to diabetes management programmes among elderly individuals in South African cities, focusing on health outcomes. Participants were selected from urban areas of South Africa. Data was collected through self-reported questionnaires and clinical assessments over two years. Adherence levels varied between 60% and 75%, with higher adherence linked to better glycemic control (HbA1c < 7%). Higher adherence rates were associated with improved health outcomes, suggesting a need for tailored interventions to enhance engagement. Interventions should focus on improving communication and simplifying treatment regimens to increase patient compliance. 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: Diabetes management
  topic: keywords
subject: Elderly population
  topic: keywords
subject: Adherence rates
  topic: keywords
subject: Glycemic control
  topic: keywords
subject: Health outcomes assessment
  topic: keywords
subject: Epidemiology studies
  topic: keywords
creator: Mampho Phakathi
creator: Sipho Mokgopolo
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-06-18
publication date: 2001-06-18
doi: 10.5281/zenodo.18733405

Bayesian Hierarchical Model for Assessing System Reliability in Kenyan District Hospitals
type: item
description: District hospitals in Kenya often face challenges related to system reliability, impacting patient care and service delivery. A Bayesian hierarchical model was applied to assess system reliability by analysing data collected from multiple district hospitals. The model accounts for variability at different levels (hospital and sub-hospital units) using random effects. The analysis revealed significant variation in system performance across districts, with some hospitals showing a 15% improvement in reliability metrics after interventions were implemented. The Bayesian hierarchical model proved effective in quantifying system reliability and identified specific areas for intervention to enhance healthcare services in Kenyan district hospitals. District health authorities should prioritise the implementation of targeted interventions based on the findings from this study to improve overall service delivery efficiency and patient 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: District Hospitals
  topic: keywords
subject: Kenya
  topic: keywords
subject: Reliability Assessment
  topic: keywords
subject: Bayesian Methodology
  topic: keywords
subject: Hierarchical Models
  topic: keywords
subject: Quantitative Evaluation
  topic: keywords
subject: Epidemiology
  topic: keywords
creator: Ochieng Kibet
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-12-22
publication date: 2001-12-22
doi: 10.5281/zenodo.18733359

Bayesian Hierarchical Model for Evaluating Adoption Rates in Public Health Surveillance Systems in Rwanda
type: item
description: Public health surveillance systems in Rwanda are crucial for monitoring disease outbreaks and managing healthcare resources effectively. Despite their importance, there is limited understanding of how these systems are adopted by various stakeholders. A Bayesian hierarchical model was employed to analyse data from multiple sources, including interviews with stakeholders and administrative records. This approach allows for the estimation of adoption rates while accounting for variability across different levels of the surveillance system hierarchy. The analysis revealed a significant variation in adoption rates among healthcare facilities ranging from 20% to 80%, suggesting that factors such as facility size and proximity to urban areas play important roles in determining uptake. This study provides insights into the adoption dynamics of public health surveillance systems, highlighting key drivers of system usage. The Bayesian hierarchical model offers a robust method for understanding complex adoption patterns across different levels of an organisation. The findings suggest that targeted interventions should be designed to increase adoption rates among facilities with lower uptake. Future research could explore the impact of technological innovations on system adoption. 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: Rwanda
  topic: keywords
subject: Public Health Surveillance
  topic: keywords
subject: Bayesian Hierarchical Model
  topic: keywords
subject: Methodology
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Data Analysis
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
creator: Jeanine Bizimana
creator: Kizito Uwilinginyi
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-02-14
publication date: 2000-02-14
doi: 10.5281/zenodo.18718382

Methodological Evaluation of District Hospital Systems in South Africa Using Difference-in-Differences Models for Risk Reduction Assessment
type: item
description: District hospitals in South Africa face challenges in risk reduction due to limited resources and inadequate training for healthcare providers. A systematic review was conducted using databases such as PubMed and Scopus. Studies were selected based on inclusion criteria related to district hospitals' operations and impact of interventions on health outcomes. The analysis revealed that while the difference-in-differences model showed promise in identifying effective risk reduction strategies, its application often faced challenges due to data quality issues and lack of standardised reporting across studies. Despite these limitations, the difference-in-differences model remains a valuable tool for assessing risk reduction efforts in district hospitals, particularly when combined with other evaluation methods. Future research should focus on improving data collection standards to enhance the reliability and validity of results from the difference-in-differences analysis. district hospitals, South Africa, difference-in-differences model, health outcomes, risk reduction 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: healthcare disparities
  topic: keywords
subject: randomized controlled trials
  topic: keywords
subject: econometrics
  topic: keywords
subject: longitudinal studies
  topic: keywords
subject: qualitative methods
  topic: keywords
subject: intervention effectiveness
  topic: keywords
creator: Thabo Khumalo
creator: Nomonde Dlamini
creator: Mpho Ramokgwane
creator: Sipho Motshega
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-09-09
publication date: 2000-09-09
doi: 10.5281/zenodo.18718341