African Operations Research (Business/Math crossover)
African Operations Research (Business/Math crossover) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Palliative Care Accessibility and Patient Satisfaction in Libyan City Hospitals
Palliative care is a critical component of end-of-life care for cancer patients in Libyan city hospitals, yet access to such services remains constrained by various healthcare sector challenges. A mixed-methods design combining qualitative interviews with quantitative surveys to evaluate service availability, quality of care, and patient-reported outcomes across five major Libyan city hospitals. Palliative care services were found to be available at only two out of the five surveyed hospitals, with a reported satisfaction rate among patients below 50% for pain management and emotional support interventions. While palliative care is recognised as essential in Libyan city hospitals, significant disparities exist in service availability and patient satisfaction levels, necessitating targeted improvements. Hospitals should prioritise expansion of palliative care services, with a focus on training healthcare providers to improve quality of care. Policy-makers must also address financial barriers that limit access to these critical resources. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Geographic Terms: North_Africa Methodological Terms: Qualitative_Research Theoretical_Terms: Cultural_Healthcare_Challenges Relevant_Palliative_Care_Terms: End_of_Life_Care Patient_Satisfaction_Terms: Quality_Of_Living Societal_Impact_Terms: Healthcare_Inequities
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Gender-Based Violence Community Dialogue Sessions in Urban South Africa
Gender-based violence (GBV) is a significant public health issue in urban South Africa, affecting both women and children disproportionately. Community dialogue sessions have been proposed as an intervention to reduce GBV incidents among perpetrators. A mixed-methods approach, including surveys and focus group discussions, was employed. Data were collected from a sample of 300 participants in three urban areas. Community dialogue sessions led to significant reductions (p<0.05) in reported incidents of GBV perpetration among male participants compared to baseline levels. The effectiveness of community dialogue sessions was confirmed, with a notable decrease in perpetrators' GBV-related behaviors post-intervention. Policy makers should consider implementing and funding more community dialogue sessions as part of comprehensive GBV prevention strategies. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Time-Series Forecasting Model for Evaluating Clinical Outcomes in Nigerian Community Health Centres Systems
Community health centers in Nigeria face challenges in monitoring clinical outcomes due to limited data collection and analysis methods. A mixed-method approach was employed, including quantitative data analysis using a SARIMA (Seasonal AutoRegressive Integrated Moving Average) model to forecast future trends and qualitative interviews with healthcare providers to assess model applicability. The SARIMA model demonstrated an R² value of 0.85 in forecasting monthly outpatient visits, indicating moderate predictive accuracy; however, variability in data collection methods across centers led to discrepancies in forecasts. While the time-series model showed promise for clinical outcome prediction, further validation and standardisation are required to enhance its utility in diverse settings. Standardise data collection protocols and conduct additional empirical tests before implementing the model in different Nigerian health centers. SARIMA, Time-Series Forecasting, Clinical Outcomes, Community Health Centers, Nigeria Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Uganda
Public health surveillance systems in Uganda are crucial for monitoring disease outbreaks and controlling communicable diseases. However, their effectiveness varies widely across different regions and implementation stages. A comprehensive search strategy was employed to identify relevant studies published between and . Studies were assessed based on predefined inclusion criteria related to methodology, implementation details, and outcomes. Our analysis revealed that the use of a mixed-methods approach (combining quantitative data from surveillance systems with qualitative insights from community health workers) significantly improved the accuracy and timeliness of disease outbreak notifications by 20% in selected districts compared to traditional methods alone. The findings suggest that integrating both quantitative and qualitative research methodologies can enhance the performance of public health surveillance systems, leading to more effective early detection and response strategies. Given the efficacy observed in our study, it is recommended that Uganda's Ministry of Health adopt a mixed-methods approach for future public health surveillance initiatives. Additionally, continuous training programmes should be established for surveillance personnel to ensure consistent quality and reliability across all regions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospital Systems in South Africa
The healthcare landscape in South Africa's district hospitals is characterized by varying levels of service provision and resource allocation, leading to disparities in clinical outcomes. A randomized controlled trial was conducted across ten randomly selected district hospitals. Participants were divided into two groups: intervention (enhanced service delivery) and control (standard care). Data collection included pre- and post-intervention patient outcomes measured using the Glasgow Outcome Scale (GOS). The intervention group showed a statistically significant improvement in GOS scores by an average of 10% with a confidence interval of ±2%, indicating better clinical outcomes. This randomized field trial provides robust evidence for the efficacy of enhanced service delivery in district hospitals, demonstrating improvements in patient recovery rates. District hospital managers should consider implementing similar intervention programmes to improve clinical outcomes and resource allocation. district hospitals, clinical outcomes, randomized field trial, Glasgow Outcome Scale Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Social Media Campaigns and Mental Health Awareness Among South African Teenagers
Social media platforms have become integral to communication among teenagers in South Africa, offering both opportunities and challenges for health campaigns. A longitudinal study design was employed with mixed methods including surveys and qualitative interviews, analysing trends in social media engagement related to mental health topics among teenagers aged 13-18 years in South Africa. Over the study period, there was a significant increase (p < 0.05) in positive posts about mental health on social media by 24%, reflecting heightened awareness and discussion of these issues. The findings suggest an effective role for social media campaigns in fostering greater understanding and support around mental health among teenagers. Further research should explore the long-term effects of sustained social media interventions and consider diverse cultural contexts to inform future strategies. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Digital diagnostics have shown promise in enhancing healthcare delivery, particularly in rural settings where access to specialized medical personnel is limited. A mixed-methods approach was employed, including pre- and post-intervention surveys along with qualitative interviews to assess provider satisfaction and usage patterns. Rural healthcare providers demonstrated a moderate (54%) preference for the digital kits over traditional methods, highlighting their convenience in initial diagnosis processes. The digital diagnostic kits were found to be effective in improving the speed of diagnosis without compromising accuracy. Provider feedback indicated significant ease of use and reliability. Further training sessions should be organised to maximise user proficiency with the digital tools, while ongoing support is crucial for sustained adoption. digital diagnostics, rural healthcare, provider satisfaction, convenience Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Efficacy Analysis of Community Health Worker Networks in HIV/AIDS Prevention within Nairobi Community
HIV/AIDS remains a significant public health challenge in Nairobi, Kenya, where community health worker (CHW) networks have been implemented to enhance prevention efforts. A mixed-methods approach was employed, including quantitative surveys and qualitative interviews. Data were analysed using logistic regression models with robust standard errors to account for potential confounders. CHWs reported a 30% reduction in HIV transmission risk behaviors among their clients compared to baseline levels (95% confidence interval: -25% to -34%). The CHW networks showed promise in promoting safer health practices, though further tailored interventions are needed. Enhanced training and support for CHWs, coupled with community engagement strategies, could amplify the effectiveness of these programmes. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Adoption Mechanisms of Precision Medicine Programmes by Primary Healthcare Centers in Lagos
Precision medicine programmes aim to tailor healthcare interventions based on individual patient characteristics such as genetics, lifestyle, and environment, improving treatment efficacy and reducing adverse effects. A comparative analysis will be conducted using qualitative research methods including interviews with key informants, document review, and focus group discussions. Data triangulation techniques will ensure robust conclusions. Primary healthcare centers in Lagos showed varied levels of adoption strategies, with some implementing genetic screening programmes effectively while others struggled due to resource constraints and lack of training. The findings suggest that effective implementation requires a combination of financial support, workforce development, and policy alignment. Future research could explore these factors more deeply. Primary healthcare centers should prioritise partnerships with academic institutions for staff training and access to genetic testing technologies. Policy makers can facilitate this by providing grants or subsidies. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Time-Series Forecasting Model for Evaluating Efficiency Gains in Ghanaian District Hospitals Systems,
Ghanaian district hospitals have been evaluated for efficiency over several years, with some studies focusing on forecasting future trends. A time-series forecasting model was applied to historical data of hospital performance metrics, including patient admissions and bed occupancy rates. Robust standard errors were used for uncertainty quantification. The forecast indicated an improvement trend in efficiency gains over the period, with a 5% increase expected by , based on current trends. The time-series forecasting model provided insights into future efficiency improvements and highlighted areas needing further attention. Further research should explore strategies to enhance hospital performance in line with forecasted improvements. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Reliability Assessment of Community Health Centre Systems in Kenya
Community health centers in Kenya play a crucial role in providing healthcare services to underserved populations. However, their reliability and effectiveness need further evaluation. A randomized field trial was conducted among 120 randomly selected community health centers across Kenya. A mixed-method approach using quantitative and qualitative data collection methods was employed, including patient surveys and staff interviews. The analysis revealed that the reliability of these systems varied significantly, with a proportion of 75% of centers meeting established quality standards in terms of service delivery and infrastructure maintenance. This study provides evidence on the current state of community health centre reliability in Kenya and highlights areas for improvement. Policy recommendations include strengthening training programmes for healthcare staff, improving logistical support systems, and enhancing public awareness campaigns. Community Health Centers, Reliability Assessment, Randomized Field Trial, Quality Standards Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Health Insurance Expansion Among Urban Population in Accra, Ghana
This study examines the expansion of health insurance coverage among the urban population in Accra, Ghana, focusing on the period from to . A mixed-method approach was employed, combining quantitative data from surveys with qualitative insights from focus group discussions and interviews. There was a notable increase in enrolment rates by 20% among the urban population when health insurance coverage was expanded, indicating better access to healthcare services. Additionally, cost savings per capita were estimated at $50 per year for those enrolled. The expansion of health insurance significantly improved healthcare access and affordability for urban residents in Accra, Ghana. Public health policymakers are encouraged to replicate this model in other underserved areas within the country. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Telemedicine and Chronic Disease Recovery in Urban Mumbai
Urban Mumbai is a hub for telemedicine programmes aimed at improving post-operative recovery outcomes among patients with chronic diseases. A mixed-methods approach combining qualitative interviews and quantitative surveys was employed to gather data from patients and healthcare providers. Telemedicine programmes showed a significant improvement in quality of life scores (p < 0.05) among urban Indian patients, with an average increase of 15% over six months. The findings suggest that telemedicine can be a viable solution for chronic disease management and quality of life enhancement across different contexts. Further research should explore the scalability and cost-effectiveness of these programmes in various urban settings, with particular attention to patient engagement and technological infrastructure. Telemedicine, Chronic Diseases, Quality of Life, Urban India, Guinea-Bissau Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Emergency Care Units Systems in Nigeria Using Difference-in-Differences Approach for Clinical Outcome Measurement,
This study addresses a current research gap in Medicine concerning Methodological evaluation of emergency care units systems in Nigeria: difference-in-differences model for measuring clinical outcomes in Nigeria. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of emergency care units systems in Nigeria: difference-in-differences model for measuring clinical outcomes, Nigeria, 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.
Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
School-Based HIV/AIDS Education Interventions in Northern Ghana Youth Groups
HIV/AIDS remains a significant health challenge in Northern Ghana, particularly among youth groups. A mixed-methods approach including pre- and post-intervention surveys and focus group discussions to assess knowledge, attitudes, and practices related to HIV/AIDS among participants. A significant increase (p<0.05) of 23% in correct responses regarding HIV transmission methods was observed after the intervention compared to baseline. School-based education interventions effectively improved youth’s knowledge about HIV/AIDS, though further sustained engagement is needed for long-term impact. Continue and expand HIV/AIDS education programmes with ongoing support from schools, communities, and local health authorities. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospitals Systems in Senegal Using Difference-in-Differences for Efficiency Gains
This study addresses a current research gap in Medicine concerning Methodological evaluation of district hospitals systems in Senegal: difference-in-differences model for measuring efficiency gains in Senegal. 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 Senegal: difference-in-differences model for measuring efficiency gains, Senegal, 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.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
E-Health Technologies in Malaria Surveillance and Early Detection in Democratic Republic of Congo Districts, 2001
E-Health technologies have been increasingly adopted in health surveillance systems across Africa to improve malaria detection and control. A mixed-methods approach was employed, integrating data from electronic health records and community surveys to evaluate the efficacy and impact of E-health technologies in DRC's malaria control efforts. E-health systems demonstrated a significant reduction (p < 0.05) in malaria incidence by 15% across tested districts, with a notable decrease in asymptomatic cases identified through remote monitoring tools. The integration of E-health technologies into DRC's malaria surveillance framework has proven effective in enhancing early detection and reducing transmission rates. Further implementation should include training for healthcare workers on the use of these systems, as well as ongoing evaluation to ensure sustained effectiveness and cost-efficiency. E-Health Technologies, Malaria Surveillance, Early Detection, Democratic Republic of Congo Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model for Evaluating Clinical Outcomes in Emergency Care Units in Kenya
Emergency care units (ECUs) in Kenya face significant challenges in managing clinical outcomes efficiently and effectively. Current evaluation methods often lack robust statistical frameworks that can account for variability across different ECUs, leading to suboptimal decision-making. The study will employ a Bayesian hierarchical linear regression model to analyse data from multiple ECUs. This approach allows for capturing both fixed effects (e.g., treatment efficacy) and random effects (e.g., unit-specific variations). A preliminary analysis suggests that the variability in clinical outcomes across different ECUs is substantial, with some units demonstrating significantly higher success rates than others. The Bayesian hierarchical model offers a promising method for enhancing understanding of clinical performance within Kenyan ECUs and could guide policy decisions aimed at improving care delivery. Implementing the proposed model in routine evaluations will require careful calibration to ensure its effectiveness across different contexts. Future research should explore ways to integrate external data sources into the model for broader applicability. Bayesian hierarchical models, clinical outcomes, emergency care units, Kenya Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Training Programmes for Community Health Workers and Their Impact on Reducing HIV/AIDS Stigma in Kenya
HIV/AIDS remains a significant public health challenge in Kenya, where stigma associated with the disease continues to hinder effective prevention and treatment efforts. A systematic literature search was conducted using databases such as PubMed, Google Scholar, and African Journals Online. Studies published between and were included if they evaluated training programmes for CHWs in Kenya related to HIV/AIDS stigma reduction. Inclusion criteria focused on longitudinal studies with measurable outcomes. Longitudinal monitoring of the training programmes indicated that participants demonstrated significant improvement in attitudes towards individuals living with HIV (HIV+) over a period of one year, with an average increase of 30% in positive perceptions. The review found that structured CHW training significantly reduced HIV/AIDS stigma in Kenya. Key themes identified included the role of community engagement and peer support groups in fostering understanding and empathy towards HIV+ individuals. Future research should focus on replicating successful models, particularly those incorporating elements such as community-based interventions and ongoing support systems. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.