Pub Date : 2024-05-05DOI: 10.51594/imsrj.v4i5.1121
Charles Chukwudalu Ebulue, Ogochukwu Virginia Ekkeh, Ogochukwu Roseline Ebulue, Chukwunonso Sylvester Ekesiobi
Predicting and preventing HIV outbreaks in Sub-Saharan Africa, a region disproportionately affected by the epidemic remains a significant challenge. This review explores the effectiveness and challenges of using machine learning (ML) for forecasting HIV spread in high-risk areas. ML models have shown promise in identifying patterns and trends in HIV data, enabling more accurate predictions and targeted interventions. ML insights into HIV outbreak predictions leverage various data sources, including demographic, epidemiological, and behavioural data. By analysing these data, ML algorithms can identify high-risk populations and geographical areas susceptible to HIV transmission. This information is crucial for public health authorities to allocate resources efficiently and implement preventive measures effectively. Despite the potential benefits, several challenges exist in using ML for HIV outbreak predictions. These include data quality issues, such as incomplete or inaccurate data, which can affect the reliability of predictions. Additionally, the complexity of HIV transmission dynamics and the need for real-time data pose challenges for ML models. To address these challenges, researchers and practitioners are exploring innovative approaches, such as integrating multiple data sources and using advanced ML techniques. Collaborations between researchers, public health officials, and technology experts are also crucial for developing robust ML models for HIV outbreak predictions. In conclusion, while ML offers valuable insights into HIV outbreak predictions in Sub-Saharan Africa, addressing challenges such as data quality and model complexity is essential for its effective use. By overcoming these challenges, ML has the potential to significantly improve HIV prevention efforts and ultimately reduce the burden of the epidemic in the region. Keywords: Machine Learning, AI, HIV Outbreaks: Predictions, Insights.
撒哈拉以南非洲地区受艾滋病疫情的影响尤为严重，预测和预防该地区的艾滋病疫情爆发仍是一项重大挑战。本综述探讨了使用机器学习（ML）预测高风险地区艾滋病传播的有效性和挑战。ML 模型在识别 HIV 数据中的模式和趋势方面已显示出良好的前景，从而能够进行更准确的预测和有针对性的干预。对艾滋病毒爆发预测的 ML 见解利用了各种数据源，包括人口、流行病学和行为数据。通过分析这些数据，ML 算法可以识别易受 HIV 传播影响的高危人群和地理区域。这些信息对于公共卫生部门高效分配资源和有效实施预防措施至关重要。尽管有潜在的益处，但在使用 ML 进行艾滋病爆发预测时仍存在一些挑战。其中包括数据质量问题，如数据不完整或不准确，这会影响预测的可靠性。此外，HIV 传播动态的复杂性和对实时数据的需求也对 ML 模型提出了挑战。为了应对这些挑战，研究人员和从业人员正在探索创新方法，如整合多个数据源和使用先进的 ML 技术。研究人员、公共卫生官员和技术专家之间的合作对于开发用于预测艾滋病爆发的强大 ML 模型也至关重要。总之，尽管 ML 为撒哈拉以南非洲地区的艾滋病疫情预测提供了宝贵的见解，但解决数据质量和模型复杂性等挑战对其有效使用至关重要。通过克服这些挑战，ML 有可能显著改善 HIV 预防工作，并最终减轻该地区的疫情负担。关键词 机器学习、人工智能、艾滋病爆发：预测、洞察。
{"title":"Machine learning insights into HIV outbreak predictions in Sub-Saharan Africa","authors":"Charles Chukwudalu Ebulue, Ogochukwu Virginia Ekkeh, Ogochukwu Roseline Ebulue, Chukwunonso Sylvester Ekesiobi","doi":"10.51594/imsrj.v4i5.1121","DOIUrl":"https://doi.org/10.51594/imsrj.v4i5.1121","url":null,"abstract":"Predicting and preventing HIV outbreaks in Sub-Saharan Africa, a region disproportionately affected by the epidemic remains a significant challenge. This review explores the effectiveness and challenges of using machine learning (ML) for forecasting HIV spread in high-risk areas. ML models have shown promise in identifying patterns and trends in HIV data, enabling more accurate predictions and targeted interventions. ML insights into HIV outbreak predictions leverage various data sources, including demographic, epidemiological, and behavioural data. By analysing these data, ML algorithms can identify high-risk populations and geographical areas susceptible to HIV transmission. This information is crucial for public health authorities to allocate resources efficiently and implement preventive measures effectively. Despite the potential benefits, several challenges exist in using ML for HIV outbreak predictions. These include data quality issues, such as incomplete or inaccurate data, which can affect the reliability of predictions. Additionally, the complexity of HIV transmission dynamics and the need for real-time data pose challenges for ML models. To address these challenges, researchers and practitioners are exploring innovative approaches, such as integrating multiple data sources and using advanced ML techniques. Collaborations between researchers, public health officials, and technology experts are also crucial for developing robust ML models for HIV outbreak predictions. In conclusion, while ML offers valuable insights into HIV outbreak predictions in Sub-Saharan Africa, addressing challenges such as data quality and model complexity is essential for its effective use. By overcoming these challenges, ML has the potential to significantly improve HIV prevention efforts and ultimately reduce the burden of the epidemic in the region. \u0000Keywords: Machine Learning, AI, HIV Outbreaks: Predictions, Insights.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":"280 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-05DOI: 10.51594/imsrj.v4i5.1119
Charles Chukwudalu Ebulue, Ogochukwu Virginia Ekkeh, Ogochukwu Roseline Ebulue, Chukwunonso Sylvester Ekesiobi
This paper proposes a novel approach to combating HIV drug resistance through the development of predictive models leveraging genomic data and artificial intelligence (AI). With the increasing prevalence of drug-resistant strains of HIV, there is a critical need for innovative strategies to predict and manage resistance mutations, thereby optimizing treatment outcomes and prolonging the efficacy of antiretroviral therapy (ART). Drawing on advances in genomics and AI, this study outlines a conceptual framework for the development of predictive models that can identify potential drug-resistance mutations in HIV genomes and inform clinical decision-making. The proposed framework integrates genomic data from HIV-infected individuals with AI algorithms capable of learning complex patterns within the data. By analyzing genomic sequences obtained from HIV-positive patients, the models aim to identify genetic variations associated with drug resistance, predict the likelihood of resistance development, and guide the selection of appropriate treatment regimens. This approach holds promise for personalized medicine in HIV care, enabling clinicians to tailor therapy based on an individual's genetic profile and risk of resistance. Key components of the conceptual framework include data preprocessing to extract relevant genomic features, model training using machine learning techniques such as deep learning and ensemble methods, and validation of predictive performance through cross-validation and independent testing. Furthermore, the integration of clinical data, such as treatment history and viral load measurements, enhances the predictive accuracy of the models and provides valuable insights into treatment response dynamics.The development of predictive models for HIV drug resistance represents a paradigm shift in HIV care, offering a proactive approach to treatment management and surveillance. By leveraging genomic and AI technologies, healthcare providers can anticipate and address emerging resistance mutations before they compromise treatment efficacy. Ultimately, the implementation of predictive models holds the potential to improve patient outcomes, reduce the transmission of drug-resistant HIV strains, and advance the global fight against HIV/AIDS. Keywords: Developing, Predictive Models, HIV Drug Resistance, Genomic, AI Approach.
本文提出了一种利用基因组数据和人工智能（AI）开发预测模型来对抗艾滋病耐药性的新方法。随着艾滋病耐药株的日益流行，亟需创新战略来预测和管理耐药突变，从而优化治疗效果并延长抗逆转录病毒疗法（ART）的疗效。本研究利用基因组学和人工智能方面的进展，概述了开发预测模型的概念框架，该模型可识别 HIV 基因组中潜在的耐药性突变，并为临床决策提供信息。所提出的框架整合了艾滋病毒感染者的基因组数据和能够学习数据中复杂模式的人工智能算法。通过分析 HIV 阳性患者的基因组序列，这些模型旨在识别与耐药性相关的基因变异，预测耐药性产生的可能性，并指导选择适当的治疗方案。这种方法为艾滋病护理中的个性化医疗带来了希望，使临床医生能够根据个体的基因特征和耐药性风险量身定制治疗方案。概念框架的关键组成部分包括提取相关基因组特征的数据预处理、使用深度学习和集合方法等机器学习技术进行模型训练，以及通过交叉验证和独立测试验证预测性能。此外，治疗史和病毒载量测量等临床数据的整合提高了模型的预测准确性，并为治疗反应动态提供了有价值的见解。通过利用基因组学和人工智能技术，医疗服务提供者可以在新出现的耐药性突变影响治疗效果之前对其进行预测和处理。最终，预测模型的实施有可能改善患者的治疗效果，减少耐药艾滋病菌株的传播，推动全球抗击艾滋病的斗争。关键词 开发 预测模型 HIV 耐药性 基因组 人工智能方法
{"title":"Developing predictive models for HIV Drug resistance: A genomic and AI approach","authors":"Charles Chukwudalu Ebulue, Ogochukwu Virginia Ekkeh, Ogochukwu Roseline Ebulue, Chukwunonso Sylvester Ekesiobi","doi":"10.51594/imsrj.v4i5.1119","DOIUrl":"https://doi.org/10.51594/imsrj.v4i5.1119","url":null,"abstract":" This paper proposes a novel approach to combating HIV drug resistance through the development of predictive models leveraging genomic data and artificial intelligence (AI). With the increasing prevalence of drug-resistant strains of HIV, there is a critical need for innovative strategies to predict and manage resistance mutations, thereby optimizing treatment outcomes and prolonging the efficacy of antiretroviral therapy (ART). Drawing on advances in genomics and AI, this study outlines a conceptual framework for the development of predictive models that can identify potential drug-resistance mutations in HIV genomes and inform clinical decision-making. The proposed framework integrates genomic data from HIV-infected individuals with AI algorithms capable of learning complex patterns within the data. By analyzing genomic sequences obtained from HIV-positive patients, the models aim to identify genetic variations associated with drug resistance, predict the likelihood of resistance development, and guide the selection of appropriate treatment regimens. This approach holds promise for personalized medicine in HIV care, enabling clinicians to tailor therapy based on an individual's genetic profile and risk of resistance. Key components of the conceptual framework include data preprocessing to extract relevant genomic features, model training using machine learning techniques such as deep learning and ensemble methods, and validation of predictive performance through cross-validation and independent testing. Furthermore, the integration of clinical data, such as treatment history and viral load measurements, enhances the predictive accuracy of the models and provides valuable insights into treatment response dynamics.The development of predictive models for HIV drug resistance represents a paradigm shift in HIV care, offering a proactive approach to treatment management and surveillance. By leveraging genomic and AI technologies, healthcare providers can anticipate and address emerging resistance mutations before they compromise treatment efficacy. Ultimately, the implementation of predictive models holds the potential to improve patient outcomes, reduce the transmission of drug-resistant HIV strains, and advance the global fight against HIV/AIDS. \u0000Keywords: Developing, Predictive Models, HIV Drug Resistance, Genomic, AI Approach.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":"354 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sustainable Supply Chain Management (SSCM) has emerged as a critical paradigm in the modern healthcare landscape, aiming to reconcile the often conflicting objectives of environmental stewardship, social responsibility, and economic viability within medical supply chains. This paper offers a comprehensive theoretical and practical exploration of SSCM within the context of the medical industry. Six keywords - sustainability, supply chain management, healthcare, environmental stewardship, social responsibility, economic viability - encapsulate the essence of this examination. The introduction sets the stage by highlighting the growing importance of sustainability in healthcare operations and the unique challenges faced by the medical sector in achieving sustainable supply chains. It underscores the significance of integrating environmental, social, and economic considerations into the fabric of medical supply chain management practices. The subsequent sections delve into various facets of SSCM in the medical industry. They address key components such as reducing carbon footprint and waste, fostering social responsibility through ethical sourcing practices, and striking a balance between sustainability objectives and cost efficiency. Regulatory frameworks and compliance requirements specific to healthcare supply chains are also explored, emphasizing the need for alignment with evolving sustainability standards. Technological innovations play a pivotal role in driving sustainability in medical supply chains, with advancements in data analytics, blockchain, and IoT enabling enhanced visibility, traceability, and efficiency. Moreover, collaboration and partnerships among stakeholders are deemed essential for fostering sustainable practices across the healthcare ecosystem. Drawing from real-world case studies, the paper illustrates successful implementations of SSCM principles in the medical industry, showcasing best practices and lessons learned. Finally, it prognosticates future trends and challenges, anticipating continued emphasis on sustainability amidst evolving market dynamics and regulatory landscapes. In sum, this theoretical and practical examination underscores the imperative for sustainable supply chain management in the medical industry, offering insights and strategies to navigate the complex interplay of environmental, social, and economic factors in healthcare logistics. Keywords: Sustainability, Supply Chain Management, Healthcare, Environmental Stewardship, Social Responsibility, Economic Viability.
{"title":"SUSTAINABLE SUPPLY CHAIN MANAGEMENT IN THE MEDICAL INDUSTRY: A THEORETICAL AND PRACTICAL EXAMINATION","authors":"Emmanuel Adeyemi Abaku, Agnes Clare Odimarha","doi":"10.51594/imsrj.v4i3.931","DOIUrl":"https://doi.org/10.51594/imsrj.v4i3.931","url":null,"abstract":"Sustainable Supply Chain Management (SSCM) has emerged as a critical paradigm in the modern healthcare landscape, aiming to reconcile the often conflicting objectives of environmental stewardship, social responsibility, and economic viability within medical supply chains. This paper offers a comprehensive theoretical and practical exploration of SSCM within the context of the medical industry. Six keywords - sustainability, supply chain management, healthcare, environmental stewardship, social responsibility, economic viability - encapsulate the essence of this examination. The introduction sets the stage by highlighting the growing importance of sustainability in healthcare operations and the unique challenges faced by the medical sector in achieving sustainable supply chains. It underscores the significance of integrating environmental, social, and economic considerations into the fabric of medical supply chain management practices. The subsequent sections delve into various facets of SSCM in the medical industry. They address key components such as reducing carbon footprint and waste, fostering social responsibility through ethical sourcing practices, and striking a balance between sustainability objectives and cost efficiency. Regulatory frameworks and compliance requirements specific to healthcare supply chains are also explored, emphasizing the need for alignment with evolving sustainability standards. Technological innovations play a pivotal role in driving sustainability in medical supply chains, with advancements in data analytics, blockchain, and IoT enabling enhanced visibility, traceability, and efficiency. Moreover, collaboration and partnerships among stakeholders are deemed essential for fostering sustainable practices across the healthcare ecosystem. Drawing from real-world case studies, the paper illustrates successful implementations of SSCM principles in the medical industry, showcasing best practices and lessons learned. Finally, it prognosticates future trends and challenges, anticipating continued emphasis on sustainability amidst evolving market dynamics and regulatory landscapes. In sum, this theoretical and practical examination underscores the imperative for sustainable supply chain management in the medical industry, offering insights and strategies to navigate the complex interplay of environmental, social, and economic factors in healthcare logistics. \u0000Keywords: Sustainability, Supply Chain Management, Healthcare, Environmental Stewardship, Social Responsibility, Economic Viability.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":" 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140213765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The intersection of mental health and substance use presents a complex challenge for public health initiatives globally. This review delves into the critical review and integration of mental health and substance use services within public health frameworks. Understanding the intricate relationship between mental health disorders and substance abuse is pivotal in designing effective interventions and policies. The review examines existing literature, policies, and programs aimed at addressing mental health and substance use disorders within public health initiatives. It highlights the interconnectedness of these issues and the need for integrated approaches that consider the biopsychosocial aspects of individuals' well-being. Furthermore, it explores the prevalence of comorbidity and the implications it poses for treatment outcomes and resource allocation. Integration of mental health and substance use services into public health initiatives involves the collaboration of various stakeholders, including healthcare providers, policymakers, community organizations, and individuals with lived experiences. Strategies such as co-location of services, cross-training of professionals, and implementation of evidence-based practices are essential for fostering synergy and enhancing service delivery. Moreover, the review discusses the importance of destigmatizing mental health and substance use disorders to facilitate help-seeking behavior and access to care. Public awareness campaigns and educational initiatives play a crucial role in challenging misconceptions and promoting a culture of acceptance and support. This review underscores the significance of reviewing and integrating mental health and substance use services within public health initiatives. It advocates for a holistic approach that addresses the complex needs of individuals while striving for equity, accessibility, and quality in service provision. Keywords: Mental Health, Healthcare, Public Health, Services, Cross-training, Review.
{"title":"REVIEW AND INTEGRATION OF MENTAL HEALTH AND SUBSTANCE USE SERVICES IN PUBLIC HEALTH INITIATIVES","authors":"Chinyere Assumpta Onyenwe, Chinyere Onwumere, Ifeoma Pamela Odilibe","doi":"10.51594/imsrj.v4i3.933","DOIUrl":"https://doi.org/10.51594/imsrj.v4i3.933","url":null,"abstract":"The intersection of mental health and substance use presents a complex challenge for public health initiatives globally. This review delves into the critical review and integration of mental health and substance use services within public health frameworks. Understanding the intricate relationship between mental health disorders and substance abuse is pivotal in designing effective interventions and policies. The review examines existing literature, policies, and programs aimed at addressing mental health and substance use disorders within public health initiatives. It highlights the interconnectedness of these issues and the need for integrated approaches that consider the biopsychosocial aspects of individuals' well-being. Furthermore, it explores the prevalence of comorbidity and the implications it poses for treatment outcomes and resource allocation. Integration of mental health and substance use services into public health initiatives involves the collaboration of various stakeholders, including healthcare providers, policymakers, community organizations, and individuals with lived experiences. Strategies such as co-location of services, cross-training of professionals, and implementation of evidence-based practices are essential for fostering synergy and enhancing service delivery. Moreover, the review discusses the importance of destigmatizing mental health and substance use disorders to facilitate help-seeking behavior and access to care. Public awareness campaigns and educational initiatives play a crucial role in challenging misconceptions and promoting a culture of acceptance and support. This review underscores the significance of reviewing and integrating mental health and substance use services within public health initiatives. It advocates for a holistic approach that addresses the complex needs of individuals while striving for equity, accessibility, and quality in service provision. \u0000Keywords: Mental Health, Healthcare, Public Health, Services, Cross-training, Review.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":" 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140218674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The intersection of big data and healthcare product development has catalyzed transformative shifts in the industry, revolutionizing how medical solutions are conceptualized, designed, and deployed. This theoretical and analytical review explores the profound impact of big data on healthcare product development, elucidating its implications across various facets of the healthcare landscape. Utilizing big data analytics, healthcare stakeholders can harness vast volumes of structured and unstructured data to derive actionable insights. These insights inform evidence-based decision-making processes, driving innovation in product development pipelines. By analyzing real-time patient data, trends, and treatment outcomes, developers gain invaluable insights into disease progression, treatment efficacy, and patient preferences, thus facilitating the creation of tailored, patient-centric solutions. Moreover, big data analytics play a pivotal role in improving patient outcomes and quality of care. Through predictive analytics and machine learning algorithms, healthcare providers can identify at-risk populations, predict disease outbreaks, and personalize treatment plans. This proactive approach enhances preventive care strategies and minimizes healthcare costs by averting complications and hospital readmissions. However, the integration of big data into healthcare product development is not without challenges. Data privacy and security concerns necessitate robust frameworks to safeguard sensitive patient information. Moreover, regulatory compliance frameworks must evolve to accommodate the complexities of big data analytics while ensuring patient safety and data integrity. Despite these challenges, the potential of big data in healthcare product development is vast. By leveraging big data analytics, stakeholders can bridge gaps in healthcare access and equity, tailor interventions to underserved populations, and optimize resource allocation. In conclusion, this review underscores the transformative impact of big data on healthcare product development. By embracing data-driven approaches, stakeholders can drive innovation, enhance patient outcomes, and navigate the evolving healthcare landscape with agility and efficacy. Keywords: Big Data, Healthcare Product Development, Innovation, Patient Outcomes, Data Analytics, Regulatory Compliance.
{"title":"THE IMPACT OF BIG DATA ON HEALTHCARE PRODUCT DEVELOPMENT: A THEORETICAL AND ANALYTICAL REVIEW","authors":"Damilola Oluwaseun Ogundipe","doi":"10.51594/imsrj.v4i3.932","DOIUrl":"https://doi.org/10.51594/imsrj.v4i3.932","url":null,"abstract":"The intersection of big data and healthcare product development has catalyzed transformative shifts in the industry, revolutionizing how medical solutions are conceptualized, designed, and deployed. This theoretical and analytical review explores the profound impact of big data on healthcare product development, elucidating its implications across various facets of the healthcare landscape. Utilizing big data analytics, healthcare stakeholders can harness vast volumes of structured and unstructured data to derive actionable insights. These insights inform evidence-based decision-making processes, driving innovation in product development pipelines. By analyzing real-time patient data, trends, and treatment outcomes, developers gain invaluable insights into disease progression, treatment efficacy, and patient preferences, thus facilitating the creation of tailored, patient-centric solutions. Moreover, big data analytics play a pivotal role in improving patient outcomes and quality of care. Through predictive analytics and machine learning algorithms, healthcare providers can identify at-risk populations, predict disease outbreaks, and personalize treatment plans. This proactive approach enhances preventive care strategies and minimizes healthcare costs by averting complications and hospital readmissions. However, the integration of big data into healthcare product development is not without challenges. Data privacy and security concerns necessitate robust frameworks to safeguard sensitive patient information. Moreover, regulatory compliance frameworks must evolve to accommodate the complexities of big data analytics while ensuring patient safety and data integrity. Despite these challenges, the potential of big data in healthcare product development is vast. By leveraging big data analytics, stakeholders can bridge gaps in healthcare access and equity, tailor interventions to underserved populations, and optimize resource allocation. In conclusion, this review underscores the transformative impact of big data on healthcare product development. By embracing data-driven approaches, stakeholders can drive innovation, enhance patient outcomes, and navigate the evolving healthcare landscape with agility and efficacy. \u0000Keywords: Big Data, Healthcare Product Development, Innovation, Patient Outcomes, Data Analytics, Regulatory Compliance.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140213511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Esther Oleiye Itua, James Tabat Bature, Michael Alurame Eruaga
Pharmacy practice standards and challenges in Nigeria constitute a critical area of concern due to their profound impact on healthcare delivery and patient outcomes. This comprehensive analysis delves into the multifaceted landscape of pharmacy practice in Nigeria, highlighting prevailing standards and the array of challenges faced by pharmacists in their professional endeavors. Nigeria, like many other developing countries, grapples with a complex healthcare system marked by resource constraints, regulatory ambiguities, and evolving patient needs. Within this context, pharmacists play a pivotal role as frontline healthcare providers, responsible for ensuring safe and effective medication use. However, the absence of robust regulatory frameworks and standardized practices poses significant hurdles to the delivery of quality pharmaceutical care. This analysis examines the existing pharmacy practice standards in Nigeria, emphasizing the role of regulatory bodies such as the Pharmacists Council of Nigeria (PCN) in setting guidelines and enforcing compliance. It also scrutinizes the challenges encountered by pharmacists, including inadequate infrastructure, limited access to essential medicines, counterfeit drugs, and insufficient professional development opportunities. Furthermore, the analysis explores the impact of socio-economic factors, cultural beliefs, and healthcare disparities on pharmacy practice in Nigeria. It underscores the need for collaborative efforts among stakeholders, including government agencies, healthcare institutions, pharmaceutical industry players, and professional associations, to address these challenges comprehensively. In conclusion, this study underscores the importance of enhancing pharmacy practice standards in Nigeria to promote patient safety, optimize medication therapy outcomes, and advance public health objectives. By addressing the identified challenges and fostering a supportive environment for pharmacists, Nigeria can harness the full potential of its pharmacy workforce to meet the healthcare needs of its population effectively. Keywords: Pharmacy, Standards, Nigeria, Practices, Review.
{"title":"PHARMACY PRACTICE STANDARDS AND CHALLENGES IN NIGERIA: A COMPREHENSIVE ANALYSIS","authors":"Esther Oleiye Itua, James Tabat Bature, Michael Alurame Eruaga","doi":"10.51594/imsrj.v4i3.921","DOIUrl":"https://doi.org/10.51594/imsrj.v4i3.921","url":null,"abstract":"Pharmacy practice standards and challenges in Nigeria constitute a critical area of concern due to their profound impact on healthcare delivery and patient outcomes. This comprehensive analysis delves into the multifaceted landscape of pharmacy practice in Nigeria, highlighting prevailing standards and the array of challenges faced by pharmacists in their professional endeavors. Nigeria, like many other developing countries, grapples with a complex healthcare system marked by resource constraints, regulatory ambiguities, and evolving patient needs. Within this context, pharmacists play a pivotal role as frontline healthcare providers, responsible for ensuring safe and effective medication use. However, the absence of robust regulatory frameworks and standardized practices poses significant hurdles to the delivery of quality pharmaceutical care. This analysis examines the existing pharmacy practice standards in Nigeria, emphasizing the role of regulatory bodies such as the Pharmacists Council of Nigeria (PCN) in setting guidelines and enforcing compliance. It also scrutinizes the challenges encountered by pharmacists, including inadequate infrastructure, limited access to essential medicines, counterfeit drugs, and insufficient professional development opportunities. Furthermore, the analysis explores the impact of socio-economic factors, cultural beliefs, and healthcare disparities on pharmacy practice in Nigeria. It underscores the need for collaborative efforts among stakeholders, including government agencies, healthcare institutions, pharmaceutical industry players, and professional associations, to address these challenges comprehensively. In conclusion, this study underscores the importance of enhancing pharmacy practice standards in Nigeria to promote patient safety, optimize medication therapy outcomes, and advance public health objectives. By addressing the identified challenges and fostering a supportive environment for pharmacists, Nigeria can harness the full potential of its pharmacy workforce to meet the healthcare needs of its population effectively. \u0000Keywords: Pharmacy, Standards, Nigeria, Practices, Review.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":"79 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michael Alurame Eruaga, Esther Oleiye Itua, James Tabat Bature
Medication quality control in Nigeria faces multifaceted challenges rooted in regulatory inefficiencies, infrastructural limitations, and systemic inadequacies. This study undertakes a comprehensive analysis of these challenges while proposing pragmatic solutions to bolster the quality control framework in the Nigerian pharmaceutical sector. Drawing upon extensive literature review and expert insights, the research identifies key regulatory challenges impeding effective medication quality control in Nigeria. These challenges encompass inadequate regulatory capacity, inconsistent enforcement mechanisms, rampant substandard and counterfeit medications, and limited access to essential medicines. Additionally, infrastructural deficiencies such as inadequate laboratory facilities and insufficient human resources further exacerbate the problem, leading to compromised patient safety and public health risks. In response to these challenges, the study proposes a multifaceted approach to enhance medication quality control in Nigeria. This includes strengthening regulatory frameworks through legislative reforms aimed at bolstering enforcement capabilities and harmonizing standards with international best practices. Moreover, improving regulatory capacity through training programs and investment in state-of-the-art laboratory infrastructure is essential to enhance surveillance and detection of substandard medications. Furthermore, fostering collaboration between regulatory agencies, healthcare providers, and pharmaceutical manufacturers is imperative to streamline supply chains and ensure the integrity of medications from production to distribution. Additionally, public awareness campaigns and community engagement initiatives play a pivotal role in empowering consumers to make informed decisions and report instances of substandard medications. By addressing these regulatory challenges and implementing comprehensive solutions, Nigeria can significantly enhance medication quality control, safeguard patient health, and foster a conducive environment for pharmaceutical innovation and growth. Keywords: Medical, Medication, Drugs, Quality Control, Nigeria, Regulations, Review.
{"title":"ENHANCING MEDICATION QUALITY CONTROL IN NIGERIA: A COMPREHENSIVE ANALYSIS OF REGULATORY CHALLENGES AND SOLUTIONS","authors":"Michael Alurame Eruaga, Esther Oleiye Itua, James Tabat Bature","doi":"10.51594/imsrj.v4i3.920","DOIUrl":"https://doi.org/10.51594/imsrj.v4i3.920","url":null,"abstract":"Medication quality control in Nigeria faces multifaceted challenges rooted in regulatory inefficiencies, infrastructural limitations, and systemic inadequacies. This study undertakes a comprehensive analysis of these challenges while proposing pragmatic solutions to bolster the quality control framework in the Nigerian pharmaceutical sector. Drawing upon extensive literature review and expert insights, the research identifies key regulatory challenges impeding effective medication quality control in Nigeria. These challenges encompass inadequate regulatory capacity, inconsistent enforcement mechanisms, rampant substandard and counterfeit medications, and limited access to essential medicines. Additionally, infrastructural deficiencies such as inadequate laboratory facilities and insufficient human resources further exacerbate the problem, leading to compromised patient safety and public health risks. In response to these challenges, the study proposes a multifaceted approach to enhance medication quality control in Nigeria. This includes strengthening regulatory frameworks through legislative reforms aimed at bolstering enforcement capabilities and harmonizing standards with international best practices. Moreover, improving regulatory capacity through training programs and investment in state-of-the-art laboratory infrastructure is essential to enhance surveillance and detection of substandard medications. Furthermore, fostering collaboration between regulatory agencies, healthcare providers, and pharmaceutical manufacturers is imperative to streamline supply chains and ensure the integrity of medications from production to distribution. Additionally, public awareness campaigns and community engagement initiatives play a pivotal role in empowering consumers to make informed decisions and report instances of substandard medications. By addressing these regulatory challenges and implementing comprehensive solutions, Nigeria can significantly enhance medication quality control, safeguard patient health, and foster a conducive environment for pharmaceutical innovation and growth. \u0000Keywords: Medical, Medication, Drugs, Quality Control, Nigeria, Regulations, Review.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":"93 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140234958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, Mobile Health (mHealth) innovations have emerged as a transformative force in the realm of public health, revolutionizing the way healthcare is delivered and monitored worldwide. This review presents a comprehensive overview of the latest advancements in mHealth technologies, focusing particularly on their role in soliciting and utilizing public health feedback on a global scale. The proliferation of smartphones and mobile applications has paved the way for novel approaches to healthcare delivery, monitoring, and data collection. Through leveraging the ubiquity and connectivity of mobile devices, mHealth initiatives have facilitated enhanced communication between healthcare providers and patients, enabling real-time monitoring of health metrics, adherence to treatment regimens, and timely interventions. One of the key aspects of mHealth innovations is their capacity to engage diverse populations and solicit feedback regarding various aspects of public health, ranging from disease outbreaks to healthcare service quality. Through interactive platforms and user-friendly interfaces, individuals can provide valuable insights, report symptoms, and participate in surveys, thereby contributing to the generation of actionable data for public health interventions. Furthermore, mHealth solutions have demonstrated significant promise in overcoming barriers to healthcare access, particularly in underserved and remote communities. By delivering health information, diagnostic tools, and remote consultations via mobile platforms, these innovations have expanded the reach of essential healthcare services, thereby bridging gaps in healthcare delivery and improving health outcomes on a global scale. However, challenges such as privacy concerns, technological literacy, and disparities in digital access persist, underscoring the importance of equitable deployment and user-centered design in mHealth initiatives. Moreover, the integration of mHealth solutions into existing healthcare infrastructure requires careful coordination among stakeholders, including policymakers, healthcare providers, and technology developers. Mobile Health (mHealth) innovations hold immense potential to revolutionize public health feedback mechanisms on a global scale. By harnessing the power of mobile technologies, these initiatives can empower individuals, enhance healthcare delivery, and inform evidence-based public health policies for a healthier future. Keywords: Mobile Health, mHealth, Public Health, Healthcare, Innovation, Review.
{"title":"MOBILE HEALTH (MHEALTH) INNOVATIONS FOR PUBLIC HEALTH FEEDBACK: A GLOBAL PERSPECTIVE","authors":"Chioma Anthonia Okolo, Oloruntoba Babawarun, Tolulope Oyinlola Olorunsogo","doi":"10.51594/imsrj.v4i3.915","DOIUrl":"https://doi.org/10.51594/imsrj.v4i3.915","url":null,"abstract":"In recent years, Mobile Health (mHealth) innovations have emerged as a transformative force in the realm of public health, revolutionizing the way healthcare is delivered and monitored worldwide. This review presents a comprehensive overview of the latest advancements in mHealth technologies, focusing particularly on their role in soliciting and utilizing public health feedback on a global scale. The proliferation of smartphones and mobile applications has paved the way for novel approaches to healthcare delivery, monitoring, and data collection. Through leveraging the ubiquity and connectivity of mobile devices, mHealth initiatives have facilitated enhanced communication between healthcare providers and patients, enabling real-time monitoring of health metrics, adherence to treatment regimens, and timely interventions. One of the key aspects of mHealth innovations is their capacity to engage diverse populations and solicit feedback regarding various aspects of public health, ranging from disease outbreaks to healthcare service quality. Through interactive platforms and user-friendly interfaces, individuals can provide valuable insights, report symptoms, and participate in surveys, thereby contributing to the generation of actionable data for public health interventions. Furthermore, mHealth solutions have demonstrated significant promise in overcoming barriers to healthcare access, particularly in underserved and remote communities. By delivering health information, diagnostic tools, and remote consultations via mobile platforms, these innovations have expanded the reach of essential healthcare services, thereby bridging gaps in healthcare delivery and improving health outcomes on a global scale. However, challenges such as privacy concerns, technological literacy, and disparities in digital access persist, underscoring the importance of equitable deployment and user-centered design in mHealth initiatives. Moreover, the integration of mHealth solutions into existing healthcare infrastructure requires careful coordination among stakeholders, including policymakers, healthcare providers, and technology developers. Mobile Health (mHealth) innovations hold immense potential to revolutionize public health feedback mechanisms on a global scale. By harnessing the power of mobile technologies, these initiatives can empower individuals, enhance healthcare delivery, and inform evidence-based public health policies for a healthier future. \u0000Keywords: Mobile Health, mHealth, Public Health, Healthcare, Innovation, Review.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":"15 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, the integration of Internet of Things (IoT) technologies into healthcare systems has shown immense promise in revolutionizing patient care, particularly in pediatric populations. This systematic review aims to explore the current landscape of IoT applications in pediatric healthcare, specifically focusing on pancreatic diseases and obesity, two significant health challenges affecting children worldwide. The review comprehensively analyzes existing literature, including peer-reviewed articles, conference papers, and relevant reports. By employing systematic search strategies across various databases, studies were identified, screened, and synthesized to elucidate the diverse applications of IoT in managing pancreatic diseases and obesity among pediatric patients. The findings reveal a multitude of IoT applications tailored to pediatric healthcare, ranging from wearable devices for continuous glucose monitoring in diabetic children to smart scales and activity trackers for managing pediatric obesity. These technologies offer real-time monitoring, data analytics, and personalized interventions, enhancing disease management, improving patient outcomes, and promoting patient engagement and adherence to treatment regimens. Furthermore, this review identifies critical challenges and limitations associated with current IoT implementations in pediatric healthcare, such as data privacy concerns, interoperability issues, and the need for robust regulatory frameworks. Addressing these challenges is crucial to maximizing the potential benefits of IoT in pediatric healthcare and ensuring its safe and effective integration into clinical practice. The review outlines promising future directions for IoT in managing pancreatic diseases and obesity in pediatric populations. These include integrating advanced sensors and artificial intelligence algorithms for predictive analytics, developing user-friendly and child-centric IoT solutions, and establishing collaborative networks for data sharing and knowledge exchange. This systematic review underscores the transformative impact of IoT technologies in pediatric healthcare, particularly in managing pancreatic diseases and obesity. By highlighting current applications and future directions, this study provides valuable insights for clinicians, researchers, and policymakers to harness the full potential of IoT in improving pediatric health outcomes. Keywords: IoT, Healthcare, Pancreatic, Disease, Obesity, Pediatric, Review.
{"title":"INTEGRATING IOT IN PEDIATRIC HEALTHCARE: A SYSTEMATIC REVIEW OF CURRENT APPLICATIONS AND FUTURE DIRECTIONS FOR PANCREATIC DISEASES AND OBESITY Tolulope O. Olorunsogo1","authors":"Tolulope O. Olorunsogo","doi":"10.51594/imsrj.v4i3.923","DOIUrl":"https://doi.org/10.51594/imsrj.v4i3.923","url":null,"abstract":" In recent years, the integration of Internet of Things (IoT) technologies into healthcare systems has shown immense promise in revolutionizing patient care, particularly in pediatric populations. This systematic review aims to explore the current landscape of IoT applications in pediatric healthcare, specifically focusing on pancreatic diseases and obesity, two significant health challenges affecting children worldwide. The review comprehensively analyzes existing literature, including peer-reviewed articles, conference papers, and relevant reports. By employing systematic search strategies across various databases, studies were identified, screened, and synthesized to elucidate the diverse applications of IoT in managing pancreatic diseases and obesity among pediatric patients. The findings reveal a multitude of IoT applications tailored to pediatric healthcare, ranging from wearable devices for continuous glucose monitoring in diabetic children to smart scales and activity trackers for managing pediatric obesity. These technologies offer real-time monitoring, data analytics, and personalized interventions, enhancing disease management, improving patient outcomes, and promoting patient engagement and adherence to treatment regimens. Furthermore, this review identifies critical challenges and limitations associated with current IoT implementations in pediatric healthcare, such as data privacy concerns, interoperability issues, and the need for robust regulatory frameworks. Addressing these challenges is crucial to maximizing the potential benefits of IoT in pediatric healthcare and ensuring its safe and effective integration into clinical practice. The review outlines promising future directions for IoT in managing pancreatic diseases and obesity in pediatric populations. These include integrating advanced sensors and artificial intelligence algorithms for predictive analytics, developing user-friendly and child-centric IoT solutions, and establishing collaborative networks for data sharing and knowledge exchange. This systematic review underscores the transformative impact of IoT technologies in pediatric healthcare, particularly in managing pancreatic diseases and obesity. By highlighting current applications and future directions, this study provides valuable insights for clinicians, researchers, and policymakers to harness the full potential of IoT in improving pediatric health outcomes. \u0000Keywords: IoT, Healthcare, Pancreatic, Disease, Obesity, Pediatric, Review.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":"8 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Coinfections, particularly in patients with HIV, hepatitis C, or tuberculosis, present complex challenges in anesthesia and pain management. This review examines the unique considerations, techniques, and strategies for providing safe and effective care to this vulnerable population. It explores the impact of coinfections on anesthesia outcomes, the role of multidisciplinary approaches, and the implications for public health. Patients with coinfections often have complex medical histories, including comorbidities and compromised immune systems, which can affect their response to anesthesia and pain management. Strategies such as preoperative optimization, tailored anesthetic plans, and close monitoring are crucial to mitigate risks and ensure positive outcomes. Multidisciplinary collaboration is essential in managing coinfections, involving anesthesiologists, infectious disease specialists, surgeons, and other healthcare professionals. This approach allows for comprehensive care that addresses the unique needs and challenges of coinfected patients. Public health implications of coinfections in anesthesia and pain management are significant, as they can impact healthcare resource utilization, treatment outcomes, and overall healthcare costs. Understanding the challenges and implementing effective strategies can lead to improved public health outcomes for this vulnerable population. In conclusion, coinfections present complex challenges in anesthesia and pain management, requiring tailored approaches and multidisciplinary collaboration. By addressing these challenges, healthcare providers can improve outcomes for coinfected patients and contribute to better public health outcomes overall. Keywords: Anesthesia, Pain Management, Public Health, Techniques, Coinfected Patients.
{"title":"ANESTHESIA, PAIN MANAGEMENT, AND PUBLIC HEALTH: A REVIEW OF TECHNIQUES AND STRATEGIES FOR COINFECTED PATIENTS","authors":"Chioma Anthonia Okolo, Oloruntoba Babawarun, Tolulope Oyinlola Olorunsogo","doi":"10.51594/imsrj.v4i3.916","DOIUrl":"https://doi.org/10.51594/imsrj.v4i3.916","url":null,"abstract":" Coinfections, particularly in patients with HIV, hepatitis C, or tuberculosis, present complex challenges in anesthesia and pain management. This review examines the unique considerations, techniques, and strategies for providing safe and effective care to this vulnerable population. It explores the impact of coinfections on anesthesia outcomes, the role of multidisciplinary approaches, and the implications for public health. Patients with coinfections often have complex medical histories, including comorbidities and compromised immune systems, which can affect their response to anesthesia and pain management. Strategies such as preoperative optimization, tailored anesthetic plans, and close monitoring are crucial to mitigate risks and ensure positive outcomes. Multidisciplinary collaboration is essential in managing coinfections, involving anesthesiologists, infectious disease specialists, surgeons, and other healthcare professionals. This approach allows for comprehensive care that addresses the unique needs and challenges of coinfected patients. Public health implications of coinfections in anesthesia and pain management are significant, as they can impact healthcare resource utilization, treatment outcomes, and overall healthcare costs. Understanding the challenges and implementing effective strategies can lead to improved public health outcomes for this vulnerable population. In conclusion, coinfections present complex challenges in anesthesia and pain management, requiring tailored approaches and multidisciplinary collaboration. By addressing these challenges, healthcare providers can improve outcomes for coinfected patients and contribute to better public health outcomes overall. \u0000Keywords: Anesthesia, Pain Management, Public Health, Techniques, Coinfected Patients.","PeriodicalId":508118,"journal":{"name":"International Medical Science Research Journal","volume":"147 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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