Comparative Nursing and Midwifery Regulatory Analysis: Ghana, South Africa, Kenya and Liberia in Context
Abstract
This comparative analysis examines the nursing and midwifery regulatory frameworks of Ghana, South Africa, Kenya, and Liberia to identify strengths, weaknesses, and areas for improvement. The analysis reveals that while Ghana and South Africa have relatively comprehensive and up-to-date frameworks, Kenya and Liberia face challenges related to the scope and currency of their legislation and the effectiveness of their regulatory bodies. Key recommendations include conducting comprehensive reviews and harmonization of regulatory frameworks, strengthening the capacity of regulatory bodies, establishing formal requirements for continuous professional development, promoting collaboration and sharing of best practices, enhancing transparency and accountability in regulatory processes, and investing in research and data collection. The analysis holds significant policy implications for strengthening healthcare governance and improving the quality of care in these countries. By providing a roadmap for evidence-based policy decisions and targeted interventions, this analysis can drive meaningful change and improvement in the governance of nursing and midwifery in Ghana, South Africa, Kenya, and Liberia.
... This sub-issue concerns who is held responsible when errors occur in AI-assisted telemedicine consultations. [24] examines AI and medical negligence, highlighting the complexities of determining liability when AI systems are involved in healthcare delivery. The study notes that Ghana's current medical negligence laws, as discussed in [41], may not adequately address scenarios involving AI systems. ...
This study examines the adequacy of regulations concerning consent and patient autonomy in AI telemedicine in Ghana. Using the IRAC (Issue, Rule, Analysis, and Conclusion) method, the research analyzes existing Ghanaian healthcare laws and regulations in the context of AI-driven telemedicine. The study finds significant gaps in the current regulatory framework, including a lack of specific provisions for informed consent in AI telemedicine, unclear guidelines on maintaining patient autonomy, and inadequate addressing of liability issues in AI-assisted healthcare. Recommendations include developing specific AI healthcare legislation, updating existing laws to incorporate AI and telemedicine considerations, establishing AI ethics committees, and implementing short-term mitigation strategies such as interpretive guidelines and enhanced disclosure protocols. The study emphasizes the need for a two-pronged approach: long-term regulatory development and immediate implementation of interim measures to protect patient rights and ensure ethical use of AI in telemedicine.
This compilation of bibliographies is to help researchers conducting studies into healthcare regulation in developing countries. They have been compiled in one document to facilitate the ease of scholarly research into the relevant healthcare regulation in developing countries especially Ghana.
This compilation of bibliographies is to help researchers conducting studies into healthcare regulation in developing countries. They have been compiled in one document to facilitate the ease of scholarly research into the relevant healthcare regulation in developing countries especially Ghana.
This compilation of bibliographies is to help researchers conducting studies into healthcare regulation in developing countries. They have been compiled in one document to facilitate the ease of scholarly research into the relevant healthcare regulation in developing countries especially Ghana.
This compilation of bibliographies is to help researchers conducting studies into healthcare regulation in developing countries. They have been compiled in one document to facilitate the ease of scholarly research into the relevant healthcare regulation in developing countries especially Ghana.
This paper provides a comprehensive analysis of artificial intelligence (AI) implementation in Ghana's healthcare system, synthesizing findings from recent Ghanaian studies. It examines legal and regulatory frameworks, ethical considerations, bias and fairness, transparency and accountability, interdisciplinary approaches, patient rights and data protection, healthcare access and equity, and implementation and oversight. The analysis reveals both significant opportunities for AI to improve healthcare delivery in Ghana and substantial challenges in ensuring its ethical, equitable, and effective implementation. Key findings highlight the need for AI-specific healthcare regulations, investment in local capacity building, culturally sensitive AI design, robust fairness and accountability mechanisms, and ongoing stakeholder engagement. This paper contributes to the discourse on AI in healthcare in developing countries, offering insights into the unique challenges faced by lower-middle-income countries. It aims to inform evidence-based policymaking and enrich academic understanding of AI implementation in diverse cultural and economic contexts.
This paper examines the critical role of trust and transparency in the adoption and implementation of AI health tools in Ghana. Through a comprehensive analysis of Ghanaian studies, it explores the regulatory, ethical, and practical challenges of integrating AI into the healthcare system. The study employs the CRAC methodology to analyze claims, reasons, assumptions, and counterarguments related to trust in AI health tools. Key findings reveal inadequacies in current regulatory frameworks to address AI-specific issues, the need for a multidisciplinary approach to building trust, and the importance of transparency in mitigating medical negligence risks. The paper concludes that trust and transparency are essential for the effective and equitable implementation of AI health tools in Ghana. Recommendations include updating regulatory frameworks, establishing ethical guidelines, implementing phased adoption strategies, and fostering public-private partnerships. These insights aim to guide stakeholders in creating a healthcare ecosystem where AI tools are trusted, transparent, and beneficial to all Ghanaian citizens.
This study employs SWOT analysis to evaluate the ethical and privacy considerations of AI predictive health tools in Ghana, drawing insights from recent Ghanaian research. The analysis reveals strengths in Ghana's growing body of AI healthcare research and legal framework analyses, while identifying weaknesses in specific predictive health focus and potential legislative gaps. Opportunities include improving healthcare access, developing comprehensive regulations, and positioning Ghana as a leader in ethical AI healthcare in Africa. Threats encompass rapid technological advancement outpacing regulations, data security risks, and potential exacerbation of health disparities. The study concludes with recommendations for developing AI-specific healthcare regulations, enhancing interdisciplinary research, conducting empirical studies, and focusing on health equity. This analysis provides a structured framework for addressing the complex challenges of implementing AI predictive health tools ethically and effectively in Ghana's healthcare system.
This study examines the regulatory landscape governing liability and accountability in AI telemedicine in Ghana. Using the CREAC (Context, Rules, Explanation, Application, Conclusion) legal analytical approach, it analyzes existing Ghanaian healthcare laws and regulations in the context of AI telemedicine. The study finds that while Ghana has a comprehensive set of healthcare regulations, they are inadequately equipped to address the unique challenges posed by AI in telemedicine, particularly regarding liability determination, accountability mechanisms, and error management. Significant gaps exist in current legislation, leaving Ghana vulnerable to the risks associated with AI in healthcare. The study recommends developing AI-specific healthcare legislation, updating existing laws, establishing a national AI in healthcare ethics committee, implementing a certification system for AI in healthcare, and creating a specialized AI healthcare liability framework. These measures aim to balance innovation in AI telemedicine with patient safety and ethical healthcare delivery.
This analysis examines Ghana's regulatory framework for ensuring access, equity, and addressing disparities in AI health applications. Utilizing the CRuPAC (Context, Rules, Principles, Application, and Conclusion) method, the study reviews relevant Ghanaian legislation and recent scholarly works. The analysis reveals that while Ghana has a comprehensive set of health-related laws, these regulations lack specific provisions for AI technologies in healthcare. This gap potentially leads to inconsistencies in AI implementation, risking new forms of health disparities. Key issues identified include the need for AI-specific regulations, enhanced professional training, and measures to ensure equitable access to AI health technologies. The study concludes with recommendations for updating existing legislation, developing AI-specific healthcare regulations, strengthening data protection measures, and fostering public-private partnerships. These steps aim to create a regulatory environment that promotes innovation while ensuring equitable access and protecting patient rights in an AI-augmented healthcare system.
Background:
The Republic of Liberia has had major disruptions to the education of its health care cadres. Post Ebola, the Resilient and Responsive Health Systems (RRHS) initiative began a new era of capacity building with the support of PEPFAR and HRSA. Nursing and Midwifery serve as the largest healthcare cadres in Liberia. The national nursing and midwifery curricula were overdue for the regulated review and revisions.
Methods:
The Science of Improvement was used as the framework to accomplish this multilateral activity. The Institute for Healthcare Improvement's (IHI) stages of improvement included: 1) Forming the team, 2) Setting the aims, 3) Establishing measures, 4) Selecting measures, 5) Testing changes, 6) Implementing changes, and 7) Spreading changes. These stages served as the blueprint for the structures and processes put into place to accomplish this national activity.
Findings:
The RN, Bridging, and BScM curricula all had redundant content that did not reflect teaching pedagogy and health priorities in Liberia. Courses were eliminated or reconfigured and new courses were created. Development of Nursing and Midwifery Curricular Taskforces were not as successful as was hoped. Two large stakeholder meetings ensured that this was the curricula of the Liberian faculty, deans and directors, and clinical partners. Monitoring and evaluation tools have been adopted by the Liberian Board for Nursing and Midwifery to serve as another improvement to check that the new curricula are being implemented and to identify gaps that may require future cycles of change for continued quality and improvement.
Conclusions:
Developing trust among the multilateral partners was critical to the success of this activity. Networks have been expanded, and a proposed pilot with the Ghana Board of Nursing and Midwifery and the US academic partner will examine the feasibility of implementing electronic licensing examinations for nurses and midwives.
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