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Article Volume 6 Issue 5 2066 - 2091 October 23, 2023

AI-augmented Governance of the Ghanaian Healthcare Delivery System: Ethical and Privacy Issues in Patients Medical Records, Access and Retrieval

Lead author · Corresponding
Alfred Addy
RGN, MPH, Independent Researcher, Ghana
View PDF Full text DOIhttps://doij.org/10.10000/IJLMH.115984
Abstract

AI-augmented governance of the Ghanaian healthcare delivery system has undoubtedly revolutionized the way medical records are accessed and retrieved. However, it is imperative to address the ethical and privacy concerns surrounding patients' medical records. Firstly, the use of AI raises ethical issues regarding patient consent and autonomy. Patients have a right to know how their medical data is being used and shared. Without proper informed consent, AI algorithms may access sensitive information without patients' knowledge or approval. This infringes upon their privacy rights and undermines their autonomy in decision-making. Furthermore, there is a risk of data breaches and unauthorized access to patients' medical records when AI systems are involved. The Ghanaian healthcare system must ensure robust security measures are in place to protect patient information from cyber threats. Failure to do so not only compromises patient privacy but also exposes them to potential harm if their data falls into the wrong hands. In conclusion, while AI-augmented governance offers numerous benefits for the Ghanaian healthcare delivery system, it is crucial to prioritize ethical considerations and safeguard patient privacy. Stricter regulations should be implemented to ensure that patients have control over their medical records and that their personal information remains secure. Only by addressing these concerns can we fully harness the potential of AI in improving healthcare outcomes while maintaining respect for individual rights.

Type
Article
Information
International Journal of Law Management and Humanities, Volume 6, Issue 5, Page 2066 - 2091
DOI: https://doij.org/10.10000/IJLMH.115984
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CC BY-NC 4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.
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Copyright © IJLMH 2026
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The views and opinions expressed in this manuscript are those of the author(s) alone and do not reflect the views, policies, or position of the Journal.

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