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Medical Big Data and its Ethical Challenges in Violation of Patient Privacy
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A Ghasempour   |
| Ph.D. Graduated in Private Law, Faculty of Law and Political Science, University of Tehran. , Amin.Ghasempour@ut.ac.ir |
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Abstract: (57 Views) |
Background: Big data refers to a large volume of information that is increasing day by day, and by analyzing it, various cause and effect relationships that have not been discovered so far can be established. This capability has many applications in various fields, including the field of health and wellness, so that it is predicted that very valuable results will be obtained in the field of diagnosis, prevention and treatment of diseases. On the other hand, in addition to the numerous benefits of big data, attention should also be paid to the ethical challenges that medical big data creates. This means that the use of medical big data requires the aggregation of information related to patients and those who participate in medical research, and this "potentially" entails the risk of violating the privacy and "autonomy" of patients. The author of the article, using an analytical and descriptive method and by studying the works of other authors, has examined the challenges of the medical field in relation to big data.
Conclusion: Although obtaining "informed consent" from patients or other stakeholders and "anonymizing" data are still necessary, they are not sufficient in the current situation to meet the challenges arising from big data. The author has also suggested solutions in continuation and in complement to the above solutions; some of the most important of these solutions include the use of differential privacy, conditional consent (case-based), and data transfer. Also, reviewing laws and regulations in terms of providing more severe criminal responses and determining heavier civil liability for privacy violations is another solution |
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| Keywords: Medical Privacy, Big Data, Ethics, Anonymization, Challenge |
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Full-Text [PDF 702 kb]
(57 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2024/02/9 | Accepted: 2024/05/3 | Published: 2025/08/23
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