Patient Privacy and Data Security in the Era of AI-Driven Healthcare
Siddhi Gawankar, Saranya Nair, Vilis Pawar, Abhijit Vhatkar, Pravin Chavan
Abstract
As artificial intelligence (AI) becomes increasingly integrated into healthcare systems, concerns about patient privacy and data security have become paramount. This paper examines the implications of AI-driven technologies on patient privacy and data security, focusing on theoretical frameworks and practical approaches to mitigate risks and enhance protections. Through a comprehensive literature review, theoretical models, and ethical analyses, this study suggests ‘Integrated Security and Ethics Model.’ This framework addresses the dynamic nature of AI, the integration of ethical considerations into security practices, and the need for comprehensive governance and risk management strategies. The findings highlight the importance of balancing the benefits of AI in healthcare with the protection of patient privacy and data security. The proposed framework offers actionable guidance for policymakers, healthcare providers, and AI developers to ensure that AI technologies are implemented responsibly and ethically. Future research directions, policy implications, and practical recommendations are also discussed. This study contributes to advancing the understanding of patient privacy and data security in the context of AI-driven healthcare, aiming to foster a safer and more ethical AI ecosystem in healthcare settings.