Affiliation:
1. Symbiosis Institute of Health Sciences, Symbiosis International University (Deemed), Pune, India
Abstract
The integration of AI into EMR systems is reshaping healthcare, offering potential improvements in patient care, clinical decision-making, and administrative processes. This chapter delves into AI's multifaceted role within EMRs and its significant impact on patient privacy. While AI streamlines data management as healthcare embraces digital record-keeping, it also raises concerns regarding data security, confidentiality, and ethical considerations. The chapter examines the intricate interplay between AI, EMRs, and patient privacy, highlighting both challenges and opportunities. EMRs are pivotal in modern healthcare, housing diverse patient data. To safeguard privacy, robust data encryption, strict access controls, and anonymization are essential. Ensuring the security of sensitive patient data is vital for successful AI implementation. Innovative technologies like blockchain and attribute-based access control offer promising solutions, yet the delicate balance between data privacy and utility remains a significant hurdle in the evolving field of AI-driven healthcare.