Biometric technology in healthcare: Balancing security benefits with implementation challenges
Year: 2025
Type: article
Abstract: Biometric technology represents a transformative approach to securing electronic health records (EHRs) in an increasingly digitized healthcare landscape. As healthcare data breaches continue to rise dramatically—with 712 major incidents affecting over 87 million patient records in 2023 alone—traditional password-based authentication methods have proven inadequate in protecting sensitive patient information. This comprehensive examination explores the multifaceted implications of integrating biometric authentication in healthcare environments, revealing both promising advantages and significant challenges. Biometric solutions utilizing fingerprints, facial recognition, iris patterns, and voice recognition demonstrate substantially improved security metrics compared to conventional methods, with unauthorized access reductions of up to 68% and dramatically enhanced audit capabilities. Implementation data indicates significant workflow efficiency gains, with authentication time reduced by over 60% and substantial decreases in patient misidentification errors. However, these benefits must be balanced against environmental sensitivity issues in clinical settings, complex regulatory compliance requirements, and substantial implementation costs. Through systematic evaluation of implementation experiences across diverse healthcare facilities, this article identifies critical success factors for effective biometric integration, including thorough pre-implementation assessments, phased deployment approaches, multi-modal solutions, and comprehensive stakeholder engagement. The findings suggest that strategic implementation of biometric authentication can significantly enhance healthcare security while improving operational efficiency, provided organizations carefully navigate the technical, regulatory, and organizational challenges inherent in this technological transition.
Author: Meegada, Sreenivasul Reddy
Institution: Jawaharlal Nehru Technological University, Hyderabad
Language: English
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7083804968
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