DOI: 10.36347/sjmcr.2018.v06i12.025

Pages: 1087-1099

As artificial intelligence systems increasingly mediate clinical decision-making, ensuring their legal accountability and ethical integrity becomes critical. Traditional DevOps pipelines, though optimized for efficiency and continuous integration, lack embedded mechanisms for privacy enforcement, jurisdictional compliance, and traceability, features that are non-negotiable in healthcare settings. This paper introduces HealthDevOps, a re-engineered system architecture that integrates legal and ethical requirements directly into the AI lifecycle. Through layered system design, modular legal logic, and dynamic consent protocols, HealthDevOps operationalizes accountability, transforming compliance from an external audit task into an intrinsic system function. Drawing on foundational legal and philosophical critiques, the framework is positioned not merely as a technical innovation but as a normative shift in how healthcare AI should be built and deployed. A detailed conceptual and architectural analysis illustrates how HealthDevOps adapts across jurisdictions, enforces explainability, and preserves clinical oversight. By reframing responsibility as a coded process, HealthDevOps offers a scalable, transparent, and enforceable path toward ethically and legally compliant AI deployment in healthcare.