Algorithmic Healthcare and Legal Accountability: Patient Rights, Data Protection, and the Intersection with Digital Forensic Evidence

The rapid integration of artificial intelligence (AI) and algorithmic decision-making into healthcare systems has fundamentally transformed medical practice, raising complex questions of legal accountability and patient protection. This research critically examines the intersection of algorithmic healthcare with medical jurisprudence, focusing on patient rights, informed consent, and data protection within increasingly digitized clinical environments. It explores how AI-driven diagnostic and treatment tools challenge traditional standards of medical negligence, duty of care, and professional liability, particularly when decision-making is partially or wholly delegated to automated systems. From a legal perspective, the paper analyses the adequacy of existing regulatory frameworks in safeguarding patient autonomy and ensuring meaningful informed consent in the context of opaque “black-box” algorithms. It further evaluates data protection concerns arising from the extensive collection, processing, and sharing of sensitive health data, emphasizing the risks of misuse, breaches, and surveillance. In addition, the study investigates the growing role of digital forensic evidence in both civil and criminal proceedings involving medical technologies. It highlights evidentiary challenges relating to the admissibility, reliability, and authenticity of algorithm-generated outputs and electronic health records. The article argues for a robust, adaptive legal framework that integrates principles of transparency, accountability, and technological due diligence. It concludes by proposing reforms to harmonize healthcare innovation with constitutional protections, ensuring that technological advancement does not undermine fundamental patient rights and the integrity of the justice system.