Next-Generation Sequencing and Artificial Intelligence in Prenatal Down Syndrome Screening: Legal and Regulatory Implications for Health Insurance, Medical Liability, and Genetic Data Protection

Abstract

The integration of Next-Generation Sequencing (NGS) and AI have made Down syndrome prenatal screening earlier, more accurate, and non-invasive. These technologies offer better therapeutic outcomes and less diagnostic uncertainty, but widespread implementation poses difficult legal, ethical, and insurance issues. This research critically investigates how AI-assisted NGS-based prenatal screening affects health insurance coverage, medical and institutional liability, and genetic data protection. Predictive genomic data challenges risk pooling and non-discrimination in insurance legislation, especially when insurers employ prenatal genetic information in underwriting or coverage decisions. The study also examines professional liability, including diagnostic errors caused by algorithmic bias, system failure, or poor human oversight, and AI-driven genomic tool-based clinician and healthcare provider standards of care. The study also discusses GDPR and similar national laws' effects on genetic data privacy, informed consent, data ownership, and cross-border data transfer. This comparative and interdisciplinary study shows that AI-enabled prenatal genetic screening requires strong regulatory safeguards, explicit liability allocation mechanisms, and insurance changes to assure ethical, lawful, and equitable use. The report closes with policy recommendations to balance technological innovation, patient rights, legal accountability, and data security.

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