Acta Scientifica Malaysia (ASM)

This paper critically examines privacy-preserving consumer-behavior analytics within the expanding landscape of multi-state telemedicine. As digital healthcare platforms increasingly rely on behavioral insights to optimize patient engagement, predict adherence, and personalize care, protecting sensitive health data emerges as both a technical and ethical imperative. The review evaluates three core computational paradigms—differential privacy, k-anonymity, and federated gradient aggregation—assessing their strengths, limitations, and adaptability to fragmented state-level regulatory environments. Differential privacy provides mathematically rigorous safeguards but requires careful calibration of noise mechanisms to preserve analytical fidelity, while k-anonymity offers structured de-identification that is vulnerable to linkage attacks in complex datasets. Federated gradient aggregation demonstrates the strongest potential, enabling decentralized collaboration without compromising jurisdictional data localization, though scalability and heterogeneity remain unresolved challenges. The analysis further highlights the interplay between governance frameworks and technical models, underscoring that regulatory heterogeneity across state lines amplifies compliance burdens and risks undermining patient trust. Emerging hybrid models that combine federated learning with cryptographic protections and fairness-aware AI are presented as pathways toward more equitable and scalable telemedicine ecosystems. Ultimately, the study identifies critical gaps in interoperability, ethical governance, and trust-building, calling for integrated approaches that balance privacy, utility, and patient autonomy. By synthesizing technical, legal, and ethical perspectives, this review provides a structured foundation for advancing privacy-respectful consumer-behavior analytics in telemedicine while informing researchers, policymakers, and providers on the systemic reforms needed to ensure secure and trustworthy digital health futures