The rapid integration of virtual health support systems in healthcare has improved patient care but raised concerns about data security and patient privacy. Homomorphic encryption, Virtual health support, Data security, Patient privacy, Healthcare applications, Security mechanisms. This study proposes an algorithm integrating homomorphic encryption, specifically the Paillier cryptosystem, to enhance data security and privacy in virtual health support systems. The algorithm outlines key steps including key generation, data encryption, secure storage, computation on encrypted data, data analysis, secure data sharing, key management, and monitoring. Each step is meticulously designed to ensure patient data remains confidential and secure throughout its lifecycle. An experimental evaluation validates the algorithm’s effectiveness by comparing encrypted and unencrypted data sets across various metrics such as execution times, data size, computation success, and regulatory compliance. Results demonstrate that the proposed technique maintains high levels of data security and privacy while enabling efficient data analysis and secure sharing among authorized parties. The study underscores the algorithm’s scalability for large-scale health systems and its adherence to regulatory standards like HIPAA. Case studies illustrate real-world implementation, affirming practical viability in safeguarding sensitive health data. Future research directions include optimizing computational efficiency and scalability for broader application in healthcare settings. Overall, this work contributes a robust framework for protecting patient information in virtual health environments using advanced encryption techniques.