In the contemporary digital era, the storage of Electronic Health Records on open platforms presents significant security and privacy challenges. Addressing these concerns requires standardizing the clinical deployment models currently in use. This paper proposes a robust model that overcomes critical issues related to security, privacy, access control, and ownership transfer of patients' records. The model incorporates data collection to assess clinical needs, followed by deployment-level checks to mitigate network attacks and enhance Quality-of-Service according to scalability demands. A Modified Genetic Algorithm is employed to improve blockchain scalability. The model also introduces mechanisms for ensuring database integrity, mitigating external attacks, and enhancing usability. It further supports platform-level modularization, access control, department-specific configurations, and patient-level confidentiality. The proposed solution outperforms existing systems, particularly in terms of ease of use, deployment delay, deployment complexity, and module-level efficiency, making it a highly suitable option for implementing secure, customized clinic security systems based on Electronic Health Records.