Towards robust electronic health record systems: integrating formal verification and process modeling techniques.

The integration of complex software systems such as clinical decision aid platforms and electronic health records (EHR) has substantially improved human healthcare support by enhancing diagnostic accuracy and optimizing medical workflows. Developing these systems requires meticulous processes including requirement specification, design, implementation, testing, and deployment. While numerous approaches exist for system development, formal verification through modeling has become crucial for ensuring system reliability and security. In this research, an approach based on Hierarchical Colored Petri-Nets (HCP-Nets) for process modeling and formal verification to develop an EHR system is proposed that is accurate, complete, and consistent. The World Health Organization (WHO) emphasizes integrating modern computing techniques such as data mining and machine learning into health systems in the context of viral disease outbreaks and the need for robust public health surveillance. There is a critical need for process mining and formal verification-based systems to improve data sharing and system integration in regions like Pakistan, where healthcare infrastructure and interoperability are limited. This research addresses key gaps in EHR systems including platform effectiveness, data storage consistency, data accuracy, completeness, and security against unauthorized access. The findings suggest that formal verification using HCP-Nets with model checking and process mining can greatly enhance the reliability and security of EHR systems with an accuracy of 80 5%, providing a strong foundation to advance health informatics and supporting better health outcomes in complex and diverse environments.