Scalable Data Architecture for Health Insurance Exchanges Supporting ACA Compliance

Abstract

Exchanges for health insurance are an area of immense digital-enabled transformation, thereby facilitating comparison, choosing, and joining an eligible health plan, along with the determination of eligibility for any financial aid schemes. The system's design resolves complex challenges involving not only aspects concerning regulation with the principles of data security and privacy, but also scalability, dealing with high volumes in terms of health insurance enrollments at certain times of the year, interfacing with third-party verification services, and designing better usability for different groups of people. The complete data governance structure defines data safeguards related to any identifiable data, generation of audit trails, data sharing models involving more than one party, along with preserving transparency and managing user consent processes. The technical solutions in these systems adopt microservice design principles to provide autonomous scalability to the different parts of the technology framework, polyglot design patterns enabling specific data storage solutions based on characteristics related to data types, along with advanced data security solutions involving encryption, two-factor authentication, and ongoing threat detection processes. Techniques used for performance improvement incorporate load balancing, caching, database sharding, and auto-scaling solutions to remain responsive to sudden high volumes in terms of health insurance applicant traffic. The advancing technologies on this front include cloud-enabled systems design, artificial intelligence solutions involving processes related to health insurance fraud analysis and health insurance user support systems, ecosystem compatibility solutions to easily merge with any health ecosystem, along with blockchain solutions facilitating health insurance transaction record systems to remain resistant to any form of alteration.