Quantum Machine Learning–Empowered Serverless Cloud Framework for Healthcare ERP Systems AI-Driven Business Rule Automation and Decision Intelligence
DOI:
https://doi.org/10.15662/IJEETR.2022.0406003Keywords:
quantum machine learning, serverless cloud, healthcare ERP, business rule automation, decision intelligence, predictive analytics, hybrid quantum-classicalAbstract
This paper proposes a novel framework: a quantum-machine-learning-empowered serverless cloud architecture for healthcare Enterprise Resource Planning (ERP) systems aimed at automating business rules and enhancing decision intelligence. By combining quantum-machine-learning (QML) techniques, serverless cloud infrastructure, and domain-specific business rule automation, this framework targets healthcare ERP systems that must integrate administrative, clinical and operational workflows with heavy regulatory, privacy and real-time constraints. The proposed approach embeds QML modules for predictive and prescriptive analytics (e.g., patient flow, resource allocation, supply chain optimization) within a serverless cloud backend that scales elastically. It also supports a business-rule engine layer where business rules (such as billing validations, regulatory compliance logic, clinical-administrative handoffs) are encoded, triggered and evolved based on QML insights. Through this architecture, the ERP becomes a decision-intelligent platform rather than simply a data repository. The key contributions are (1) design of the hybrid quantum-classical pipeline and cloud integration for healthcare ERP, (2) description of how business rule automation links to QML decision modules to produce actionable outcomes, and (3) discussion of advantages, challenges, results from a simulated pilot study, and future directions. Early simulation results show improved decision-making speed, better resource utilization and enhanced rule compliance compared to classical-only baselines. The findings suggest that coupling QML with serverless cloud ERP systems offers a promising pathway for next-generation healthcare operations.
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