Automating CMS Reporting for Medicaid and Medicare Using Data Engineering Pipelines
DOI:
https://doi.org/10.63282/3117-5481/AIJCST-V3I5P104Keywords:
CMS Reporting, Medicaid, Medicare, Data Engineering Pipelines, ETL, Healthcare Data Integration, Cloud Computing, Data Automation, Regulatory Compliance, Data Validation, Anomaly Detection, Workflow Orchestration, Real-Time Reporting, Fraud Detection, Predictive Analytics, Healthcare InteroperabilityAbstract
This study focuses on improving CMS (Centers for Medicare & Medicaid Services) reporting through automated data engineering pipelines. Traditional reporting methods are often manual, time-consuming, and prone to errors. By using ETL (Extract–Transform–Load) frameworks, cloud technologies, and interoperability standards, healthcare data from multiple sources can be integrated, standardized, and processed efficiently. The automated system supports data validation, anomaly detection, and workflow management, which improves reporting accuracy, compliance, and audit readiness while reducing administrative effort. It also enables real-time reporting and better use of Medicare claims data for applications like fraud detection and risk prediction. Overall, data engineering pipelines help make CMS reporting more scalable, reliable, and efficient.
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