|Peer Reviewed, Refereed & Open Access Journal | Follows UGC CARE Journal Norms and Guidelines|
|ISSN 2349-6037|Approved by ISSN, NSL & NISCAIR| Impact Factor: 9.274 |ESTD:2013|
|Scholarly Open Access Journal, Peer-Reviewed, and Refereed Journals, Impact factor 9.274 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Multidisciplinary, Quarterly, Citation Generator, Digital Object Identifier(DOI)|
| TITLE | Accelerating Claims Processing with Observability and Automated Dashboards |
|---|---|
| ABSTRACT | MCE for HealthCare is an environment for building blocks to adjudicate medical claims within provider and payer settings. MCE is architected to adjudicate claim input, data validation, eligibility validation, benefits rule adjudication, post-processing (payment and remittance), analytics, and reporting. MCE replaces traditional mainframe processing with cloud-based, observable, and analytics-driven infrastructure to support rapid adjudication, improved data quality, and open financial operations. The MCE is augmented by the Observability Framework, a telemetry that aggregates metrics, logs, and traces end-to-end across the data path. Real-time monitor dashboards provide throughput, error rate, end-to-end latency, and SLA compliance. Distributed tracing monitors cross-service call patterns to identify bottlenecks and points of failure. Centralized log and analysis support microservices, streaming pipeline, and mainframe replications' events correlation for performance tuning and root-cause analysis. Data elements are correlated to the observability model such as ingestion and validation, adjudication engine, payment and post-processing, and analytics layer. This enables stakeholders to monitor processing performance, straighten out real-time errors, and uphold data privacy and healthcare rule compliance. MCE, together with an observability pattern, delivers data-driven capability, operational resilience, and end-to-end visibility to facilitate industry transformation to cloud-native, observable, and AI-enabled claim processes. |
| AUTHOR | Murugan Ambalakannu Director Consulting Services, CGI, USA |
| PUBLICATION DATE | 2025-11-19 19:18:55 |
| VOLUME | 13 |
| ISSUE | 2 |
| DOI | DOI: 10.15662/IJMSERH.2025.1302079 |
| pdf/2025/4/79_Accelerating Claims Processing with Observability and Automated Dashboards.pdf | |
| KEYWORDS |
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