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Automating CMS Part C Reporting: A Strategic Approach to Medicare Advantage Compliance
Abstract
This article addresses the evolving challenges faced by Medicare Advantage Organizations (MAOs) in meeting the increasingly complex CMS Part C reporting requirements. As Medicare Advantage enrollment continues to expand rapidly, health plans face mounting pressure to accurately report performance and operational metrics across multiple domains, including Utilization Management, Grievances and Appeals, Organization Determinations, Special Needs Plan Care Management, Enrollment/Disenrollment, and Benefits/Cost-Sharing. Traditional reporting methods, characterized by manual data extraction from disparate systems, create significant challenges related to data inconsistency, administrative burden, delayed submissions, inadequate audit trails, and limited scalability. The article presents a comprehensive technological framework for automating CMS Part C reporting, detailing essential components such as data integration infrastructure, standardization engines, workflow management, regulatory rules repositories, documentation capabilities, analytics dashboards, and secure cloud architecture. Implementation strategies emphasize phased approaches, cross-functional governance, process standardization before automation, data quality programs, rigorous testing protocols, staff role evolution, and continuous improvement mechanisms. The evidence demonstrates that automation yields substantial benefits, including operational efficiency gains, improved submission quality, enhanced audit readiness, cost-effective scalability, positive impact on quality metrics, and significant financial returns. Through careful implementation of automation technologies and appropriate change management strategies, Medicare Advantage plans can transform regulatory reporting from a resource-intensive burden into a strategic asset that enhances compliance, efficiency, and ultimately, the quality of care delivered to beneficiaries.
Article information
Journal
Journal of Computer Science and Technology Studies
Volume (Issue)
7 (6)
Pages
725-733
Published
Copyright
Open access

This work is licensed under a Creative Commons Attribution 4.0 International License.