Abstract
The healthcare industry is increasingly under financial pressure due to high rates of claims denials, leading to substantial revenue loss and operational inefficiencies. Claims denials result from various factors, including coding errors, incomplete documentation, and regulatory non-compliance, all of which contribute to revenue leakage that often reaches 5–10% annually for healthcare providers. This paper explores a proprietary Software-as-a-Service (SaaS) solution that leverages data analytics, machine learning, and real-time reporting to enhance the claims denial management process. Through predictive and prescriptive analytics, the proposed solution enables healthcare providers to identify denial trends, reduce denial rates, optimize claims resolution, and increase revenue retention. The paper includes system architecture, data security protocols, pilot implementation findings, and a comparative analysis of performance metrics. The paper concludes with a discussion on future developments, including real- time denial prediction, automated appeals generation, and enhanced integration capabilities with existing Electronic Health Record (EHR) systems. Keywords: Revenue Cycle Management, healthcare claims denial, claim under payment, SaaS, data analytics, machine learning, real-time reporting, financial sustainability, healthcare providers
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