Building a Real-Time Claims Analytics Solution to Detect Underpayments
The customer is a U.S.-based healthcare technology company that offers innovative revenue cycle management (RCM) solutions.
The Need
Claims underpayments cost U.S. healthcare providers millions in lost revenue every year. Studies show that healthcare providers lose up to 11% of their net patient revenue due to underpayments. Therefore, as providers prioritize sustainability and operational efficiency, identifying and recovering underpayments has become a top priority. The customer wanted to build an analytical solution that would help their clients (providers) detect and appeal underpaid claims.
The Challenge
High-volume rule processing with rapid response times: The analytics solution had to process a large and diverse set of over 60,000 rules. These rules spanned Medicaid and Medicare fee schedules, payer-specific contracts, and billing compliance standards. The solution had to process these rules and deliver results in just a few seconds.
Real-time, revenue-critical performance
The system was expected to function in real time. Any lag or missed response window could lead to missed revenue opportunities for both the customer and their provider clients.Sophisticated data matching across multiple sources
The platform needed to reconcile claims data, both submitted and adjudicated, against varied state-level pricing structures and payer-specific reimbursement terms. This called for a highly tuned data model and an optimized Extract-Transform-Load (ETL) workflow.
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