Predictive Model Routing for Pharmacy Claims Processing
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Solution Overview
Problem
Processing large volumes of pharmacy claims is computationally intensive and time-consuming, requiring efficient methods to optimize claim processing.
Innovation Solution
A predictive model is used to guide health claims processing by prioritizing claims for processing through either a real-time adjudication system or a cloud-based statistical model, optimizing the use of resources and improving processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all pharmacy claims are processed through a real-time adjudication system, then processing accuracy is maintained, but processing time increases and system resources are overwhelmed
Solution Approach 1:
The patent segments the claims processing workload into two distinct pathways: a real-time adjudication system for complex or high-risk claims, and a cloud-based statistical model for routine, low-risk claims. This segmentation allows each system to handle the type of claims it is best suited for, maintaining accuracy where needed while reducing processing time for standard claims.
Solution Approach 2:
The patent introduces a predictive model as an intermediary that evaluates claims before routing them to appropriate processing systems. This intermediary assesses claim characteristics and determines whether a claim should be handled by the real-time adjudication system or the cloud-based statistical model, optimizing resource allocation and processing efficiency.
2Productivity
If a dual-system approach is implemented with a predictive model, then processing efficiency improves, but system complexity increases
Solution Approach 1:
The patent creates a universal processing framework that can handle both real-time adjudication and cloud-based statistical modeling through a single predictive model interface. The system maintains multiple processing pathways but unifies them under a common routing logic, allowing the same infrastructure to serve multiple processing needs without requiring entirely separate systems.
Solution Approach 2:
The patent uses cloud-based statistical models as a simplified copy or alternative representation of the full real-time adjudication system. Rather than replicating the entire complex adjudication infrastructure in the cloud, the system creates a streamlined statistical version that handles routine claims, reserving the full real-time system for cases requiring its complete functionality.
3Use of energy by moving object
If cloud-based statistical models are used for routine claims, then resource utilization optimizes, but processing complexity for individual claims increases
Solution Approach 1:
The patent replaces the mechanical real-time adjudication system with a cloud-based statistical model for handling routine claims. This substitution uses computational algorithms and statistical methods instead of traditional rule-based processing, reducing the load on real-time system resources while maintaining efficient processing of standard claims through automated statistical evaluation.
Data Source
AI summary
Systems and methods herein describe probability-based health claims processing. The described systems and methods access a plurality of pharmacy claims, determine an aggregate rating of the pharmacy claims based on pharmacy claims data, submit a first subset of pharmacy claims to a first pharmacy claims approval system, submit a second subset of pharmacy claims of the plurality of pharmacy claims to a second pharmacy claims approval system, receive, from the first pharmacy claims approval system, a first set of decisions for the first subset of pharmacy claims, and, receive from the second pharmacy claims approval system, a second set of decisions for the second subset of pharmacy claims.