Insurance Authorization Confidence System
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Solution Overview
Problem
The complexity and frequent updates of insurance approval guidelines make it costly and inefficient for software to accurately determine insurance authorization, leading to high operational costs and insurance denial rates.
Innovation Solution
A system that retrieves and extracts information from authorization requests, identifies relevant guidelines, applies rules in a standardized format to provide a confidence indicator for approval, and presents a submission score, allowing for improved prediction analysis and reduced denial rates by automating the insurance authorization process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If insurance approval guidelines are coded into software to determine authorization, then approval accuracy is improved, but software complexity and operational costs increase prohibitively
Solution Approach 1:
The patent introduces an intermediary component that translates complex insurance approval guidelines into a standardized, machine-readable format. This intermediary layer acts as a mediator between the raw guideline documents and the software processing system, enabling accurate guideline interpretation without requiring the software to directly encode all guideline complexity. The intermediary format serves as a buffer that simplifies the processing while maintaining fidelity to the original guidelines.
Solution Approach 2:
The patent transforms the parameters of guideline representation from unstructured textual formats into a standardized, structured format with defined parameters and data types. This parameter transformation enables software to process guidelines efficiently through automated parsing and validation, reducing computational complexity while maintaining approval accuracy. The standardized format changes the state of guideline data from ambiguous text to precise, machine-interpretable parameters.
2Reliability
If software is updated to reflect guideline revisions, then approval accuracy is maintained, but operational costs and deployment time increase
Solution Approach 1:
The patent implements preliminary action by pre-structuring guidelines into a standardized format that anticipates future revisions. The standardized template design allows guideline updates to be incorporated by simply replacing content within the existing structure rather than redesigning the entire software architecture. This preliminary structuring enables rapid adaptation to guideline changes without requiring comprehensive software re-development and re-deployment.
Solution Approach 2:
The patent introduces dynamic adaptability to the software system through the standardized guideline format, which is designed to accommodate revisions without structural changes. The system can dynamically load and process updated guidelines by parsing them through the established standardized interface, enabling flexible response to changing requirements without rigid, time-consuming software update cycles.
3Manufacturing precision
If comprehensive guideline criteria are applied to authorization requests, then approval quality is improved, but processing time and complexity increase
Solution Approach 1:
The patent replaces manual, mechanical review processes with automated computational processing of standardized guideline criteria. By transforming guidelines into a machine-readable standardized format, the system enables computers to automatically evaluate authorization requests against comprehensive criteria without human intervention. This substitution of mechanical human review with automated digital processing maintains thoroughness while dramatically increasing processing speed and reducing operational complexity.
Data Source
AI summary
A method or system of vetting insurance authorization requests and improving chances of approval can include an application at a server or one or more processors that perform the functions of retrieving and extracting information from an authorization request including a treatment and a diagnosis, identifying treatment guidelines based on the information retrieved and extracted from the authorization request, applying rules that have been converted to a standard format that is human readable to provide a confidence of approval value or indicator, and presenting the confidence value or indicator on a user interface based on the rules applied.