Claim Remittance Pattern Analysis for Denial Reduction
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Solution Overview
Problem
Healthcare providers face significant challenges in managing claim submissions and re-submissions due to extensive and burdensome insurance adjudication processes, leading to claim denials and adjustments that result in lost revenue and administrative inefficiencies.
Innovation Solution
A computer-implemented method and system that analyzes large volumes of remittance documents to identify patterns and trends in claim denials, using unique statistical processes to reduce computing load and improve claim submissions by correlating characteristic patterns with adjudication outcomes, thereby reducing claim denials and adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking and analysis of claim denials is performed by medical billers, then claim submission accuracy can be improved, but the administrative workload and time required to process large volumes of claims becomes prohibitively difficult
Solution Approach 1:
The patent replaces manual mechanical tracking and analysis of claim denials with an automated computer-based system that uses statistical processes and pattern recognition algorithms to analyze remittance documents, identify denial patterns, and generate actionable insights, thereby eliminating the need for manual processing while maintaining or improving accuracy
Solution Approach 2:
The patent introduces an intermediary automated analysis system that acts as a bridge between raw remittance data and decision-making processes, using statistical models and pattern recognition to transform unstructured denial information into structured, actionable intelligence that guides claim submission improvements
2Measurement precision
If comprehensive analysis of all remittance documents is performed to identify denial patterns, then claim submission accuracy improves, but the computing load and processing time increase significantly
Solution Approach 1:
The patent extracts only the most relevant and significant features from remittance documents using statistical process selection, identifying and focusing on key denial patterns and characteristics while discarding redundant or less important data elements, thereby reducing computing requirements while maintaining analytical accuracy
Solution Approach 2:
The patent segments the large-scale analysis problem into smaller, manageable statistical processes that can be executed independently and in parallel, breaking down the complex task of analyzing millions of remittance records into discrete analytical steps that reduce overall computing load and enable efficient processing
3Device complexity
If claim denials are not addressed systematically, then administrative processes remain simple, but revenue loss from adjustments and denials increases substantially
Solution Approach 1:
The patent implements a feedback mechanism where analyzed denial patterns and statistical insights are fed back into the claim submission process, enabling continuous improvement of claim accuracy and systematic addressing of recurring denial issues, thereby reducing revenue loss while maintaining manageable process complexity
Solution Approach 2:
The patent performs preliminary analysis of remittance documents and identifies potential denial patterns before they result in revenue loss, enabling proactive adjustments to claim submissions and preventive measures that address systemic issues before they cause substantial financial impact
Data Source
AI summary
An apparatus and method for processing records associated with adjudication decisions that include: obtaining records associated with respective adjudication decisions; proceeding, starting with factors in the obtained records and in an iterative or recursive manner, to: determine a number of factors for evaluating the obtained records, select the determined number factors from plural factors comprised in the obtained records, identify a subset of records described by the selected factors, record the identified subset of records in association with the selected factors as a factor set to a data storage, and remove the subset of records from the obtained records for a next iteration until the obtained plurality of records have been all removed; and outputting factor sets and associated subsets of records from the data storage for displaying factor sets and associated subsets of records in correspondence with one or more adjudication decisions comprised in the associated subsets of records.


