Claim Editing Engine Automates Data Integration and Error Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Complex data processing systems, such as those in medical and insurance claim centers, face challenges in updating and processing hundreds or thousands of interrelated data records, often stored in disparate formats and systems, leading to errors and inefficiencies due to manual intervention and lack of centralized record management.
Innovation Solution
A claim editing system with a data warehouse and a claim editing engine that extracts, transforms, and integrates claim components into unified claims, applies a rule set to simulate execution and identify errors, and transmits instructions for error resolution, enabling automated integration and error resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual intervention is used to process claims, then flexibility and adaptability are maintained, but processing speed and productivity decrease
Solution Approach 1:
The system enables self-service through automated claim processing where the computer system independently extracts data from unstructured text, validates information against medical knowledge bases, and updates electronic health records without human intervention. The processor automatically performs validation rules and error detection, allowing the system to service itself rather than requiring manual processing at each step.
Solution Approach 2:
Manual mechanical processing by human operators is replaced with automated computational processes. The system uses natural language processing algorithms, validation rules, and computer-based data extraction to substitute the mechanical actions of manual data entry, verification, and record updating, thereby increasing processing speed while maintaining accuracy through systematic automated validation.
2Reliability
If data records are stored in disparate formats and systems, then system flexibility is maintained, but data integration accuracy and reliability decrease
Solution Approach 1:
The system implements a universal data extraction and validation framework that can handle multiple data formats and sources through a single integrated process. The processor uses standardized validation rules and medical knowledge bases that work across different data structures, allowing one system to universally process claims from various payers, providers, and formats without requiring separate processing paths for each data type.
Solution Approach 2:
The system introduces an intermediary validation layer between disparate data sources and the electronic health record system. This intermediary processor extracts data from unstructured text, validates it against standardized medical knowledge bases and validation rules, and transforms it into a consistent format before updating the EHR, thereby mediating between heterogeneous data formats and ensuring integration accuracy.
3Duration of action of moving object
If linear manual processing is used, then processing thoroughness is maintained, but time sensitivity and processing duration worsen
Solution Approach 1:
The system implements continuous automated processing where claims are extracted, validated, and updated in an uninterrupted sequence without manual handoffs. The processor continuously applies validation rules, checks medical knowledge bases, and updates records in real-time as claims are received, eliminating the discontinuous nature of manual batch processing and maintaining thorough validation while significantly reducing overall processing time.
Solution Approach 2:
The system performs preliminary data extraction and validation before claims require manual review or processing. By pre-extracting data from unstructured text and pre-validating against medical knowledge bases, the system prepares claims in advance, reducing the time required for subsequent processing steps and enabling faster response to time-sensitive claims while maintaining thoroughness through preliminary validation.
4Productivity
If automated processing is implemented, then processing speed increases, but error detection capability and measurement precision may decrease
Solution Approach 1:
The system implements feedback loops where validation results are continuously checked against medical knowledge bases and error patterns. When validation rules identify potential errors, the system cross-references with established medical guidelines and previously detected error patterns to confirm accuracy. This feedback mechanism ensures that automated error detection maintains high precision by continuously validating against authoritative medical sources and learning from detected error patterns.
Solution Approach 2:
The system performs preliminary validation and error detection using established medical knowledge bases and validation rules before claims are finalized. By pre-checking extracted data against medical standards, provider credentials, and historical error patterns, the system detects errors early in the automated process, maintaining high detection accuracy while enabling rapid processing of claims that pass validation without requiring manual review.
Data Source
AI summary
A claim editing engine for automated integration and error resolution of claim records is provided. The processor of the engine is configured to extract a set of claim components of a plurality of claim components. The processor is further configured to transform the set of claim components to conform to a standardized data format. The processor is also configured to integrate the set of transformed claim components into a set of unified claims by unifying each of the set of transformed claim components having matching claim identifiers into a unified claim. The processor is configured to apply a rule set to the set of unified claims to generate a simulation of execution of the set of claims and identify errors in the simulated execution. The processor is configured to transmit an instruction to resolve each identified error. The processor is configured to cause each resolved unified claim to be processed.