Billing Data Aggregation System Standardizing Procedure Data
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Solution Overview
Problem
Current medical billing systems are complex and time-consuming due to varying requirements from different insurance providers, leading to opacity and unpredictability in payment processes.
Innovation Solution
A method and system that standardize non-standardized procedure data from user devices, parse it into a standard data structure, determine procedure details, calculate cost elements, access a cost database for forecasting, and communicate the cost range back to the user device, utilizing machine learning and database integration for efficient billing data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If medical billing systems process data according to varying requirements from different insurance providers, then billing accuracy is improved, but system complexity and processing time increase
Solution Approach 1:
The patent introduces a standardized data structure as an intermediary layer between the billing system and various insurance providers. This standard structure acts as a mediator that translates diverse insurance requirements into a unified format, allowing the system to maintain billing accuracy for different providers without increasing internal system complexity. The standard structure absorbs the variability in requirements while presenting a consistent interface to the processing system.
2Adaptability or versatility
If medical billing systems handle diverse data formats from multiple sources, then billing comprehensiveness is improved, but processing time increases
Solution Approach 1:
The patent implements preliminary action by pre-defining a standardized data structure that specifies the expected format and organization of billing data. This standard structure is established before processing occurs, allowing the system to quickly validate and transform incoming data without needing to analyze and adapt to each data format in real-time. The preliminary structure enables comprehensive handling of diverse data sources while significantly reducing processing time through predictable data organization.
3Measurement precision
If the system stores detailed billing data for analysis and forecasting, then forecasting accuracy is improved, but memory storage requirements increase
Solution Approach 1:
The patent applies the extraction principle by separating the essential billing data elements into a standardized structure that captures only the necessary information for analysis and forecasting. Rather than storing complete raw data from all sources, the system extracts and stores only the critical fields defined in the standard structure. This approach maintains forecasting accuracy by preserving essential data relationships while significantly reducing memory storage requirements through selective data retention.
Data Source
AI summary
Some implementations of the disclosed systems, apparatus, methods and computer program products are configured for implementing billing data processing systems. Such systems may receive non-standardized data from a plurality of sources and provide for the creation of data for billing and/or forecast from such non-standardized data. The system and techniques described herein aggregates non-standardized data from a plurality of sources to create standardized form modules. Furthermore, the system and techniques described herein allow for forecasting.