Medical Information Navigation Engine for Health Data Reconciliation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The healthcare industry faces challenges in reconciling and managing healthcare information due to disparities in coding systems and sources, making it difficult to determine the appropriate action for patient care.
Innovation Solution
A method and system for optimizing and routing healthcare information through a medical information navigation engine (MINE) that translates, augments, filters, and reconciles data, using wiki-based crowd-sourced quality control to ensure reliable and actionable information for healthcare providers and patients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If healthcare information from multiple sources with different coding systems is aggregated, then the quantity and diversity of information increases, but the reliability and usability of the information decreases due to coding disparities and reconciliation difficulties
Solution Approach 1:
The patent introduces a medical information navigation engine (MINE) as an intermediary system between multiple healthcare information sources and users. The MINE performs translation, augmentation, filtering, and optimization of health information from various coding systems (ICD-9, ICD-10, CPT, HCPCS, etc.) into standardized, reliable formats. This intermediary reconciles coding disparities by mapping different codes to unified representations, thereby maintaining reliability while aggregating diverse information sources.
2Reliability
If manual reconciliation of healthcare information from multiple sources is performed, then the accuracy and reliability of information improves, but the time and resources required increase significantly
Solution Approach 1:
The patent replaces manual mechanical reconciliation processes with an automated computer-based MINE system. The engine automatically performs translation of coding systems, augmentation of information, filtering of irrelevant data, and optimization of information quality. This automated system eliminates the need for manual review and reconciliation by healthcare providers, significantly reducing time consumption while maintaining or improving accuracy through systematic algorithms and crowd-sourced validation.
Solution Approach 2:
The patent implements crowd-sourced quality control mechanisms where multiple users can contribute to validating and improving the accuracy of health information translations and reconciliations. This feedback loop allows the system to learn from collective expertise, continuously improving the reliability of information processing while maintaining automated efficiency. The crowd-sourced approach distributes the validation workload, preventing bottlenecks associated with single-point manual review.
3Ease of operation
If health information is standardized and optimized through translation and filtering, then the usability and actionability of information improves, but the complexity of the processing system increases
Solution Approach 1:
The patent designs the MINE as a universal, multi-functional system that handles multiple coding systems (ICD-9, ICD-10, CPT, HCPCS, etc.), performs multiple operations (translation, augmentation, filtering, optimization), and serves various users (healthcare providers, patients, researchers). By consolidating these diverse functions into a single platform, the system manages complexity internally while presenting a simplified, standardized interface to users. The universal design allows the same core engine to handle different coding systems and information types without requiring separate processing systems for each function.
Data Source
AI summary
A method is disclosed to receive health information request (HIR), including health information request query (HIRQ) and health information request data (HIRD), and to metatag the received HIR. The metatagged HIR is reconciled based on a semantic concept and HIRS is returned.