Medical Information Navigation Engine for Clinical Knowledge Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The medical field faces challenges with unreliable and unconsolidated medical information, leading to inefficiencies and poor quality of care, as existing systems do not effectively tie payoffs to the outcomes of medical encounters, incentivizing providers to prioritize quantity over quality.
Innovation Solution
A Medical Information Navigation Engine (MINE) that extracts and processes clinical knowledge to compare actual patient encounters with optimal encounters, calculating payoffs based on reimbursement potential and optimizing coded elements for improved care efficiency and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If medical information is consolidated and managed through a centralized system, then reliability and accessibility of medical information improve, but system complexity increases
Solution Approach 1:
The patent introduces a Medical Information Navigation Engine (MINE) as an intermediary system that sits between multiple medical information sources and users. The MINE consolidates information from electronic health records, claims data, and other sources, processes it through standardized protocols, and presents it in a unified manner. This intermediary approach improves reliability without requiring complete system integration, as the MINE can operate independently while managing the complexity of information consolidation.
2Manufacturing precision
If payoffs are tied to outcome-based metrics, then care quality improves, but measurement and tracking complexity increases
Solution Approach 1:
The system implements feedback loops by continuously monitoring patient outcomes and comparing them against expected outcomes based on clinical guidelines and historical data. The MINE tracks encounter outcomes, calculates performance metrics, and provides feedback to providers about their care quality. This automated feedback mechanism enables outcome-based payoff structures without manual measurement, reducing tracking complexity while improving care quality through data-driven insights.
Solution Approach 2:
The patent transforms complex quality of care assessments into standardized, quantifiable parameters that can be automatically measured and tracked. By defining specific outcome metrics and using standardized coding systems, the system converts subjective quality assessments into objective parameters suitable for automated calculation and comparison, thereby simplifying the measurement process while maintaining precision.
3Measurement precision
If comprehensive clinical knowledge is extracted and processed, then reimbursement accuracy improves, but data processing time increases
Solution Approach 1:
The system performs preliminary processing of clinical information by pre-extracting and structuring data from electronic health records and other sources before reimbursement processing is needed. The MINE continuously analyzes clinical documentation, identifies relevant coded elements, and prepares reimbursement data in advance. This preliminary action ensures high reimbursement accuracy when needed while distributing processing workload over time, reducing peak processing times.
Data Source
AI summary
A computerized Medical Information Navigation Engine (“MINE”) extracts clinical knowledge, by identifying coded elements with reimbursement potential contributing to payoff based on clinical history, and subtracting coded elements documented in an encounter from the coded elements, based on business logic. The MINE sorts the remaining coded elements in accordance with one optimization criteria to payoff based on clinical history.