EMR Parser and Dispatch Engine for Clinical Decision Support
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Solution Overview
Problem
The challenge in using electronic medical records (EMR) for real-time clinical decision support is hindered by manual data entry errors and delays, which lead to incomplete or delayed information, impacting the reliability and usability of clinical decision support systems.
Innovation Solution
An EMR management system that includes an electronic medical record parser and dispatch engine to determine if supplemental data entry is needed and notify care providers through a user interface, using frequency-based, active application-based, or algorithm-based triggering techniques to ensure timely and accurate data entry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual data entry is used in EMR systems, then flexibility and ease of operation are improved, but data entry errors and delays increase
Solution Approach 1:
The system implements automated feedback mechanisms where the CDS application monitors EMR data completeness and quality in real-time, and automatically notifies care providers when data is missing or erroneous. This closed-loop feedback system maintains manual entry flexibility while improving data reliability through systematic validation and provider alerting.
Solution Approach 2:
The system enables self-service by allowing the CDS application to autonomously parse EMR data, identify missing information, and generate notifications without requiring manual intervention. The automated data parsing and notification generation reduce human error while maintaining operational flexibility.
2Adaptability or versatility
If manual data entry is used in EMR systems, then adaptability to different clinical workflows is improved, but data entry delays increase
Solution Approach 1:
The system performs preliminary actions by proactively monitoring and parsing EMR data as it becomes available, identifying missing information before it impacts CDS functionality. The automated notification system alerts providers in advance, allowing timely data completion without disrupting clinical workflows.
Solution Approach 2:
The system ensures continuous monitoring and parsing of EMR data throughout the clinical workflow, maintaining constant awareness of data completeness. This continuous action eliminates gaps in data collection while preserving workflow flexibility, as the system operates continuously without requiring manual initiation.
3Productivity
If automated data parsing is implemented, then data entry speed and accuracy are improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary automated parsing layer between the EMR database and the CDS application. This intermediary component handles the complexity of data extraction, validation, and notification generation, allowing the core CDS functionality to remain simple while achieving high processing speed and accuracy through automated intermediate processing.
Data Source
AI summary
Systems, apparatuses and methods provide for the management of electronic medical records (EMR) for clinical decision support (CDS) applications. For example, an apparatus (100) is configured to parse an EMR database (102), determine whether supplemental entry of current patient data is needed based on existing patient data in the EMR database, and transfer a notification that the supplemental entry of the current patient data is needed to a user interface (126) associated with a care provider.