Concurrent Automated Referral Transmission for EHR Interoperability
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Solution Overview
Problem
Current referral systems in healthcare lack real-time, concurrent information transmission capabilities, leading to inefficiencies, errors, and fragmented patient data exchange due to manual processes and interoperability issues between different electronic health record systems.
Innovation Solution
An automated referral system that integrates user input modules, filtering, dynamic threshold adjustment, and secure authentication to streamline referral processes, ensuring seamless data transmission and accurate, relevant results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual handling of referral forms and patient records is used, then system complexity is reduced, but productivity decreases and errors increase
Solution Approach 1:
The patent replaces manual mechanical processes (paper forms, manual data entry, physical record handling) with an automated electronic system that uses software algorithms to extract, validate, and transmit referral data. This substitution dramatically increases productivity while the system manages complexity through modular architecture and standardized interfaces.
Solution Approach 2:
The system enables self-service by automatically extracting patient data from source systems, populating referral forms, and transmitting information without requiring manual intervention. The automated data extraction and validation processes allow the system to serve itself, reducing human workload and increasing processing speed.
2Reliability
If real-time concurrent information transmission is implemented, but manual processes are used, then information availability improves, but reliability decreases due to human error
Solution Approach 1:
The patent replaces manual data entry and verification processes with automated electronic data extraction and validation. This substitution eliminates human errors in data transcription while maintaining high automation levels, thereby improving both reliability and the extent of automation simultaneously.
Solution Approach 2:
The system implements automated validation rules and error checking mechanisms that provide immediate feedback on data quality. This feedback loop ensures data accuracy by catching errors automatically rather than relying on manual verification, thereby improving reliability while maintaining high automation.
3Adaptability or versatility
If seamless integration with multiple EHR systems is achieved, then adaptability improves, but device complexity increases
Solution Approach 1:
The patent implements a universal integration layer that can connect to multiple different EHR systems through standardized interfaces. This multi-functional approach allows the same core system to adapt to various source systems without requiring custom development for each, thereby improving interoperability while managing integration complexity through standardization.
Solution Approach 2:
The system introduces an intermediary integration layer that mediates between different EHR systems and the referral processing core. This intermediary handles the complexity of multiple system interfaces, allowing the core system to remain simple while achieving high adaptability through the mediating layer that manages diverse connections.
4Manufacturing precision
If automated data extraction and validation are implemented, then manufacturing precision improves, but loss of time decreases (process takes longer)
Solution Approach 1:
The system performs preliminary actions by pre-configuring validation rules, data extraction templates, and error checking mechanisms before the actual referral processing occurs. This preliminary setup enables rapid automated processing with high accuracy, as the framework is already in place rather than being created during each processing cycle.
Data Source
AI summary
An automated referral system and method for generating and managing referrals. The system receives user criteria and identifies relevant search results. It then generates and transmits referral requests to recipients corresponding to the search results. The system performs two-factor authentication before transmitting requests. Read receipts are received from recipients acknowledging the referral requests. The system then displays a subset of the search results to the user, based on which recipients have acknowledged the requests via read receipts. The display may include an interactive map showing locations of the results. This method enhances reliability and user trust in the referral process by incorporating confirmation steps and secure authentication while providing a user-friendly interface for reviewing curated search results.