ICU Telemedicine EMR Data Translation via Local Rule Decoding
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Solution Overview
Problem
The integration of ICU telemedicine systems is hindered by the need for compatible software in both ICU units and remote command centers, which can be costly and inefficient due to the variety of incompatible electronic medical record (EMR) systems, requiring time-consuming and expensive translation software to ensure consistent data interpretation.
Innovation Solution
The solution involves downloading clinical analysis rules to the EMR system at each ICU, allowing it to decode its own data and reducing the need for translation at the remote command center, thus simplifying the communication chain and minimizing bandwidth requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If translation software is developed to interpret data from multiple different ICU EMR systems at the remote command center, then consistent data interpretation is achieved, but development time and cost increase significantly
Solution Approach 1:
Instead of translating incoming data from different EMR systems at the remote command center, the patent inverts the approach by having each local EMR system translate its data locally using downloaded analysis rules. This reverses the traditional centralized translation model and distributes the translation function to multiple decentralized locations, reducing the development burden at the remote command center.
Solution Approach 2:
The patent segments the data translation function from the centralized remote command center and distributes it to individual local EMR systems. Each local system receives analysis rules and translates its own clinical data locally, breaking the monolithic translation requirement into multiple independent, smaller translation tasks that can be handled separately by each facility.
2Adaptability or versatility
If translation software is developed to support multiple different ICU EMR systems, then compatibility across facilities is improved, but development cost increases
Solution Approach 1:
The patent creates a universal analysis rule set that can be applied across multiple different EMR systems. Instead of developing separate translation software for each EMR vendor, a single universal rule set is downloaded to each local EMR system, which then translates its proprietary data format using these universal rules, achieving multi-vendor compatibility through a single universal solution.
Solution Approach 2:
Each local EMR system performs its own data translation using downloaded analysis rules, making the translation function self-service rather than requiring centralized translation software development for each facility. This allows each facility to independently handle its own data compatibility issues without requiring expensive custom development.
3Reliability
If clinical data is transmitted from multiple ICUs to the remote command center for analysis, then comprehensive monitoring is achieved, but bandwidth requirements increase
Solution Approach 1:
The patent extracts the data analysis function from the remote command center and places it locally at each ICU EMR system. Instead of transmitting all raw clinical data to the remote center for analysis, only the results of local analysis (decision outcomes) are transmitted, extracting and removing the bulk data transmission requirement while maintaining comprehensive monitoring capabilities.
Solution Approach 2:
Clinical data analysis is performed preliminarily at each local EMR system before data transmission to the remote command center. By conducting the analysis action in advance locally, the system prepares the data beforehand, so that only processed results rather than raw data need to be transmitted, reducing bandwidth consumption.
Data Source
AI summary
A computer-implemented patient monitoring system includes a patient data monitoring system on a first computing system, including a patient medical data query engine configured to generate one or more rule execution requests. The monitoring system further includes a network circuit communicating with the medical database system and one or more remote patient care computing devices. The remote care computing devices in turn include a patient medical data repository and a query response engine configured to respond to received rule execution requests. Responding to rule execution requests includes verifying the validity of a rule execution request, identifying data in the patient medical data repository responsive to the rule execution request, and transmitting response patient medical data responsive to the rule execution request.


