Selective Patient Data Routing for Emergency Care
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Solution Overview
Problem
In emergency medical situations, there is a challenge in quickly routing patient data from field devices to the most appropriate treatment centers with the necessary facilities and staff, leading to potential delays in critical treatments like PCI for STEMI patients.
Innovation Solution
A system that uses a central server to route medical event data from field devices to selected treatment centers based on user-configurable rules, location, and scheduling information, ensuring that relevant data is delivered to destinations with the capability to provide timely and appropriate care.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If patient data is routed to all treatment centers, then comprehensive coverage is achieved, but data transmission time and network load increase
Solution Approach 1:
The system segments the treatment center network into multiple geographic regions, with each regional server managing a specific subset of treatment centers. This segmentation allows patient data to be routed to only the relevant regional servers first, reducing the time and network load compared to broadcasting to all treatment centers simultaneously, while still ensuring comprehensive coverage through hierarchical distribution.
Solution Approach 2:
The system performs preliminary actions by pre-establishing regional server infrastructure and pre-configuring routing rules based on treatment center capabilities and geographic locations. When patient data needs to be transmitted, the routing decision is made quickly using pre-defined criteria, eliminating the need for real-time evaluation of all treatment centers and thus reducing data transmission time while maintaining reliable coverage.
2Adaptability or versatility
If patient data is transmitted to multiple destinations simultaneously, then treatment options are maximized, but system complexity and resource consumption increase
Solution Approach 1:
The routing system dynamically adjusts data transmission based on real-time conditions such as treatment center availability, patient condition severity, and geographic proximity. Instead of statically transmitting to all destinations simultaneously, the system adaptively selects and prioritizes destinations, reducing system complexity while maintaining versatility in providing multiple treatment options when needed.
Solution Approach 2:
Different regions and treatment centers receive different subsets of patient data based on their specific capabilities, geographic location, and relevance to the patient's condition. This local quality approach ensures that each destination receives only the necessary data for its specific role, reducing overall system complexity while preserving adaptability to provide appropriate treatment options at each location.
3Reliability
If all treatment centers receive patient data, then care coordination is improved, but network bandwidth and processing resources are overutilized
Solution Approach 1:
The network is segmented into regional zones with dedicated servers managing data distribution within each zone. Patient data is transmitted only to relevant regional servers based on geographic proximity and treatment capability matching, significantly reducing overall network bandwidth consumption compared to broadcasting to all treatment centers, while maintaining effective care coordination within each region.
Solution Approach 2:
The system implements partial action by transmitting patient data only to a subset of treatment centers that are most relevant to the specific patient case, rather than to all treatment centers. This selective transmission reduces network bandwidth and processing resource utilization while still achieving effective care coordination through the hierarchical regional server structure that can relay information as needed.
Data Source
AI summary
Techniques for routing event data from a field device, such as an external defibrillator, to a selected subset of a plurality of possible destinations are described. The event data may include physiological data of the patient, such as a 12-lead electrocardiogram (ECG). The destinations may be associated with one of a plurality of patient treatment centers, and may include, as examples, computing device, printers, displays, personal digital assistants, or web-accessible accounts. In some examples, a server maintains user-configurable information or rules for at least some of the destinations, and uses the information or rules for determining whether event data received from a field device is routed to the destination. In some examples, the server may also make the routing determination based on an analysis of event data, such as a determination as to whether the event data indicates that the patient is suspected to be experiencing an acute myocardial infarction.