AI Event Response System for Medical Alert Prioritization
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Solution Overview
Problem
Current medical alarm systems and event response systems face delays due to the inclusion of test and false alarms, which can lead to inappropriate screening of true emergency alerts, potentially resulting in delayed medical assistance and increased risk to users.
Innovation Solution
Implementing an AI system integrated with an IVR system to categorize event alerts and prioritize responses based on collected information, automatically processing non-emergency alerts and ensuring timely intervention for genuine emergencies by connecting users directly to live operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If test and false alarms are included in the event alert queue, then the system can handle all types of alerts uniformly, but the queue length increases and delays emergency response to genuine emergencies
Solution Approach 1:
The patent segments the event alert queue into multiple priority levels (first priority for genuine emergencies, second priority for test/false alarms). The AI system categorizes alerts and routes them to different queue positions, allowing genuine emergencies to be processed immediately while test alarms are handled separately, thus resolving the contradiction between handling all alert types and maintaining fast emergency response.
2Reliability
If all event alerts are manually reviewed by operators, then accuracy in identifying genuine emergencies is improved, but the processing time and operational complexity increase
Solution Approach 1:
The patent introduces an AI system as an intermediary between alert reception and operator review. The AI collects additional information, categorizes alerts, and pre-screens them to identify genuine emergencies versus test/false alarms. This intermediary layer provides accurate classification while reducing the burden on operators, thus improving both reliability and productivity simultaneously.
Solution Approach 2:
The system performs preliminary actions by collecting additional information and categorizing alerts before they reach the operator queue. The AI system prepares the alert data, identifies priority levels, and routes alerts appropriately in advance, so operators receive pre-processed information that requires minimal additional analysis, thereby improving processing speed without sacrificing accuracy.
3Measurement precision
If additional information is collected for each event alert, then the accuracy of emergency identification is improved, but the time required to process each alert increases
Solution Approach 1:
The patent applies preliminary action by automatically collecting additional information and categorizing alerts in advance using AI, before human operators review them. This pre-processing eliminates the need for operators to manually gather information, thus improving identification accuracy while actually reducing total processing time since the AI can collect data in parallel and prepare categorization results ahead of time.
Data Source
AI summary
A method for artificial intelligence (AI) event response includes receiving an event alert or a communication associated with an event alert from a communication device. The method includes an AI system collecting additional information about at least one of the event alert, the communication device, or a user of the communication device. The method includes the AI system categorizing the event alert into one category of multiple categories based on the collected additional information. The method includes prioritizing subsequent handling of the event alert among other event alerts based on the category.