Remote CRT Reprogramming Using Patient Response Feedback
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Solution Overview
Problem
Current cardiac resynchronization therapy (CRT) devices often suffer from suboptimal programming, leading to inefficient use of resources and potential harm to patients due to inappropriate parameter settings, necessitating frequent in-clinic follow-up appointments that are burdensome and resource-intensive.
Innovation Solution
A system and method for remotely evaluating patient response to CRT therapy by analyzing physiologic information to determine optimal parameter settings, allowing for remote reprogramming and reducing the need for in-person visits, using artificial intelligence and machine learning to identify and adjust therapy modes based on patient-specific data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If frequent in-clinic follow-up appointments are conducted to monitor and adjust CRT therapy, then patient response optimization is improved, but clinical burden and resource consumption increase
Solution Approach 1:
The system automatically evaluates patient response to CRT therapy by analyzing physiologic information and provides feedback through remote reprogramming recommendations. The implantable medical device monitors therapy effectiveness and communicates with external systems to determine optimal parameter adjustments, eliminating the need for frequent manual in-clinic follow-ups while maintaining optimized patient care.
Solution Approach 2:
The implantable medical device performs self-evaluation of therapy effectiveness by autonomously analyzing its own physiologic data and determining patient response metrics. The device generates its own reprogramming recommendations based on evaluated response, reducing dependence on clinician intervention and minimizing clinical burden while maintaining therapeutic optimization.
2Manufacturing precision
If manual in-clinic programming is used to adjust CRT parameters, then programming precision is improved, but time consumption and resource usage increase
Solution Approach 1:
The system performs preliminary evaluation of patient response by continuously monitoring physiologic information and pre-determining optimal programming parameters before in-clinic visits are needed. The implantable medical device proactively analyzes therapy effectiveness and generates reprogramming recommendations in advance, allowing for timely adjustments without requiring manual intervention.
Solution Approach 2:
The manual mechanical process of in-clinic programming is replaced by an automated electronic system that evaluates patient response and generates programming recommendations through computer-based analysis. The implantable medical device uses electronic sensors and processing circuits to monitor physiologic data, determine response metrics, and communicate programming adjustments remotely, eliminating time-consuming manual procedures while maintaining precision.
3Device complexity
If suboptimal CRT parameter settings are used, then device simplicity is maintained, but patient outcome and therapy efficacy deteriorate
Solution Approach 1:
The CRT device transitions from static, fixed parameter settings to dynamic, adaptive programming that automatically adjusts based on evaluated patient response. The implantable medical device continuously monitors physiologic information, determines therapy effectiveness, and modifies parameters in real-time to optimize patient outcome while maintaining appropriate device complexity through automated control.
Solution Approach 2:
The system automatically modifies CRT parameters based on evaluated patient response by analyzing changes in physiologic information. The implantable medical device determines optimal parameter values through computational algorithms and implements parameter changes remotely, ensuring therapy efficacy is maintained or improved without requiring complex manual reprogramming while adapting to individual patient needs.
Data Source
AI summary
Systems and methods are disclosed to evaluate patient response to cardiac rhythm management therapy and remotely reprogram an implantable medical device, including receiving physiologic information of a patient in a first time period responsive to a first cardiac rhythm management therapy, determining a first patient response metric indicative of patient response to the first cardiac rhythm management therapy, generating a reprogramming recommendation for the implantable medical device including a second cardiac rhythm management therapy based on the first patient response metric, and remotely reprogramming the implantable medical device to provide the second cardiac rhythm management therapy to the patient in a second time period.