Remote Therapy Management for Implantable Medical Devices
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Solution Overview
Problem
Current medical devices that deliver therapy, such as neurostimulators and drug infusion systems, require lengthy and burdensome programming sessions to determine optimal parameter combinations, often necessitating multiple follow-up sessions due to inadequate initial programming and lack of effective record-keeping, leading to inefficiencies and suboptimal patient outcomes.
Innovation Solution
A remote management system for implantable medical devices that includes an IMD, a patient programmer, and a remote networking device, allowing for wireless communication and data transmission over a network to record, analyze, and adjust therapy parameters, enabling patients and clinicians to manage therapy delivery and usage information remotely, thereby reducing the burden of manual programming and improving therapy efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual programming methods are used with trial and error testing of parameter combinations, then therapy programming can be performed, but the process becomes time consuming and burdensome
Solution Approach 1:
The system automatically performs preliminary actions by collecting usage data during normal therapy delivery and pre-processing this information to identify patterns and ineffective programs. This preliminary analysis is done before the clinician needs to make programming decisions, reducing the time required during actual programming sessions.
Solution Approach 2:
The system implements continuous feedback loops where usage data from patients is collected, analyzed, and fed back to automatically adjust programming parameters. This feedback mechanism eliminates manual trial-and-error by using real-world performance data to guide programming decisions, significantly reducing programming time and improving ease of operation.
2Reliability
If multiple follow-up programming sessions are conducted to achieve adequate therapy programming, then optimal therapy parameters can be found, but patient burden and healthcare resource utilization increase
Solution Approach 1:
The system enables self-service by automatically monitoring therapy usage, analyzing effectiveness, and performing reprogramming without requiring multiple clinician visits. The implantable device and external device work together to self-adjust programming based on collected usage data, eliminating the need for repeated follow-up sessions while maintaining high reliability of therapy programming.
Solution Approach 2:
The system replaces the mechanical process of manual programming and follow-up sessions with automated electronic monitoring and analysis. Usage data is automatically collected, transmitted, and processed to generate optimized programming parameters, substituting the need for repeated clinical interventions with an automated information-based system.
3Loss of information
If comprehensive usage data is collected and stored locally in the implantable device and external device, then complete records are available, but device memory requirements and data management complexity increase
Solution Approach 1:
The system introduces an intermediary component that acts as a data management bridge between the implantable device and the clinician/patient. This intermediary handles the complex tasks of data collection, storage, transmission, and analysis, allowing the medical devices themselves to remain relatively simple while ensuring complete usage data is captured and managed efficiently.
4Productivity
If automatic analysis and reprogramming based on usage data is implemented, then programming time is reduced, but system complexity and computational requirements increase
Solution Approach 1:
The system segments the programming task across multiple components: the implantable device collects usage data, the external device stores and transmits data, and a separate analysis system processes the information to generate reprogramming parameters. This segmentation distributes computational complexity across different devices and levels, reducing the burden on any single device while maintaining high programming efficiency.
Data Source
AI summary
The disclosure is directed to techniques for remote management of information relating to therapy delivered to a patient by an implantable medical device (IMD). A remote monitoring system for therapy programming includes an IMD that delivers therapy, e.g., neurostimulation, drug therapy, or both, to a patient, an external programming device associated with the IMD, such as a patient programmer, and a remote networking device that receives usage information from the external programming device. The external programming device communicates with the IMD via local, wireless communication, and the remote networking device receives usage information from the external programming device via a network. The usage information includes information that relates to use of therapy by the patient, use of features of the external programming device and the IMD, or use of navigation patterns of a user interface of the external programming device.