Patient Management System Integrating IMD and External Data
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Solution Overview
Problem
Existing medical devices struggle to provide accurate and comprehensive patient health monitoring by relying solely on internal data from implantable medical devices (IMDs), as external factors significantly influence sensed data, leading to incomplete health assessments.
Innovation Solution
An advanced patient management system that combines internal health-related parameters from IMDs with external data sources, including user inputs and environmental data, to create a more comprehensive view of a patient's health condition, using a programmable device with modules for parameter acquisition, event detection, and communication to trend and display health parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only internal data from implantable medical devices is used for health monitoring, then device complexity is reduced, but measurement precision and reliability of health assessment deteriorate due to lack of external context
Solution Approach 1:
The patent combines internal IMD data with external data sources (environmental sensors, user inputs, electronic health records) into a unified patient management system. This merging of data sources provides comprehensive health context while maintaining manageable system complexity through standardized integration protocols.
Solution Approach 2:
The patient management system is designed to handle multiple data types from diverse sources (IMD sensors, environmental monitors, user inputs, EHR systems) through a universal platform. This multi-functional approach enables comprehensive health assessment without requiring separate specialized systems for each data source.
2Measurement precision
If multiple external data sources are integrated to improve health assessment accuracy, then measurement precision improves, but device complexity and data processing requirements worsen
Solution Approach 1:
The system segments data processing into distinct modules: data acquisition from multiple sources, data validation and filtering, contextual analysis, and clinical decision support. This segmentation allows each module to handle specific tasks efficiently, reducing overall system complexity while maintaining comprehensive health assessment capabilities.
Solution Approach 2:
The patient management system acts as an intermediary layer between raw data from multiple sources and clinical decision-making. It processes, validates, and contextualizes data before presenting actionable insights to clinicians, thereby managing complexity while improving assessment accuracy.
3Loss of information
If comprehensive health data from multiple sources is collected, then information completeness improves, but loss of time for data processing and analysis worsens
Solution Approach 1:
The system performs preliminary data validation, filtering, and contextualization as data is being collected from various sources. By preparing and organizing data in advance rather than processing raw data when needed, the system reduces subsequent processing time while maintaining complete health context.
Solution Approach 2:
The system continuously monitors incoming data streams and provides real-time feedback on data quality and completeness. This allows for dynamic adjustment of data collection and processing priorities, ensuring comprehensive health context is captured while minimizing processing delays through adaptive resource allocation.
Data Source
AI summary
Systems, devices and methods for defining, identifying and using health-related significant events are disclosed. One aspect is a programmable device having machine executable instructions for performing a method to assist with managing a patient's health. In various embodiments, at least one previously-defined event is detected based on a number of acquired health-related parameters. The at least one detected event is recorded with an associated time when the at least one detected significant event occurred. An action is triggered based on the at least one detected event. The at least one detected event is displayed with at least one trended health-related parameter in a single display area. Other aspects and embodiments are provided herein.