Real-Time Patient Data Streaming on Mobile Devices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current wireless communication systems for healthcare providers lack the ability to efficiently transmit and display real-time, high-resolution patient physiological data on small handheld devices, such as PDAs and cellular phones, which is crucial for effective monitoring and decision-making.
Innovation Solution
The system utilizes Microsoft's .NET platform and smart client applications to optimize data transmission and display on handheld devices, incorporating customized charting components and GAPI for high-performance graphic rendering, enabling real-time monitoring and analysis of patient data with features like zooming, scrolling, and HIPAA-compliant security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If patient data is transmitted over wireless networks to handheld devices, then real-time monitoring capability is improved, but data transmission reliability deteriorates due to low bandwidth and intermittent connections
Solution Approach 1:
The system performs preliminary actions by buffering patient data locally at the handheld device before transmission is needed. Data is collected and stored in a local buffer when connections are available, then transmitted when connectivity is established, ensuring real-time monitoring capability while maintaining reliability during intermittent connections.
Solution Approach 2:
A data buffering mechanism acts as an intermediary between the patient monitoring system and the handheld device. This buffer absorbs the mismatch between continuous data generation and intermittent transmission capability, maintaining both real-time monitoring and transmission reliability.
2Measurement precision
If high-resolution graphical patient data is displayed on small handheld screens, then data discernability is improved, but device memory requirements worsen
Solution Approach 1:
The system extracts only the essential graphical data elements needed for clinical decision-making and displays them in an optimized format on the handheld device. Non-essential data is omitted or stored separately, reducing memory requirements while maintaining data discernability for critical patient parameters.
Solution Approach 2:
The system transitions from displaying complete high-resolution graphical waveforms to displaying key features and summaries of patient data in a condensed format. Critical information is preserved while reducing the dimensional complexity of the displayed data, thereby lowering memory requirements.
3Loss of information
If complete patient data is transmitted continuously, then data completeness is improved, but network bandwidth consumption worsens
Solution Approach 1:
The system extracts and transmits only the most critical patient data parameters and alarm conditions rather than complete continuous data streams. This selective transmission maintains data completeness for clinical decision-making while significantly reducing network bandwidth consumption.
Solution Approach 2:
Instead of continuous transmission, the system employs periodic data transmission at optimized intervals. Data is transmitted in periodic updates rather than continuously, reducing bandwidth consumption while maintaining sufficient data completeness for patient monitoring.
Data Source
AI summary
A data-processing tool for displaying real-time patient data on remote and/or mobile devices. The tool renders graphical data on the screen of the remote device in a manner that makes it practical for the health care provider to review the data. Charting components provide landscape support, an ability to overlay patient data and patient images, zoom in/zoom out, custom variable speed scrolling, split screen support, and formatting control. The methodology operates as an asynchronous application, allowing patient data to be streamed in real-time to the handheld device while conserving enough CPU power to simultaneously allow the end user to interact at will with the responsive display application. Finally, the methodology implements an IT management console that allows system managers to monitor the exchange of data between hospital systems and the primary database, including all patient data packets, notifications and alerts, connected remote devices, etc.