Remote IMD Monitoring via Virtual Check-in
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Solution Overview
Problem
Infections associated with implantable medical devices (IMDs) pose a significant health and economic concern due to the risk of microbial introduction during implantation, leading to potential complications that require aggressive systemic drug treatment and often necessitate device explantation, highlighting the need for early detection and intervention.
Innovation Solution
A system of processing circuitry in computing devices, including mobile devices, facilitates virtual check-ins for patients, enabling interactive sessions for monitoring IMDs and patient health status through secure, remote communication, utilizing AI and ML models to assess images and physiological data for early detection of abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If in-person post-implant follow-up visits are conducted, then patient safety and device monitoring are ensured, but patient burden and healthcare system resources are significantly increased
Solution Approach 1:
The patent creates a virtual copy of the in-person follow-up visit through a structured remote session that replicates the essential monitoring functions. The system captures images of the implant site, collects patient-reported symptoms, retrieves device data, and performs remote evaluation, thereby copying the safety-check function without requiring physical patient presence at the clinic.
Solution Approach 2:
The patent replaces the mechanical in-person visit system with a digital/telemedical system. Instead of physically transporting the patient to the clinic, the system uses image capture devices, communication networks, and electronic data processing to perform the follow-up evaluation remotely, substituting physical presence with digital information exchange.
2Reliability
If in-person post-implant follow-up visits are conducted, then device performance and infection detection are monitored, but healthcare system resources and time are consumed
Solution Approach 1:
The system creates a virtual replica of the clinical evaluation process by capturing implant site images, collecting patient symptoms, retrieving device data, and performing remote analysis. This virtual copy enables comprehensive infection detection without requiring HCP time for in-person visits, thereby maintaining detection reliability while improving system productivity.
Solution Approach 2:
The patient performs self-monitoring activities including capturing images of the implant site, reporting symptoms, and providing device information. This self-service approach shifts the burden from the healthcare system to the patient, allowing the system to maintain monitoring capabilities without consuming HCP resources for routine checks.
3Reliability
If early detection of infections is implemented, then device explantation can be avoided, but detection capability and intervention timing must be optimized
Solution Approach 1:
The system performs preliminary detection actions by capturing implant site images and collecting patient symptom data at scheduled intervals during the critical post-implant period. This preliminary monitoring identifies early signs of infection before they progress to require device explantation, enabling timely intervention.
Solution Approach 2:
The system establishes feedback loops by continuously monitoring patient symptoms, implant site images, and device data, then providing timely feedback to both the patient and healthcare provider. This feedback mechanism enables early detection of infection signs and facilitates prompt intervention to avoid device explantation.
Data Source
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AI summary
Techniques for remote monitoring of a patient and corresponding medical device(s) are described. The remote monitoring comprises providing an interactive session configured to allow a user to navigate a plurality of subsessions, determining a first set of data items in accordance with a first subsession, the first set of data items including the image data, determining a second set of data items in accordance with a second subsession of the interactive session, determining, based at least in part on the first set of data items and the second set of data items, an abnormality, and outputting a post implant report of the interactive session.