Secure Mobile Clinical Image Communication via Unique Identifiers
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Solution Overview
Problem
Current healthcare systems are not mobile-friendly, making it difficult for clinicians to access and review radiology and clinical images remotely, and there is a need for secure, efficient communication of clinical findings while maintaining patient information security.
Innovation Solution
A system and method for bi-directional communication between a centralized healthcare system and mobile devices, using a sender and receiver service to transmit and receive clinical images and findings securely, with unique identifiers to ensure patient information privacy and minimal user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If clinicians use traditional internal healthcare systems to review clinical images, then patient information security is maintained, but mobile accessibility and remote viewing capability are lost
Solution Approach 1:
The system segments patient information by separating identifiable patient data from clinical images. Unique identifiers are used to reference images without exposing patient identities in external communications, allowing mobile accessibility while maintaining security through data compartmentalization
Solution Approach 2:
The system introduces an intermediary layer that translates between internal healthcare system references and external mobile device communications. The unique identifier acts as a mediator, enabling secure transmission of clinical images to mobile devices without directly exposing patient information to external systems
2Adaptability or versatility
If clinicians access healthcare systems from desktop computers only, then system security is maintained, but remote work flexibility and accessibility are reduced
Solution Approach 1:
The system creates a universal interface that works across multiple device types (desktop computers, tablets, smartphones). The unique identifier-based communication protocol enables the same clinical image review functionality to operate on any device with email capability, eliminating device-specific constraints
Solution Approach 2:
The system creates simplified copies of clinical images for external transmission. Instead of transferring full access to the complex internal healthcare system, the system transmits referenced copies via email that can be viewed on any device without requiring the full system architecture
3Productivity
If manual processes are used for transmitting and tracking clinical images, then system complexity is reduced, but time efficiency and productivity are decreased
Solution Approach 1:
The system performs preliminary actions by automatically generating unique identifiers and embedding them in email communications before transmission. Tracking information and image references are prepared in advance, eliminating the need for manual tracking processes and improving time efficiency
Solution Approach 2:
The system implements automated feedback mechanisms where incoming emails containing unique identifiers are automatically tracked and matched to corresponding clinical images. This closed-loop feedback system eliminates manual tracking while maintaining system organization through automated correspondence monitoring
Data Source
AI summary
Methods, systems, and computer-readable media are disclosed herein that provide services for automatically facilitate mobile-friendly messages containing identification-scrubbed clinical images transferred between a secure healthcare system and an external application that is accessed on a mobile device. Through the services and using minimal inputs, a scrubbed outgoing message containing patient-specific images is automatically generated and transmitted to a mobile device for a user to review. The services automatically track replies as incoming messages that can be mapped back to one patient and one patient visit using unique identifiers that ensure patient information is not shared outside the secure healthcare system. Also, the services automatically extract clinical finding from incoming messages and provide notifications containing the clinical findings to the appropriate clinician for the patient that corresponds to the reviewed images.