DICOM Study Tracking with Cryptographic Hashes Across Networks
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Solution Overview
Problem
Current systems require remote connection to a medical service provider's VPN or WiFi network to access protected health information (PHI) for medical imaging analysis, which is inefficient and insecure, especially when dealing with de-identified data that lacks chronological order and common identifiers.
Innovation Solution
A system that maintains a database of patient identifiers within the organization, generates cryptographic hashes, and uses a trusted broker service to link related studies without exposing identifying information, allowing secure and efficient access to PHI across networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If de-identified data is stored in the cloud without identifiers, then data security and privacy are improved, but the ability to match and relate studies across time and organizations is lost
Solution Approach 1:
The patent introduces cryptographic hashes as an intermediary mechanism that allows studies to be linked without exposing identifying information. The hash function acts as a mediator between the de-identified cloud storage and the identifying information maintained locally, enabling study matching while preserving data security and privacy.
Solution Approach 2:
The system segments identifying information into two parts: cryptographic hashes stored with de-identified data in the cloud, and the actual identifying fields maintained locally in a database. This segmentation allows the cloud to store secure de-identified data while the local system maintains the ability to match studies through hash comparison.
2Reliability
If each incoming DICOM upload is treated as a different study with obfuscated UIDs, then data security is maintained, but the efficiency of tracking and retrieving PHI data that has changed is reduced
Solution Approach 1:
Cryptographic hashes serve as the intermediary that enables efficient tracking of PHI changes. By computing hashes of identifying fields and storing them with the DICOM data, the system can quickly compare hashes to identify updated studies without treating each upload as a completely new study, thus improving tracking efficiency while maintaining security.
Solution Approach 2:
The system performs preliminary action by computing and storing cryptographic hashes of identifying fields at the time of data upload. This preliminary hash computation enables future efficient comparison and identification of updated studies without requiring re-processing of the entire dataset, improving operational efficiency.
3Ease of operation
If Patient ID, Accession Number, Name and Birthdate are stored with all identifiers left intact, then study matching is simplified, but personally identifiable information security is degraded
Solution Approach 1:
Cryptographic hashes act as the intermediary that simplifies study matching without exposing actual identifying information. The hash comparison provides a simple and efficient matching mechanism, while the actual Patient ID, Accession Number,_name and Birthdate remain protected and are only accessed locally where needed, reducing PHI security risks.
Solution Approach 2:
Instead of storing the actual identifying information in the cloud, the system creates a copy in the form of cryptographic hashes. These hash copies enable study matching operations while the original identifying information remains secure and is not exposed in the cloud storage environment.
4Loss of information
If a service maintains a database of personally identifiable information and generates cryptographic hashes, then the ability to link related studies is improved, but system complexity increases
Solution Approach 1:
The cryptographic hash function serves as a relatively simple intermediary that bridges the gap between de-identified cloud storage and identifying information. By using standard cryptographic hashing algorithms, the system achieves effective study linkage without requiring complex database structures or sophisticated matching algorithms, thus limiting the increase in system complexity.
Data Source
AI summary
A protected health information (PHI) service is provided which de-identifies medical study data (e.g., digital imaging and communications in medicine (DICOM) study data) and allows medical providers to control PHI data, and uploads the de-identified data to a remote service system. The PHI service, or an associated service, hosted within an organization performing scans, maintains a database of personally identifiable information, and enables the user to access PHI without having to establish a connection to a virtual private network or WiFi network of the medical service provider. The system also increases the speed, efficiency and flexibility of the technology of medical imaging and analysis over computer networks by correlating unique identifiers in the PHI Service in order to accept DICOM study data over time, and track and retrieve what PHI data has changed regardless of the chronological order in which it was received.