Automated Medical Data Anonymization for Cloud Compliance
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Solution Overview
Problem
The existing methods for transmitting medical data records from hospitals to cloud-based storage units are prone to errors, time-intensive, and difficult to control due to the need for manual anonymization, which does not comply with country-specific data protection provisions and may not allow the uploaded data to be processed by cloud services.
Innovation Solution
A method that automatically adjusts patient data records by selecting from a set of predetermined anonymization settings based on the location and services of the external data storage unit, generating an anonymized patient data record, and transmitting it to an external storage unit, while allowing for optional encryption and storage of mapping data to ensure compliance with data protection guidelines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual anonymization is performed before upload, then data protection provisions are observed, but the process becomes error-prone, time-intensive, and difficult to control
Solution Approach 1:
The system performs automatic anonymization of patient data records before upload to cloud services. The anonymization process is executed autonomously by the medical information processing system without requiring manual intervention, thereby eliminating human errors and reducing the time required for the anonymization process while ensuring consistent compliance with data protection provisions.
Solution Approach 2:
The anonymization process is performed in advance before the data is uploaded to external cloud services. By pre-processing the patient data records to remove or mask personally identifiable information, the system ensures that data protection requirements are met prior to transmission, avoiding the need for post-upload corrections and reducing overall processing time.
2Reliability
If manual anonymization is performed, then data protection is improved, but the process becomes difficult to control
Solution Approach 1:
The system autonomously manages the anonymization process through automated algorithms that consistently apply data protection rules. This self-service approach eliminates the variability and control difficulties associated with manual anonymization, as the system automatically identifies and protects sensitive information according to predefined criteria without requiring human judgment or intervention.
Solution Approach 2:
The system applies systematic parameter changes to patient data records during automatic anonymization, such as masking, hashing, or removing specific data fields. These standardized transformations ensure consistent application of data protection measures across all records, making the process controllable and auditable without manual intervention.
3Ease of operation
If patient data is uploaded without anonymization, then upload simplicity is improved, but data protection provisions are violated
Solution Approach 1:
The system performs automatic anonymization as a preliminary step before the upload process. This pre-processing ensures that patient data records are already anonymized when they reach the upload stage, maintaining data protection compliance while keeping the actual upload operation simple and straightforward without requiring manual anonymization steps.
Solution Approach 2:
The anonymization function is integrated into the upload system, allowing it to automatically process and anonymize data records during the upload workflow. This self-service capability maintains the simplicity of the upload process by handling anonymization automatically, eliminating the need for separate manual anonymization steps while ensuring data protection provisions are met.
4Productivity
If automatic anonymization is implemented, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The medical information processing system is designed to perform multiple functions including data reception, automatic anonymization, and upload to various cloud services. By integrating these functions into a single multi-functional system, the patent achieves high processing efficiency without proportionally increasing complexity, as the same system infrastructure handles multiple tasks through standardized processes.
Data Source
AI summary
The present embodiments relate to a method for transmitting medical data records. The method includes receiving a patient data record from an internal data storage unit, selecting an anonymization setting from a set of predetermined anonymization settings, generating an anonymized patient data record on the basis of the selected anonymization setting or rule, and transmitting the anonymized patient data record to an external data storage unit.