Patient Recruitment Server with Pseudonymization
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Solution Overview
Problem
Current patient recruitment systems face challenges in efficiently identifying and notifying suitable patients for clinical surveys or organ transplants across healthcare institutions while ensuring data protection and minimizing staff input.
Innovation Solution
A patient recruitment server with search and notification routines that pseudonymize patient data records, allowing for efficient recruitment notification and data protection, utilizing distributed patient data processing units and pseudonym administration servers to maintain patient anonymity and secure data handling within healthcare institution intranets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If patient data records are searched and processed across multiple healthcare institutions, then recruitment efficiency and patient identification speed are improved, but data protection requirements and system complexity increase
Solution Approach 1:
A central patient recruitment server acts as an intermediary between healthcare institutions and recruitment requests. The server receives recruitment criteria, coordinates searches across multiple institutions' patient data processing units, aggregates results, and manages notification distribution. This intermediary architecture enables efficient multi-institutional recruitment without requiring direct complex connections between all participating institutions, thus improving productivity while managing system complexity.
2Measurement precision
If patient data is accessed and processed for recruitment purposes, then patient identification accuracy is improved, but data protection risks increase
Solution Approach 1:
The system segments patient data processing by maintaining local patient data processing units at each healthcare institution that store and process patient records locally. The central recruitment server does not directly access raw patient data but instead receives processed recruitment results from these distributed units. This segmentation allows accurate patient identification through coordinated searching while minimizing data protection risks by keeping sensitive patient data localized and reducing centralized data exposure.
3Reliability
If manual patient recruitment processes are used, then data protection control is improved, but recruitment time and staff input increase
Solution Approach 1:
The system implements automated self-service functionality where the patient recruitment server automatically receives recruitment criteria, executes searches across connected healthcare institutions, aggregates patient matches, and dispatches notifications to identified patients. This automation eliminates the need for manual staff involvement in coordinating recruitment across institutions, significantly reducing recruitment time and staff input while maintaining data protection through automated controlled processes and audit trails.
Data Source
AI summary
The invention is based on a patient recruitment system (10)having at least one patient recruitment server (16),which comprises at least one search routine (70) that is provided to search for patient data records (32) on the basis of recruitment characteristics (66).It is proposed that the patient recruitment server (16) comprises a notification routine (82) which is provided to send a recruitment notification (76) regarding at least one patient data record (32) found on the basis of the recruitment characteristics (66).


