OKS Implementation of SPHN
1. Data Architecture and Primary Systems
At the Eastern Switzerland Children’s Hospital (OKS), medical data exchange is primarily managed via the Orchestra communication server, using established interface standards such as HL7 (Health Level 7) and LDT for laboratory data transfers. Orchestra consolidates data from multiple source systems and integrates them into the Clinical Information System (KIS), where patient data are centrally compiled into an electronic patient record.
The KIS serves as a key data provider for downstream processes. Relevant data are transmitted through dedicated interfaces to internal coding services and to the SAP system used for patient administration and billing. Currently, OKS does not operate a centralized Clinical Data Warehouse or Repository (CDW/CDR). Instead, data retrieval is performed directly on operational databases or their respective replicas.
2. Data Preparation
To enable SPHN integration, a manual ETL (Extract, Transform, Load) workflow has been established. Data are extracted from heterogeneous database systems (e.g., Oracle, PostgreSQL, MS SQL) via custom queries. This approach introduces considerable complexity and is time-consuming, as essential steps such as data joins, encryption, and harmonization across differing data structures must be handled manually.
3. Data Extraction
SPHN-relevant datasets are identified and extracted using manually maintained SQL scripts executed directly on the respective database systems. This requires in-depth system knowledge and careful handling to ensure completeness and accuracy.
4. Data Security and De-identification
Data protection measures are applied early in the process. Pre-encryption is performed at the database level during extraction. Field-level encryption is implemented using pgcrypto, while timestamp de-identification follows a time-shifting approach in accordance with SPHN guidelines.
5. Quality Assurance, Data Transformation and Data Transfer
The final export process is subject to a multi-stage quality assurance framework. Extracted datasets are validated for structural integrity and semantic consistency and finally converted to the rdf format using the SPHN Connector. Prior to transmission to BiomedIT, datasets are compressed and undergo a second layer of encryption using the sett tool (Secured Encryption Transfer Tool), ensuring a high level of security throughout the transfer process.
Figure 1. System Architecture and Data Flow Diagram. EAI: Enterprise Application Integration; IAM: Identity and Access Management; ETL: Extract, Transform, Load; DQ: Data Quality; SPHN Swiss Ped Health Network; sett-Tool: Secured Encryption Transfer Tool