Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation Study | JoVE Visualize

Area of Science:

Oncology
Health Informatics
Data Science

Background:

Real-world data (RWD) from diverse sources like electronic health records and cancer registries offer valuable insights into patient populations beyond clinical trials.
Six Bavarian university hospitals have established a collaborative research IT infrastructure to effectively leverage oncological RWD for advancing cancer research.

Purpose of the Study:

To design, implement, and deploy a modular data transformation pipeline for oncological RWD.
To convert RWD into Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) format and subsequently into a tabular format.
To prepare data for a federated analysis (FA) across six Bavarian Cancer Research Center university hospitals, ensuring privacy through decentralization.

Main Methods:

Developed a pipeline to convert the oncological basic dataset (oBDS) into HL7 FHIR and tabular formats for FA.
Ensured the pipeline's adaptability to diverse IT infrastructures and systems while maintaining data privacy via decentralization.
Assessed pipeline functionality and validity by defining a cohort for two medical research questions and comparing FA results with the Bavarian Cancer Registry and local tumor documentation systems.

Main Results:

Conducted an FA of 17,885 cancer cases from 2021/2022, identifying breast, prostate, and malignant melanoma as prevalent diagnoses.
Observed gender-specific trends: larynx and esophagus cancers more common in males; breast and thyroid cancers more frequent in females.
Noted discrepancies with the Bavarian Cancer Registry, likely due to differing time periods and data source scope, with the registry reporting approximately three times more cases.

Conclusions:

The modular pipeline successfully transformed oncological RWD across six hospitals, enabling privacy-preserving federated analysis.
The federated approach facilitated comprehensive data analysis while maintaining patient privacy.
Future work includes supporting newer oBDS versions, automating data quality checks, and integrating additional clinical data to enhance federated health data networks for cancer research.