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Build an Open Standard Comprehensive Cancer Cohort Research Database.

Chung-Yueh Lien1, Chao-Wei Hsu1, Pau-Choo Chung2

  • 1Dept. of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan.

Studies in Health Technology and Informatics
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Summary

This study created a cancer research database using healthcare interoperability standards like Fast Healthcare Interoperability Resources (FHIR) and Digital Imaging and Communications in Medicine (DICOM). The framework integrates diverse data from Electronic Health Records for comprehensive cancer cohort analysis.

Keywords:
DICOMHL7 FHIRdigital pathologyinteroperability

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Area of Science:

  • Biomedical Informatics
  • Health Data Science
  • Cancer Research Informatics

Background:

  • Healthcare data is fragmented across multiple Electronic Health Records (EHR) systems.
  • Integrating diverse data types (demographics, imaging, genomics) is crucial for comprehensive cancer research.
  • Standardized interoperability frameworks are needed to facilitate data aggregation.

Purpose of the Study:

  • To develop a framework for a comprehensive cancer cohort research database.
  • To leverage healthcare interoperability standards (FHIR, DICOM) for data integration.
  • To enable seamless data exchange and analysis across multiple EHR systems.

Main Methods:

  • Developed a data collection pipeline for EHR data, including demographics, reports, CT images, whole slide images (DICOM), and genomic data.
  • Converted collected data into Fast Healthcare Interoperability Resources (FHIR) format using international terminologies (ICD, LOINC, SNOMED CT).
  • Utilized a FHIR imaging report implementation guide and integrated genomic data via cBioPortal into a centralized portal.

Main Results:

  • Successfully collected and integrated data from 625 non-small cell lung cancer and 373 head and neck cancer cases.
  • Established a FHIR-based data structure for diverse cancer-related information.
  • Implemented a centralized portal for accessing and analyzing integrated multimodal cancer data.

Conclusions:

  • The developed framework effectively integrates heterogeneous healthcare data for cancer research.
  • Utilizing FHIR and DICOM standards facilitates the creation of robust cancer cohort databases.
  • The centralized portal provides a valuable resource for advancing cancer research through data integration.