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CASIDE: A data model for interoperable cancer survivorship information based on FHIR
Lorena González-Castro1, Victoria M Cal-González2, Guilherme Del Fiol3
1Department of eHealth, Galician Research & Development Center in Advanced Telecommunications (GRADIANT), Vigo, Spain; atlanTTic Research Center, Department of Telematics Engineering, University of Vigo, Vigo, Spain.
Journal of Biomedical Informatics
|November 15, 2021
Summary
Cancer survivorship research needs more attention. CASIDE, a new data model using HL7 FHIR, improves sharing and analysis of cancer survivor health data for better clinical decisions.
Area of Science:
- Oncology
- Health Informatics
- Data Science
Background:
- Cancer survivorship research is underfunded despite long-term health consequences and comorbidities.
- Secondary use of healthcare data offers insights into survivor health trajectories but faces data silos and inconsistency.
- There is an urgent need for improved data infrastructure to support cancer survivorship research.
Purpose of the Study:
- To introduce CASIDE, an interoperable data model for cancer survivorship information.
- To accelerate the secondary use of healthcare data and facilitate data sharing across institutions.
- To provide a holistic view of cancer survivors, integrating clinical data and patient perspectives.
Main Methods:
- Development of CASIDE, a data model built upon the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard.
- Utilizing FHIR for standardized data representation and interoperability in cancer survivorship.
- Discussing the advantages and challenges of information modeling with FHIR.
Main Results:
- CASIDE enables a holistic view of cancer survivors by integrating diverse data types.
- The model facilitates the secondary use of healthcare data for cancer survivorship research.
- CASIDE is a generalizable approach supporting downstream applications and collaborative research.
Conclusions:
- CASIDE promotes data sharing and secondary data use in cancer survivorship research.
- The data model supports clinical decision-making and translational research.
- Adoption of FHIR standard enhances interoperability for cancer survivorship data.
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