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The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
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State-of-the-Art Fast Healthcare Interoperability Resources (FHIR)-Based Data Model and Structure Implementations:

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|September 24, 2024
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Summary

The Fast Healthcare Interoperability Resources (FHIR) standard enhances clinical research by improving data interoperability. This review identifies dynamic and static FHIR data models, tools, and challenges for better data integration and analysis.

Keywords:
FHIRFast Healthcare Interoperability ResourcesPRISMAdata modelinteroperabilitymodeling

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Area of Science:

  • Health Informatics
  • Clinical Research Data Management
  • Interoperability Standards

Background:

  • Standardized data models are essential for leveraging clinical data in research.
  • Semantic interoperability requires well-defined data relationships.
  • Fast Healthcare Interoperability Resources (FHIR) offers a practical approach to enhance data accessibility and research.

Purpose of the Study:

  • To provide a comprehensive overview of FHIR-based data models and structures.
  • To identify and discuss tools, resources, and limitations in FHIR-based research.
  • To analyze the current landscape of FHIR implementation in clinical studies.

Main Methods:

  • Systematic review following PRISMA-ScR guidelines.
  • Analysis of articles from major scientific databases (PubMed, Scopus, Web of Science, IEEE Xplore, ACM Digital Library, Google Scholar).
  • Synthesis of extracted data to identify patterns in FHIR data model usage.

Main Results:

  • Identified dynamic (pipeline-based) and static FHIR data models.
  • Categorized use cases: chronic diseases, infectious diseases (including COVID-19), cancer research, intensive care, and general medical notes.
  • Common FHIR resources: Observation, Condition, Patient. Key tools include FHIR frameworks, machine learning, and secure data storage. Limitations involve data integration, interoperability, standardization, performance, and scalability.

Conclusions:

  • FHIR is a promising standard for real-world healthcare applications and translational research.
  • FHIR modeling of electronic health records facilitates data integration, transmission, and analysis.
  • FHIR-based data exports improve interoperability across different settings, though challenges remain.