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Fast Healthcare Interoperability Resources (FHIR) for Interoperability in Health Research: Systematic Review.

作者信息

Vorisek Carina Nina, Lehne Moritz, Klopfenstein Sophie Anne Ines, Mayer Paula Josephine, Bartschke Alexander, Haese Thomas, Thun Sylvia

机构信息

Core Facility Digital Medicine and Interoperability, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.

Institute for Medical Informatics, Charité - Universitätsmedizin Berlin, Berlin, Germany.

出版信息

JMIR Med Inform. 2022 Jul 19;10(7):e35724. doi: 10.2196/35724.


DOI:10.2196/35724
PMID:35852842
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9346559/
Abstract

BACKGROUND: The standard Fast Healthcare Interoperability Resources (FHIR) is widely used in health information technology. However, its use as a standard for health research is still less prevalent. To use existing data sources more efficiently for health research, data interoperability becomes increasingly important. FHIR provides solutions by offering resource domains such as "Public Health & Research" and "Evidence-Based Medicine" while using already established web technologies. Therefore, FHIR could help standardize data across different data sources and improve interoperability in health research. OBJECTIVE: The aim of our study was to provide a systematic review of existing literature and determine the current state of FHIR implementations in health research and possible future directions. METHODS: We searched the PubMed/MEDLINE, Embase, Web of Science, IEEE Xplore, and Cochrane Library databases for studies published from 2011 to 2022. Studies investigating the use of FHIR in health research were included. Articles published before 2011, abstracts, reviews, editorials, and expert opinions were excluded. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and registered this study with PROSPERO (CRD42021235393). Data synthesis was done in tables and figures. RESULTS: We identified a total of 998 studies, of which 49 studies were eligible for inclusion. Of the 49 studies, most (73%, n=36) covered the domain of clinical research, whereas the remaining studies focused on public health or epidemiology (6%, n=3) or did not specify their research domain (20%, n=10). Studies used FHIR for data capture (29%, n=14), standardization of data (41%, n=20), analysis (12%, n=6), recruitment (14%, n=7), and consent management (4%, n=2). Most (55%, 27/49) of the studies had a generic approach, and 55% (12/22) of the studies focusing on specific medical specialties (infectious disease, genomics, oncology, environmental health, imaging, and pulmonary hypertension) reported their solutions to be conferrable to other use cases. Most (63%, 31/49) of the studies reported using additional data models or terminologies: Systematized Nomenclature of Medicine Clinical Terms (29%, n=14), Logical Observation Identifiers Names and Codes (37%, n=18), International Classification of Diseases 10th Revision (18%, n=9), Observational Medical Outcomes Partnership common data model (12%, n=6), and others (43%, n=21). Only 4 (8%) studies used a FHIR resource from the domain "Public Health & Research." Limitations using FHIR included the possible change in the content of FHIR resources, safety, legal matters, and the need for a FHIR server. CONCLUSIONS: Our review found that FHIR can be implemented in health research, and the areas of application are broad and generalizable in most use cases. The implementation of international terminologies was common, and other standards such as the Observational Medical Outcomes Partnership common data model could be used as a complement to FHIR. Limitations such as the change of FHIR content, lack of FHIR implementation, safety, and legal matters need to be addressed in future releases to expand the use of FHIR and, therefore, interoperability in health research.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dad4/9346559/25182d15c9fb/medinform_v10i7e35724_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dad4/9346559/7573cf8814c4/medinform_v10i7e35724_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dad4/9346559/339c52527503/medinform_v10i7e35724_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dad4/9346559/34a900344446/medinform_v10i7e35724_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dad4/9346559/25182d15c9fb/medinform_v10i7e35724_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dad4/9346559/7573cf8814c4/medinform_v10i7e35724_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dad4/9346559/339c52527503/medinform_v10i7e35724_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dad4/9346559/34a900344446/medinform_v10i7e35724_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dad4/9346559/25182d15c9fb/medinform_v10i7e35724_fig4.jpg

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本文引用的文献

[1]
CoCross: An ICT Platform Enabling Monitoring Recording and Fusion of Clinical Information Chest Sounds and Imaging of COVID-19 ICU Patients.

Healthcare (Basel). 2022-1-30

[2]
Development of a repository of computable phenotype definitions using the clinical quality language.

JAMIA Open. 2021-12-3

[3]
Fast Healthcare Interoperability Resources (FHIR) in a FAIR Metadata Registry for COVID-19 Research.

Stud Health Technol Inform. 2021-11-18

[4]
CASIDE: A data model for interoperable cancer survivorship information based on FHIR.

J Biomed Inform. 2021-12

[5]
Data Sharing in Distributed Architectures - Concept and Implementation in HiGHmed.

Stud Health Technol Inform. 2021-9-21

[6]
ADT2FHIR - A Tool for Converting ADT/GEKID Oncology Data to HL7 FHIR Resources.

Stud Health Technol Inform. 2021-9-21

[7]
Towards the Representation of Genomic Data in HL7 FHIR and OMOP CDM.

Stud Health Technol Inform. 2021-9-21

[8]
Correction: The Fast Health Interoperability Resources (FHIR) Standard: Systematic Literature Review of Implementations, Applications, Challenges and Opportunities.

JMIR Med Inform. 2021-8-17

[9]
REDCap on FHIR: Clinical Data Interoperability Services.

J Biomed Inform. 2021-9

[10]
Fast Healthcare Interoperability Resources (FHIR®) Representation of Medication Data Derived from German Procedure Classification Codes (OPS) Using Identification of Medicinal Products (IDMP) Compliant Terminology.

Stud Health Technol Inform. 2021-5-24

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