A systematic review of the use of FHIR to support clinical research, public health and medical education
| Date | 03 September 2024 |
| Pages | 134-154 |
| DOI | https://doi.org/10.1108/DTA-11-2023-0804 |
| Published date | 03 September 2024 |
| Author | João Pavão,Rute Bastardo,Nelson Pacheco Rocha |
A systematic review of the use
of FHIR to support clinical
research, public health and
medical education
Jo~
ao Pav~
ao and Rute Bastardo
Science and Technology School, University of Tr�
as-os-Montes and Alto Douro,
Vila Real, Portugal , and
Nelson Pacheco Rocha
Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
Abstract
Purpose –This systematic review aimed to identify and categorize applications using Fast Healthcare
Interoperability Resources (FHIR) to support activities outside of direct healthcare provision.
Design/methodology/approach –A systematic electronic search was performed, and 53 studies were
included after the selection process.
Findings –The results show that FHIR is being used to support (1) clinical research (i.e. clinical research
based on interventional trials, data interoperability to support clinical research and advanced communication
services to support clinical research), (2) public health and (3) medical education. Despite the FHIR potential to
support activities outside of direct healthcare provision, some barriers were identified, namely difficulties
translating the proposed applications to clinical environments or FHIR technical issues that require further
developments.
Originality/value –This study provided a broad review of how FHIR is being applied in clinical activities
outside of direct clinical care and identified three major domains, that is, clinical research, public health and
medical education, being the first and most representative in terms of number of publications.
Keywords Systematic review, Fast Health Interoperability Resources, FHIR, Clinical research, Public health,
Medical education
Paper type Literature review
1. Introduction
In 2013, Health Level Seven International (HL7) published the first draft version of Fast
Healthcare Interoperability Resource (FHIR) to surpass the shortcomings of the previously
developed HL7 clinical care standards. FHIR information model separates clinical data into
granular components or resources, which provide generic data structures for common
healthcare concepts (e.g. patient or condition), each one with standardized data elements,
constraints and relationships to other resources. Moreover, the fields of the FHIR resources
and respective data types can be serialized using JavaScript Object Notation (JSON) or
Extensible Markup Language (XML).
The specification of FHIR puts a strong emphasis on its implementation using a
representational state transfer (REST) application programming interface (API)
incorporating well-defined interfaces to turn different clinical applications interoperable.
Due to these characteristics, the FHIR facilitates the development of applications to support
clinical practice (Staff, 2022), namely, to provide clinicians with comprehensive, up-to-date,
safe and congruent information from the patients, immediately accessible at the point of care,
even if multiple healthcare services or institutions are involved. The detailed FHIR
information model suitable for validation, and the existence of reference implementations,
design and development tools as well as an active community of developers promoted its
DTA
59,1
134
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2514-9288.htm
Received 30 November 2023
Revised 13 April 2024
Accepted 14 August 2024
Data Technologies and
Applications
Vol. 59 No. 1, 2025
pp. 134-154
© Emerald Publishing Limited
2514-9288
DOI 10.1108/DTA-11-2023-0804
adoption by healthcare community and health system providers (Ayaz et al., 2021).
Moreover, recent legislative and regulatory initiatives (e.g. the 21st Century Cures Act of
United States (Gabay, 2017) or the German Medical Informatics Initiative (Semler et al., 2018))
promoted the dissemination of FHIR (Jones et al., 2021).
The massive accumulation of large-scale data in recent decades led to the growing interest
in the secondary use of clinical data, being secondary use associated with purposes other
than individual care, such as research, improvement of quality and safety of care, financial
management and education (Safran et al., 2007;Robertson et al., 2016). The secondary use of
clinical data presents several advantages (Safran et al., 2007), since data (1) are readily
available, (2) have a high level of generalization due to the real-life setting in which they are
collected that facilitates representative sampling while simultaneously increasing external
validity, (3) can be aggregated from different sites, which facilitates obtaining large samples
(Elger et al., 2010) and (4) can be used for retroactive conduct of interventional studies that
cannot be conducted prospectively due to ethical reasons (Lee, 2017). Moreover, if the
protection of personal data is guaranteed, patients can contribute with their clinical data
without being exposed to immediate risks (Setyawan et al., 2021).
While the benefits of secondary use of clinical data are relevant, some barriers must be
considered (Van Panhuis et al., 2014), namely (1) motivational (e.g. unavailability to share
information), (2) economic (e.g. the value of clinical data), (3) legal (e.g. privacy protection)
and (4) political (e.g. lack of trust) barriers. These barriers are exacerbated in the context of
rare disease research, where the patients are easily identifiable because the datasets are small
and the integration of multiple data modalities (e.g. genomic, phenotypical, demographic or
medical history) is often required. This means that the purposes and circumstances of
secondary use of clinical data still raise many ethical, legal and regulatory issues and
patients’ privacy must be guaranteed according to international and national legislation and
regulation (Tayefi et al., 2021).
In addition to these barriers, there are also technical issues, resulting from the lack of
widely adopted sharing protocols and the need for harmonized clinical data structures based
on existing forms and medical concepts (Krumm et al., 2014). In this respect, although FHIR
was developed to meet clinical interoperability needs, its resources, data types and extension
mechanisms are seen as able to bridge the gap between applications of patient data to
support direct clinical care and secondary use of clinical data (Safran et al., 2007).
Due to the growing popularity of FHIR, some researchers have authored review articles to
assess the general use of FHIR in the implementation of applications to support healthcare
provision (Lehne et al., 2019;Dullabh et al., 2020;Ayaz et al., 2021;Setyawan et al., 2021;Balch
et al., 2023;Montazeri et al., 2023;Nan and Xu, 2023). Moreover, in terms of secondary use of
clinical data, Vorisek et al. (2022) and Pav~
ao et al. (2023) identified FHIR implementations in
health research and Duda et al. (2022) reviewed published literature, federally funded project
databases and application websites to identify FHIR-based applications to support clinical
trials.
The motivation of this study was to complement the aforementioned reviews by
providing a systematic review of existing literature to identify and categorize applications
using FHIR to support activities outside of direct healthcare provision, namely the use of
FHIR in interventional clinical trials, including the ones conducted to determine the
efficiency and safety of new drugs, treatments or devices or to support the various purposes
of the secondary use of clinical data, as defined by American Medical Informatics
Association (AMIA) (i.e. “analysis, research, quality and safety measurement, public health,
payment, provider certification or accreditation, marketing, and other business applications”
(Safran et al., 2007)). Given the importance of the clinical research and the remarkable
potential of secondary use of clinical data, this study can assist researchers, experts,
Data
Technologies and
Applications
135
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