The Use of FHIR in Digital Health – A Review of the Scientific Literature
Open accessAbstract
Fast Healthcare Interoperability Resources (FHIR), an international standard for exchanging digital health data, is increasingly used in health information technology. FHIR promises to facilitate the use of electronic health records (EHRs), enable mobile technologies and make health data accessible to large-scale analytics. Until now, there is no comprehensive review of scientific articles about FHIR and its use in digital health. Here, we aim to address this gap and provide an overview of the main topics associated with FHIR in the scientific literature. For this, we screened all articles about FHIR on Web of Science and PubMed and identified the main topics discussed in these articles. We also explored the temporal trend and geography of publications and performed some basic text mining on article abstracts. We found that the topics most commonly discussed in the articles were related to data models, mobile and web applications as well as medical devices. Since its introduction, the number of publications about FHIR have steadily increased until 2017, indicating an increasing popularity of FHIR in healthcare (in 2018, publication numbers remained stable). In sum, our study provides an overview of the scientific literature about FHIR and its current use in digital health.
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Lehne et al [91] only reviewed articles related to a general introduction of FHIR, without providing in-depth analysis on either FHIR or articles mentioning FHIR.
“For example, Lehne et al [91] only reviewed articles related to a general introduction of FHIR, without providing in-depth analysis on either FHIR or articles mentioning FHIR.”
From The Fast Health Interoperability Resources (FHIR) Standard: Systematic Literature Review of Implementations, Applications, Challenges and Opportunities (2021) · cites this paper as [91]
The previous review by Lehne et al could not fully introduce and address various aspects of FHIR, such as challenges, applications, goals, mapping, and implementation models.
“Based on a thorough reading, we concluded that this previous review could not fully introduce and address various aspects of FHIR, such as challenges, applications, goals, mapping, and implementation models.”
From The Fast Health Interoperability Resources (FHIR) Standard: Systematic Literature Review of Implementations, Applications, Challenges and Opportunities (2021) · cites this paper as [91]
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- Authors
- Moritz, L., Sandra, L., Paulina, V. F. G. I., & Sylvia, T.
- Venue
- Studies in Health Technology and Informatics
- Publisher
- IOS Press
- Published
- 2019
- Volume
- 267
- Pages
- 52-58
- ISSN
- 0926-9630 (ISSN-L)
- OpenAlex
- W2981115805
- Cited by
- 88
- References
- 0
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 15 · 2023: 18 · 2022: 11 · 2021: 20 · 2020: 11
- FWCI
- 26.27
- Type
- book chapter
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Studies in health technology and informatics (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (submittedVersion)
- PubMed
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Keywords
- FHIR, Fast Healthcare Interoperability Resources, health data interoperability, electronic health records, digital health, health information technology, data model, mobile health apps, web application, medical devices, health data analytics, publication trends
- MeSH terms
- Medical Informatics, PubMed, Data Mining, Electronic Health Records
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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