FHIR in the healthcare sector: Basics, use and challenges
Knowledge database Technology Integration & interoperability A.1: Tech-FoundationThe digital exchange of healthcare data is still associated with numerous challenges, such as fragmented IT systems, a lack of standards and an unclear semantic basis. The international standard FHIR (Fast Healthcare Interoperability Resources) offers a technical framework that could address these problems. The following article analyses the potential and challenges of FHIR and shows how a step-by-step implementation can contribute to the better use of healthcare data.
Problem description, research question and relevance
Interoperability in the healthcare sector is a key challenge, as many hospital information systems (HIS) use proprietary interfaces and data is often not structured or standardised. This makes it difficult to exchange patient data across sectors and leads to inefficient work processes. For example, data cannot be transferred between different hospitals without manual adjustments, which causes delays in treatment (Vorisek et al., 2022).
Fast Healthcare Interoperability Resources (FHIR) is a standard developed by Health Level Seven International (HL7) for the digital exchange of healthcare information(Fhir.org, 2025). FHIR is based on modular "resources" that incorporate health data in a standardised, easily accessible and usable form via web technologies (Saripalle et al., 2019). By using RESTful APIs, JSON and XML, FHIR enables flexible, fast and secure data exchange between different healthcare systems (Ayaz et al., 2021).
While Germany already relies extensively on FHIR with legal initiatives such as the electronic patient file (ePA) and the telematics infrastructure(ISiK | Gematik, 2025), FHIR has so far only been used to a limited extent in Switzerland. The electronic patient dossier (EPD) does not use FHIR as an end-to-end standard, but only for specific applications such as the electronic vaccination record and medication plans (eHealth Suisse, 2024). This suggests that there may still be potential for improved interoperability in Switzerland.
FHIR addresses several key problems in the Swiss healthcare system. Many hospitals work with fragmented IT systems that do not enable seamless data exchange. In addition, the diversity of coding systems such as ICD-10, SNOMED CT or LOINC makes standardised semantic interoperability difficult (Meredith et al., 2023). The infrastructure poses a further challenge, as many facilities are still based on legacy systems that are difficult to adapt to modern standards. Finally, the use of health data for research and AI in Switzerland lags behind the possibilities, despite initiatives such as Digisanté calling for greater standardisation and use of interoperable platforms (FOPH, 2024). The use of FHIR can address these problems by creating a standardised, flexible and interoperable infrastructure for data exchange.
Methods and procedures in the project
The study is based on a systematic analysis of current scientific literature, including several studies on the implementation and use of HL7 FHIR in various contexts. Best practices, challenges and potentials of the standard were recorded and analysed with regard to their relevance for the SHIFT sub-project A.1, the Tech-Foundation.
Results and findings
- Fragmented IT systems and lack of interoperability: Many hospitals in Switzerland use proprietary systems that make seamless communication difficult. FHIR relies on REST APIs and standardised resources to simplify data exchange and enable the integration of different systems (Nan & Xu, 2023).
- Different data formats and coding systems: The variety of terminologies such as ICD-10, SNOMED CT or LOINC makes semantic interoperability difficult. The use of the FOXS stack (FHIR, openEHR, XDS, SNOMED CT) could create a consistent, interoperable data structure and facilitate exchange between institutions (Meredith et al., 2023)
- Legacy systems and technological infrastructure: Many healthcare facilities in Switzerland work with outdated IT systems that are difficult to convert to modern standards. In Germany, FHIR is already integrated into national programmes, which promotes its dissemination(ISiK | Gematik, 2025).
- Swiss challenges and development potential: The EPR is a central component of Switzerland's digital health strategy, but has so far only been implemented slowly (eHealth Suisse, 2024). The integration of FHIR could help to improve the use of the EPR and make it more interoperable with existing systems.
- Lack of use of health data for research and AI: The availability and use of health data for research and AI applications falls short of the potential in Switzerland. According to the Digisanté initiative, the potential of structured and interoperable health data is not being sufficiently utilised (FOPH, 2024).
Recommendations for practice
- Define an interoperability strategy: It would be advisable for healthcare organisations to develop a clear strategy for FHIR implementation that takes into account existing systems and gradually builds interoperability (Nan & Xu, 2023).
- Further develop the framework for interoperability: In order to connect siloed IT systems, legal frameworks should be created that include the obligation to use interoperable standards and the homologation of software systems. This could accelerate the integration of FHIR in the healthcare sector and support the digital transformation (eHealth Suisse, 2025)
- Use FHIR for real-time data processing: The use of FHIR for real-time data processing in emergency and monitoring systems can improve patient care, especially in the field of Internet of Medical Things (IoMT) (S. Rubí & L. Gondim, 2019).
- Use FOXS stack as a complementary solution: Combining FHIR with openEHR, IHE XDS and SNOMED CT could strengthen semantic and structural interoperability and enable more flexible data exchange (Meredith et al., 2023).
- Encourage participation in interoperability tests such as the Digital Health Projectathon: Events such as the Digital Health Projectathon 2025 provide a platform for practical testing and further development of FHIR implementations. Participation makes it possible to test systems for interoperability and improve technical integration(Digital Health Projectathon 2025 - Test Event, 2025).
- Optimised use of health data and AI applications: Greater standardisation as well as the targeted use of FHIR could facilitate the exchange and processing of large amounts of data. This could particularly advance research areas such as predictive analyses, personalised medicine and clinical decision support. The combination of FHIR with big data technologies and AI models can help to improve the quality of medical care and promote innovation in the healthcare sector (BAG, 2024).
Literature and other sources
Ayaz, M., Pasha, M. F., Alzahrani, M. Y., Budiarto, R., & Stiawan, D. (2021). The Fast Health Interoperability Resources (FHIR) Standard: Systematic Literature Review of Implementations, Applications, Challenges and Opportunities. JMIR Medical Informatics, 9(7), e21929. doi.org/10.2196/21929
FOPH, B. for G. (2024, June 12). DigiSanté: Promoting digital transformation in the healthcare sector.www.bag.admin.ch/dam/bag/de/dokumente/nat-gesundheitspolitik/foerderprogramme/DigiSant--F-rderung-der-digitalen-Transformation-im-Gesundheitswesen/medienmitteilung-ueberweisung-finanzierungskredit-digisante.pdf.download.pdf/Bundesrat%20will%20mit%20DigiSant%C3%A9%20die%20Digitalisierung%20im%20Gesundheitswesen%20beschleunigen.pdf
Digital Health Projectathon 2025 test event. (2025). www.e-health-suisse.ch
eHealth Suisse. (2024, July 3). eHealth Suisse.www.e-health-suisse.ch
eHealth Suisse. (2025). Strategic foundations-Humans at the centre.www.e-health-suisse.ch
Fhir.org. (2025, March 13). FHIR. fhir.org/about.html
ISiK | gematik. (2025, March 13). www.gematik.de/anwendungen/isik
Meredith, J., Whitehead, N., & Dacey, M. (2023). Aligning Semantic Interoperability Frameworks with the FOXS Stack for FAIR Health Data. Methods of Information in Medicine, 62(Suppl 1), e39-e46. doi.org/10.1055/a-1993-8036
Nan, J., & Xu, L.-Q. (2023). Designing Interoperable Health Care Services Based on Fast Healthcare Interoperability Resources: Literature Review. JMIR Medical Informatics, 11, e44842. doi.org/10.2196/44842
S. Rubí, J. N., & L. Gondim, P. R. (2019). IoMT Platform for Pervasive Healthcare Data Aggregation, Processing, and Sharing Based on OneM2M and OpenEHR. Sensors (Basel, Switzerland), 19(19), 4283. doi.org/10.3390/s19194283
Saripalle, R., Runyan, C., & Russell, M. (2019). Using HL7 FHIR to achieve interoperability in patient health record. Journal of Biomedical Informatics, 94, 103188. doi.org/10.1016/j.jbi.2019.103188
Vorisek, C. N., Lehne, M., Klopfenstein, S. A. I., Mayer, P. J., Bartschke, A., Haese, T., & Thun, S. (2022). Fast Healthcare Interoperability Resources (FHIR) for Interoperability in Health Research: Systematic Review. JMIR Medical Informatics, 10(7), e35724. doi.org/10.2196/35724