ORIGINAL RESEARCH article
Front. Med.
Sec. Regulatory Science
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1661091
This article is part of the Research TopicPushing Boundaries in EHR Implementation and Innovation through Advanced Digital Health TechnologiesView all 6 articles
Preparing for the European Health Data Space: An Open-Source Compiler for Fast, Transparent, and Portable Health Data Transformations
Provisionally accepted- 1AIT Austrian Institute of Technology, Vienna, Austria
- 2Institute of Neural Engineering, Graz University of Technology, Graz, Austria
- 3ELGA GmbH, Vienna, Austria
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Abstract Introduction: Healthcare systems generate vast amounts of data in diverse and often incompatible formats. Efficient conversion between these formats is essential to ensure interoperability and enable secondary data use, particularly in the context of the European Health Data Space (EHDS) and the proposed Austrian Health Data Donation Space (AHDDS). While standards such as HL7 FHIR aim to facilitate interoperability, inconsistencies in implementation persist. Electronic Health Record (EHR) providers, including Austria's ELGA, continue to face challenges in this area. The FHIR Mapping Language (FML) offers a promising solution for format translation, but current tools for executing FML mappings are limited, especially in terms of processing speed. To address this gap, there is a pressing need for a compiler that translates FML mappings into efficient, executable code. Materials & Methods: We developed the Mapping Language Compiler for Health Data (MaLaC-HD), which compiles FML code into Python. To assess performance, we benchmarked the compiler using a large ELGA document on a typical end-user device, comparing execution speed with existing FML tools. Baseline overhead was measured using an empty mapping. Conformance was manually evaluated by comparing the output of a wide range of example mappings and input data against the Java reference implementation. Additionally, we analyzed the structure and correctness of the generated Python code to assess functional completeness. Results: After adjusting for overhead, MaLaC-HD achieved execution speeds nearly 100 times faster than existing tools. The output closely matched that of the reference implementation, with only minor discrepancies. The generated Python code met all functional requirements and demonstrated the compiler's ability to support complex transformations. MaLaC-HD is publicly available under the LGPL license. Conclusion: MaLaC-HD can serve a wide array of use cases and has the potential to integrate with existing platforms for secondary data use to support large-scale health data research across Europe and beyond. MaLaC-HD could provide the EHR community with a powerful, efficient tool for accelerating data transformation, an essential capability for the success of the EHDS initiative.
Keywords: Electronic Health Record (EHR), interoperability, Standards, data transformation, FHIR5, FHIR Mapping Language (FML), MaLaC-HD, European Health Data Space (EHDS)
Received: 07 Jul 2025; Accepted: 01 Sep 2025.
Copyright: © 2025 Beyer, Tanjga, Kleinoscheg, Hayn, Donsa, Kreiner and Schreier. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Stefan Beyer, AIT Austrian Institute of Technology, Vienna, Austria
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.