ArticleApplied clinical informatics2023
"fhircrackr": An R Package Unlocking Fast Healthcare Interoperability Resources for Statistical Analysis.
Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Benchmarking Fast Healthcare Interoperability Resources-Based Analytics: Quantitative Study of RESTful Server Queries and Big Data Engines.JMIR medical informatics · 2026Article
- Interpretable machine learning models for predicting perioperative myocardial injury in non-cardiac surgery.European heart journal. Digital health · 2026Article
- [Evidence generation and methodological consultation by the project "EVAluation research based on data from routine clinical care 4 the Medical Informatics Initiative" (EVA4MII)].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2026Review
- A FHIR-Powered Python Implementation of the SENECA Algorithm for Sepsis Subtyping.Applied clinical informatics · 2025Article
- Leveraging Interoperable Electronic Health Record (EHR) Data for Distributed Analyses in Clinical Research: Technical Implementation Report of the HELP Study.JMIR medical informatics · 2025Article
- SQL on FHIR - Tabular views of FHIR data using FHIRPath.NPJ digital medicine · 2025Article
- Leveraging electronic medical records to evaluate a computerized decision support system for staphylococcus bacteremia.NPJ digital medicine · 2025Article
- Design and validation of an automated healthcare-integrated biobanking algorithm for identification of advanced chronic kidney disease.Computational and structural biotechnology journal · 2025Article
- [Interoperability Working Group: core dataset and information systems for data integration and data exchange in the Medical Informatics Initiative].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024Article
- FHIR-PYrate: a data science friendly Python package to query FHIR servers.BMC health services research · 2023Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe growing interest in the secondary use of electronic health record (EHR) data has increased the number of new data integration and data sharing infrastructures. The present work has been developed in the context of the German Medical Informatics Initiative, where 29 university hospitals agreed to the usage of the Health Level Seven Fast Healthcare Interoperability Resources (FHIR) standard for their newly established data integration centers. This standard is optimized to describe and exchange medical data but less suitable for standard statistical analysis which mostly requires tabular data formats.
objectivesThe objective of this work is to establish a tool that makes FHIR data accessible for standard statistical analysis by providing means to retrieve and transform data from a FHIR server. The tool should be implemented in a programming environment known to most data analysts and offer functions with variable degrees of flexibility and automation catering to users with different levels of FHIR expertise.
methodsWe propose the fhircrackr framework, which allows downloading and flattening FHIR resources for data analysis. The framework supports different download and authentication protocols and gives the user full control over the data that is extracted from the FHIR resources and transformed into tables. We implemented it using the programming language R [1] and published it under the GPL-3 open source license.
resultsThe framework was successfully applied to both publicly available test data and real-world data from several ongoing studies. While the processing of larger real-world data sets puts a considerable burden on computation time and memory consumption, those challenges can be attenuated with a number of suitable measures like parallelization and temporary storage mechanisms.
conclusionThe fhircrackr R package provides an open source solution within an environment that is familiar to most data scientists and helps overcome the practical challenges that still hamper the usage of EHR data for research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.