Leveraging Interoperable Electronic Health Record (EHR) Data for Distributed Analyses in Clinical Research: Technical Implementation Report of the HELP Study

The HELP study highlights challenges and opportunities in leveraging EHR data for clinical research, particularly in the absence of mandatory data standards and resource-intensive data harmonization efforts. Despite limitations in data availability and quality, progress in digitization and interoperability frameworks offers hope for future improvements. Lessons learned from this study can inform the development of standardized methodologies and infrastructures for sustainable EHR data integration in research.

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Publication Details

Journal
JMIR Medical Informatics
Published
2025-05-15
DOI
https://doi.org/10.2196/68171
Citations
2
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
8.34
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article

Leveraging Interoperable Electronic Health Record (EHR) Data for Distributed Analyses in Clinical Research: Technical Implementation Report of the HELP Study

André Scherag, Julia Palm, Kutaiba Saleh, Danny Ammon
2 citations
JMIR Medical Informatics
Scientific Computing and Data Management
8.34
article

Leveraging Interoperable Electronic Health Record (EHR) Data for Distributed Analyses in Clinical Research: Technical Implementation Report of the HELP Study

André Scherag, Julia Palm, Kutaiba Saleh, Danny Ammon
article en
2 citations

Abstract

The HELP study highlights challenges and opportunities in leveraging EHR data for clinical research, particularly in the absence of mandatory data standards and resource-intensive data harmonization efforts. Despite limitations in data availability and quality, progress in digitization and interoperability frameworks offers hope for future improvements. Lessons learned from this study can inform the development of standardized methodologies and infrastructures for sustainable EHR data integration in research.

JMIR Medical InformaticsVol. 13
Jena University Hospital (DE)
Openalex Percentile: Top 3%
Scientific Computing and Data Management
8.34
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