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The challenges of replication: A worked example of methods reproducibility using electronic health record data
Richard Williams1,2, Thomas Bolton3, David Jenkins1
1Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.
Plos One
|July 18, 2025
Summary
Reproducing studies with electronic health records (EHR) is hard. Recommendations for trusted research environments (TREs) and secure data environments (SDEs) aim to improve data and methods reproducibility for EHR research.
Area of Science:
- Health Informatics
- Biostatistics
- Observational Research
Background:
- Reproducibility is crucial in science, but replicating observational studies using electronic health record (EHR) data presents unique challenges.
- Difficulties arise from data access complexities, variations in EHR systems, and potential unaddressed confounding variables.
Purpose of the Study:
- To identify barriers to methods reproducibility in replication studies utilizing EHR data.
- To propose actionable recommendations for enhancing the reproducibility of EHR-based research.
Main Methods:
- Replicated a study on diabetes and COVID-19 hospitalization risk using EHR data from NHS England's Secure Data Environment (SDE).
- Compared findings and methods with an original study using data from Greater Manchester.
- Documented and categorized challenges encountered in Trusted Research Environments (TREs) and SDEs.
Main Results:
- Identified several challenges to methods reproducibility stemming from minor differences in TRE/SDEs and data sources.
- Proposed recommendations including improved machine-readable metadata, standardized governance for federated analysis, mandatory code sharing, and dedicated support structures.
- Introduced the concept of "data reproducibility" as a distinct research area.
Conclusions:
- Data reproducibility remains a significant challenge even with complete code sharing.
- Implementing the proposed recommendations can lower barriers to replication studies, thereby increasing the value of EHR observational research.
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