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ArticleBMC medical informatics and decision making2026

A distributed analysis approach for pharmacovigilance data from electronic medical records in German university hospitals: the POLAR_MI ETL Pipeline.

Miriam Kesselmeier, Torsten Thalheim, Florian Schmidt, Thomas Peschel, Julia Palm, Alexander Strübing, André Medek, Jens Przybilla, Anna Maria Wermund, Renke Maas and 12 more

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Article in BMC medical informatics and decision making, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

22 authors.

Miriam KesselmeierInstitute of Medical Statistics, Computer and Data Sciences (IMSID), Jena University Hospital-Friedrich Schiller University Jena, Jena, Germany. miriam.kesselmeier@med.uni-jena.de.ORCID http://orcid.org/0000-0001-6462-2579
Torsten ThalheimInterdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0001-5489-7405
Florian SchmidtInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0003-2027-8213
Thomas PeschelInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0009-0007-5145-7798
Julia PalmInstitute of Medical Statistics, Computer and Data Sciences (IMSID), Jena University Hospital-Friedrich Schiller University Jena, Jena, Germany.ORCID http://orcid.org/0000-0003-1568-5893
Alexander StrübingInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0001-5151-7665
André MedekMedical & Scientific Technology Development & Coordination (MWTek), University Hospital Bonn, Bonn, Germany.ORCID http://orcid.org/0000-0003-0569-2395
Jens PrzybillaInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany.
Anna Maria WermundDepartment of Clinical Pharmacy, Institute of Pharmacy, University of Bonn, Bonn, Germany.ORCID http://orcid.org/0000-0002-5735-0197
Renke MaasInstitute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.ORCID http://orcid.org/0000-0002-5498-9761
Steffen HärterichHospital Pharmacy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.ORCID http://orcid.org/0000-0003-2395-1522
Louisa RedekerDepartment of Clinical Pharmacology, School of Medicine, Faculty of Health, Witten/Herdecke University, Witten, Germany.ORCID http://orcid.org/0000-0003-4150-9084
Martin FederbuschInstitute for Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Medical Center Leipzig, Leipzig, Germany.ORCID http://orcid.org/0000-0002-1126-5763
Daniel SteinbachInstitute for Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Medical Center Leipzig, Leipzig, Germany.ORCID http://orcid.org/0000-0003-2364-598X
Jan GewehrBusiness Division for Information Technology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.ORCID http://orcid.org/0009-0006-6453-9082
Marcus WurlitzerBusiness Division for Information Technology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.ORCID http://orcid.org/0000-0002-1911-4572
Andrea RiedelErlangen University Hospital, Medical Center for Information and Communication Technology, Erlangen, Germany.ORCID http://orcid.org/0009-0006-9389-9482
Frank MeinekeInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0002-9256-7543
Daniel NeumannInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0002-4639-5189
André Scherag *Institute of Medical Statistics, Computer and Data Sciences (IMSID), Jena University Hospital-Friedrich Schiller University Jena, Jena, Germany.ORCID http://orcid.org/0000-0002-9406-4704
Markus Loeffler *Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0002-0424-9933
POLAR_MI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe cooperative project "POLypharmacy, drug interActions and Risks" (POLAR_MI) of the Medical Informatics Initiative Germany (MII) aimed at detecting medication-related risks attributed to polymedication in adult patients from German university hospitals. Here, we report technological challenges and solutions to undertake this large-scale multicentre project relying on routine healthcare data stored and processed by the data integration centres, which were recently established at the German university hospitals.

methodsWe developed and implemented a two-step, privacy-preserving, distributed analysis approach to analyse clinical routine healthcare data relying on the internationally balloted MII HL7

resultsUsing an iterative procedure between data integration centres and the cross-institutional analysis team, we overcame many challenges and established the "POLAR_MI ETL Pipeline". These challenges originated from the heterogeneity of the data integration centres and the IT infrastructure of the related university hospitals including their local hospital information system. Applying our pipeline, we analysed data from ten centres on nearly 800,000 encounters from about 500,000 patients.

conclusionsFor the first time within the MII infrastructure, we demonstrated that a project on routine healthcare data is feasible using a distributed analysis approach based on the recently established network of data integration centres in Germany. We describe an approach to obtain a valuable and insightful overview of health risks in routine healthcare and share the related code. Moreover, we propose improvements to the ETL process for future distributed analyses. Finally, our data-related challenges and solutions can be adapted to other healthcare settings (in other countries and initiatives, respectively) as long as data integration centres equivalents and a common data format/model are available.

trial registrationPOLAR_MI was registered on 27/11/2020 in the "HMA-EMA Catalogues of real-world data sources and studies" (EU PAS number: EUPAS36582).

Indexed as

Electronic Health RecordsHospitals, UniversityPharmacovigilanceData AnalyticsGermanyHumansData integrationDistributed analysisDistributed computationElectronic health recordsElectronic medical recordsETLExtract transform loadHospital information systemLessons learnedMeta-analysis

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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.