Evidence map›Paper›PMID 41576013›Full record

ArticlePloS one2026

Challenges and solutions in determining urolithiasis caseloads using the digital infrastructure of a clinical data warehouse.

Martin Schönthaler, Noah Hempen, Maria Weymann, Maximilian Ferry von Bargen, Maximilian Glienke, Antonia Elsässer, Max Behrens, Harald Binder, Nadine Binder

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Martin SchönthalerDepartment of Urology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Noah HempenInstitute of General Practice/Family Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0009-0007-4379-5973
Maria WeymannInstitute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Maximilian Ferry von BargenDepartment of Urology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Maximilian GlienkeDepartment of Urology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Antonia ElsässerDepartment of Urology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Max BehrensInstitute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Harald BinderInstitute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Nadine BinderInstitute of General Practice/Family Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo provide more evidence in urolithiasis research, we have established the German Nationwide Register for RECurrent URolithiasis (RECUR) using local clinical data warehouses (CDWH). For RECUR and other registers relying on digitalized clinical data, it is crucial to ensure the data's reliability for answering scientific questions. In this work, we aim to compare the results of different CDWH-based queries on urolithiasis cases next to manual case extraction from the primary source.

methodsSources for data extraction included the Medical Center University of Freiburg (MCUF) hospital information system (HIS), MCUF performance data (a clinical data set with merged data from patients including data from various time points throughout their treatment), and MCUF reimbursement data. We extracted data on caseloads in urolithiasis algorithmically (performance and reimbursement data) and compared those to a reference group compiled of manually extracted data from the local HIS and algorithmically extracted data.

resultsAlgorithmic extraction based on performance data resulted in correct and complete case identification as compared to the reference group. The case numbers from manual extraction from HIS data and algorithmic extraction from reimbursement data differed by 14% and 12%, respectively. The reasons for deviations in HIS data included human errors and a lack of data availability from different wards. Deviations in reimbursement data arose primarily due to the merging of cases in the context of reimbursement mechanisms. As the CDWH at MCUF is part of the German Medical Informatics Initiative (MII), the results can be transferred to other medical centers with similar CDWH structure.

conclusionsThe current study provides firm evidence of the importance of clearly defining a study's target variable, e.g., urolithiasis cases, and a thorough understanding of the data sources and modes used to extract the target data. Our work clearly shows that, depending on various data sources, a case is not a case is not a case.

Indexed as

UrolithiasisAlgorithmsDatabases, FactualGermanyHumansRegistries

Identifiers

PMID41576013
PMCPMC12829838

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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.