ArticleMedizinische Klinik, Intensivmedizin und Notfallmedizin2022
[The way to routine data from 16 emergency departments for cross-sectoral health services research : Experiences, challenges and solution approaches from the extraction of pseudonymous data for the INDEED project].
Article in Medizinische Klinik, Intensivmedizin und Notfallmedizin, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Article
- Migration context of emergency department patients and patterns of their in- and outpatient healthcare utilization - analysis of three INDEED study centers in Berlin.BMC public health · 2025Article
- Data-driven segmentation of type 2 diabetes mellitus patients: an observational study on health care utilisation prior to an emergency department visit in Germany.Frontiers in medicine · 2025Article
- Observational
- [Nationally standardized broad consent in practice: initial experiences, current developments, and critical assessment].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024Article
- [The impact of primary data quality and interoperability on the analysis of real-world data].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024Review
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn Germany there is currently no health reporting on cross-sectoral care patterns in the context of an emergency department care treatment. The INDEED project (Utilization and trans-sectoral patterns of care for patients admitted to emergency departments in Germany) collects routine data from 16 emergency departments, which are later merged with outpatient billing data from 2014 to 2017 on an individual level.
aimThe methodological challenges in planning of the internal merging of routine clinical and administrative data from emergency departments in Germany up to the final data extraction are presented together with possible solution approaches.
methodsData were selected in an iterative process according to the research questions, medical relevance, and assumed data availability. After a preparatory phase to clarify formalities (including data protection, ethics), review test data and correct if necessary, the encrypted and pseudonymous data extraction was performed.
resultsData from the 16 cooperating emergency departments came mostly from the emergency department and hospital information systems. There was considerable heterogeneity in the data. Not all variables were available in every emergency department because, for example, they were not standardized and digitally available or the extraction effort was judged to be too high.
conclusionRelevant data from emergency departments are stored in different structures and in several IT systems. Thus, the creation of a harmonized data set requires considerable resources on the part of the hospital as well as the data processing unit. This needs to be generously calculated for future projects.
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