ArticleJMIR medical informatics2025
Lessons Learned From Building a Data Platform for Longitudinal, Analytical Use Cases and Scaling to 77 German Hospitals: Implementation Report.
Article in JMIR medical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- GOLD-concordant inhaled maintenance therapy at hospital discharge after hospitalisation for severe COPD exacerbation: a multicentre retrospective observational study.The Lancet regional health. Europe · 2026Article
- Extracting Medical Information From Unstructured Clinical Text Using Large Language Models to Enhance Health Care Interoperability: Proof-of-Concept Study.Journal of medical Internet research · 2026Article
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Authors and funding
8 authors.
Funding
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Abstract
Background: Increasing adoption of electronic health records (EHRs) enables research on real-world data. In Germany, this has been limited to university hospitals, and data from acute care hospitals below the university level are lacking. To address this, we used established design patterns to build a data platform that aggregates and standardizes pseudonymized EHR data with patients' consent. Objective: We report on the design and implementation of the research platform, as well as patient participation and lessons learned during the scaling of the platform, to incorporate real-world data (with participant consent) from 77 hospitals into a unified data lake. Methods: Due to variations in EHR adoption, IT infrastructure, software vendors, interface availability, and regulatory requirements, we used an agile development cycle that involves constant, incremental standardization of data. We implemented a layered lambda infrastructure built on Apache Hadoop. Decentralized connectors ensured data minimization and pseudonymization. Unlabelled: We successfully scaled our data model both vertically and horizontally in 77 hospitals. However, we encountered issues during the scaling of real-time data pipelines and IHE (Integrating the Healthcare Enterprise) interfaces. During the first 2 years, patients were asked to consent to secondary data use 1,475,244 times during inpatient admission. We registered 1,023,633 broad instances of consent (consent rate 70.2%). Conclusions: Patients are generally willing to provide consent for secondary use of their data, but obtaining consent requires considerable effort. Building a research data platform is not an end goal, but rather a necessary step in collecting and standardizing longitudinal data to enable research on real-world data. Through the combination of agile development, phased rollouts, and very high levels of automation, we have been able to achieve fast turnaround times for incorporating user feedback and are constantly improving data quality and standardization.
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Registered trials
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 Socratic graph.