ArticleCritical care (London, England)2021
The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients.
Article in Critical care (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Respiratory physiology after resupination following prone ventilation to predict 28-day mortality in mechanically ventilated patients: a machine learning analysis.Scientific reports · 2026Article
- National centre for healthy ageing data platform: Developing a core set of research data from hospital electronic health record systems: A modified Delphi approach.Health information management : journal of the Health Information Management Association of Australia · 2026Article
- Preparing for future pandemics: Automated intensive care electronic health record data extraction to accelerate clinical insights.Journal of intensive medicine · 2025Article
- The role of circular RNA in immune response to tuberculosis and its potential as a biomarker and therapeutic target.Frontiers in immunology · 2025Review
- Creating a data warehouse to support monitoring of NSQHS blood management standard from EMR data.BMC medical informatics and decision making · 2024Article
- The role of Open Access Data in democratizing healthcare AI: A pathway to research enhancement, patient well-being and treatment equity in Andalusia, Spain.PLOS digital health · 2024Article
- Algor-ethics: charting the ethical path for AI in critical care.Journal of clinical monitoring and computing · 2024Article
- Data Lake, Data Warehouse, Datamart, and Feature Store: Their Contributions to the Complete Data Reuse Pipeline.JMIR medical informatics · 2024Article
- Reinforcement learning for intensive care medicine: actionable clinical insights from novel approaches to reward shaping and off-policy model evaluation.Intensive care medicine experimental · 2024Article
- Which decisions affect cohort distribution in COVID-19 data analytics?AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Clinical Data Warehousing: A Scoping Review.Journal of the Society for Clinical Data Management · 2024Article
- Review
- Developing a linked electronic health record derived data platform to support research into healthy ageing.International journal of population data science · 2023Article
- Prediction of in-hospital hypokalemia using machine learning and first hospitalization day records in patients with traumatic brain injury.CNS neuroscience & therapeutics · 2023Article
- Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning.Annals of intensive care · 2022Article
- Detection of COVID-19 using deep learning techniques and classification methods.Information processing & management · 2022Article
- Modern Learning from Big Data in Critical Care: Primum Non Nocere.Neurocritical care · 2022Article
- ERS International Congress 2021: highlights from the Respiratory Intensive Care Assembly.ERJ open research · 2022Article
- Dynamic prediction of mortality in COVID-19 patients in the intensive care unit: A retrospective multi-center cohort study.Intelligence-based medicine · 2022Article
- Critical Care Database Comprising Patients With Infection.Frontiers in public health · 2022Article
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57 authors.
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Abstract
backgroundThe Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients.
methodsA nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract-transform-load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers.
resultsOut of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive.
conclusionsIn this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.
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