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Multicenter Study
. 2021 Aug 23;25(1):304.
doi: 10.1186/s13054-021-03733-z.

The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

Lucas M Fleuren  1 , Tariq A Dam  2 , Michele Tonutti  3 , Daan P de Bruin  3 , Robbert C A Lalisang  3 , Diederik Gommers  4 , Olaf L Cremer  5 , Rob J Bosman  6 , Sander Rigter  7 , Evert-Jan Wils  8 , Tim Frenzel  9 , Dave A Dongelmans  10 , Remko de Jong  11 , Marco Peters  12 , Marlijn J A Kamps  13 , Dharmanand Ramnarain  14 , Ralph Nowitzky  15 , Fleur G C A Nooteboom  16 , Wouter de Ruijter  17 , Louise C Urlings-Strop  18 , Ellen G M Smit  19 , D Jannet Mehagnoul-Schipper  20 , Tom Dormans  21 , Cornelis P C de Jager  22 , Stefaan H A Hendriks  23 , Sefanja Achterberg  24 , Evelien Oostdijk  25 , Auke C Reidinga  26 , Barbara Festen-Spanjer  27 , Gert B Brunnekreef  28 , Alexander D Cornet  29 , Walter van den Tempel  30 , Age D Boelens  31 , Peter Koetsier  32 , Judith Lens  33 , Harald J Faber  34 , A Karakus  35 , Robert Entjes  36 , Paul de Jong  37 , Thijs C D Rettig  38 , Sesmu Arbous  39 , Sebastiaan J J Vonk  3 , Mattia Fornasa  3 , Tomas Machado  3 , Taco Houwert  3 , Hidde Hovenkamp  3 , Roberto Noorduijn-Londono  3 , Davide Quintarelli  3 , Martijn G Scholtemeijer  3 , Aletta A de Beer  3 , Giovanni Cina  3 , Martijn Beudel  40 , Willem E Herter  3 , Armand R J Girbes  2 , Mark Hoogendoorn  41 , Patrick J Thoral  2 , Paul W G Elbers  2
Affiliations
Multicenter Study

The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

Lucas M Fleuren et al. Crit Care. .

Abstract

Background: The 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.

Methods: A 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.

Results: Out 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.

Conclusions: In 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.

Keywords: Big data; COVID-19; Data sharing; Database.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Overview of the Dutch Data Warehouse pipeline. Overview of the collaboration to realize the Dutch Data Warehouse. EHR electronic health record, ETL extract–transform–load
Fig. 2
Fig. 2
Overview of the Dutch Data Warehouse content. Overview of the data domains in the Dutch Data Warehouse. Examples of data are given per domain. EHR electronic health record, BMI body mass index, GCS Glasgow Coma Scale, RASS Richmond agitation and sedation scale, CAM-ICU confusion assessment method for the ICU, PEEP positive end-expiratory pressure, ECMO extracorporeal membrane oxygenation, IV intravenous
See this image and copyright information in PMC

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