Evidence map›Paper›PMID 33625129›Full record

ArticleCritical care medicine2021

Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example.

Patrick J Thoral, Jan M Peppink, Ronald H Driessen, Eric J G Sijbrands, Erwin J O Kompanje, Lewis Kaplan, Heatherlee Bailey, Jozef Kesecioglu, Maurizio Cecconi, Matthew Churpek and 6 more

2 registry-linked trialsOpen access · hybridAbstract read
In one paragraph

Article in Critical care medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 130 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
130citing papers in PubMed, 4 pooled it
24.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

NCT05497505 unknown statusnot on this mapstarted 2022, after this paper: background citation

Machine Learning in Intensive Care to Reduce Adverse Events, Complications, and Life-threatening Events (MIRACLE): Evaluation of Clinical Implementation of Machine Learning Based Decision Support for ICU Discharge

TypeobservationalSponsorPatrick J. ThoralRan2022 to 2023Enrolled1,500ConditionsCritical IllnessArmsPacmed Critical
NCT07773571 active not recruitingnot on this mapstarted 2026, after this paper: background citation

Development of an ICU Physiological State Space Monitor Based on the ICCA Database: A Single-Center Retrospective Observational Study

TypeobservationalSponsorShanghai Zhongshan HospitalRan2026 to 2029Enrolled60,000ConditionsCritical IllnessArmsMultidimensional ICU Physiological State and Trajectory Features
3 · Its place in the literature

Who cites it

130 citing papers in PubMed, 4 syntheses or guidelines pooled it, 246 citations in OpenAlex.

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70 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 8 institutions in 4 countries.

Patrick J ThoralDepartment of Intensive Care Medicine, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, Vrije Universiteit, Universiteit van Amsterdam, Amsterdam, The Netherlands.
Jan M PeppinkDepartment of Intensive Care Medicine, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, Vrije Universiteit, Universiteit van Amsterdam, Amsterdam, The Netherlands.
Ronald H DriessenDepartment of Intensive Care Medicine, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, Vrije Universiteit, Universiteit van Amsterdam, Amsterdam, The Netherlands.
Eric J G SijbrandsDepartment of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands.
Erwin J O KompanjeDepartment of Intensive Care Medicine, Erasmus MC, Rotterdam, The Netherlands.
Lewis KaplanDivision of Trauma, Surgical Critical Care and Emergency Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Heatherlee BaileyDepartment of Emergency Medicine, Durham VA Medical Center, Durham, NC.
Jozef KeseciogluDepartment of Intensive Care Medicine, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Maurizio CecconiExecutive Committee, European Society of Intensive Care Medicine, Brussels, Belgium.
Matthew ChurpekDepartment of Medicine, University of Wisconsin, Madison, WI.
Gilles ClermontDepartment of Critical Care Medicine, CRISMA Laboratory, University of Pittsburgh, Pittsburgh, PA.
Mihaela van der SchaarUniversity of Cambridge, Cambridge, United Kingdom.
Ari ErcoleDivision of Anaesthesia, University of Cambridge, Cambridge, United Kingdom.
Armand R J GirbesDepartment of Intensive Care Medicine, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, Vrije Universiteit, Universiteit van Amsterdam, Amsterdam, The Netherlands.
Paul W G ElbersDepartment of Intensive Care Medicine, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, Vrije Universiteit, Universiteit van Amsterdam, Amsterdam, The Netherlands.
Amsterdam University Medical Centers Database (AmsterdamUMCdb) Collaborators and the SCCM/ESICM Joint Data Science Task Force
Erasmus University Rotterdam · NLEuropean Society of Intensive Care Medicine · BEDurham VA Medical Center · USErasmus MC · NLUniversity of Pennsylvania · USUniversity of Pittsburgh · USUniversity of Wisconsin–Madison · USUtrecht University · NL

Funding

Sepsis Early Prediction and Subphenotype Illumination Study (SEPSIS)R01GM123193 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI CHURPEK, MATTHEW MICHAEL · 2017 to 2021
$1.9M
NIGMS NIH HHS R01 GM123193
6 · The paper itself

Abstract

objectivesCritical care medicine is a natural environment for machine learning approaches to improve outcomes for critically ill patients as admissions to ICUs generate vast amounts of data. However, technical, legal, ethical, and privacy concerns have so far limited the critical care medicine community from making these data readily available. The Society of Critical Care Medicine and the European Society of Intensive Care Medicine have identified ICU patient data sharing as one of the priorities under their Joint Data Science Collaboration. To encourage ICUs worldwide to share their patient data responsibly, we now describe the development and release of Amsterdam University Medical Centers Database (AmsterdamUMCdb), the first freely available critical care database in full compliance with privacy laws from both the United States and Europe, as an example of the feasibility of sharing complex critical care data.

settingUniversity hospital ICU. SUBJECTS: Data from ICU patients admitted between 2003 and 2016.

interventionsWe used a risk-based deidentification strategy to maintain data utility while preserving privacy. In addition, we implemented contractual and governance processes, and a communication strategy. Patient organizations, supporting hospitals, and experts on ethics and privacy audited these processes and the database. MEASUREMENTS AND MAIN

resultsAmsterdamUMCdb contains approximately 1 billion clinical data points from 23,106 admissions of 20,109 patients. The privacy audit concluded that reidentification is not reasonably likely, and AmsterdamUMCdb can therefore be considered as anonymous information, both in the context of the U.S. Health Insurance Portability and Accountability Act and the European General Data Protection Regulation. The ethics audit concluded that responsible data sharing imposes minimal burden, whereas the potential benefit is tremendous.

conclusionsTechnical, legal, ethical, and privacy challenges related to responsible data sharing can be addressed using a multidisciplinary approach. A risk-based deidentification strategy, that complies with both U.S. and European privacy regulations, should be the preferred approach to releasing ICU patient data. This supports the shared Society of Critical Care Medicine and European Society of Intensive Care Medicine vision to improve critical care outcomes through scientific inquiry of vast and combined ICU datasets.

Indexed as

ConfidentialityDatabases, FactualHealth Information ExchangeHealth Insurance Portability and Accountability ActHospitals, UniversityHumansIntensive Care UnitsNetherlandsSocieties, MedicalUnited States

Identifiers

PMID33625129
PMCPMC8132908
OpenAlexW3131505924

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 OpenQuestion graph.