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

Critical 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...

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Vydané v:Critical care medicine Ročník 49; číslo 6; s. e563
Hlavní autori: Thoral, Patrick J, Peppink, Jan M, Driessen, Ronald H, Sijbrands, Eric J G, Kompanje, Erwin J O, Kaplan, Lewis, Bailey, Heatherlee, Kesecioglu, Jozef, Cecconi, Maurizio, Churpek, Matthew, Clermont, Gilles, van der Schaar, Mihaela, Ercole, Ari, Girbes, Armand R J, Elbers, Paul W G
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 01.06.2021
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ISSN:1530-0293, 1530-0293
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Abstract Critical 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. University hospital ICU. Data from ICU patients admitted between 2003 and 2016. We 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. AmsterdamUMCdb 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. Technical, 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.
AbstractList Critical 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. University hospital ICU. Data from ICU patients admitted between 2003 and 2016. We 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. AmsterdamUMCdb 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. Technical, 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.
Critical 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.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.University hospital ICU.SETTINGUniversity hospital ICU.Data from ICU patients admitted between 2003 and 2016.SUBJECTSData from ICU patients admitted between 2003 and 2016.We 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.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.AmsterdamUMCdb 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.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.Technical, 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.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.
Author Kaplan, Lewis
Bailey, Heatherlee
Peppink, Jan M
Elbers, Paul W G
Churpek, Matthew
Sijbrands, Eric J G
van der Schaar, Mihaela
Clermont, Gilles
Cecconi, Maurizio
Kesecioglu, Jozef
Driessen, Ronald H
Ercole, Ari
Thoral, Patrick J
Kompanje, Erwin J O
Girbes, Armand R J
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  givenname: Patrick J
  surname: Thoral
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  organization: Department 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
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  givenname: Jan M
  surname: Peppink
  fullname: Peppink, Jan M
  organization: Department 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
– sequence: 3
  givenname: Ronald H
  surname: Driessen
  fullname: Driessen, Ronald H
  organization: Department 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
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  givenname: Eric J G
  surname: Sijbrands
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  organization: Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
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  givenname: Erwin J O
  surname: Kompanje
  fullname: Kompanje, Erwin J O
  organization: Department of Intensive Care Medicine, Erasmus MC, Rotterdam, The Netherlands
– sequence: 6
  givenname: Lewis
  surname: Kaplan
  fullname: Kaplan, Lewis
  organization: Executive Committee, Society of Critical Care Medicine, Mount Prospect, IL
– sequence: 7
  givenname: Heatherlee
  surname: Bailey
  fullname: Bailey, Heatherlee
  organization: Executive Committee, Society of Critical Care Medicine, Mount Prospect, IL
– sequence: 8
  givenname: Jozef
  surname: Kesecioglu
  fullname: Kesecioglu, Jozef
  organization: Executive Committee, European Society of Intensive Care Medicine, Brussels, Belgium
– sequence: 9
  givenname: Maurizio
  surname: Cecconi
  fullname: Cecconi, Maurizio
  organization: Department of Anaesthesia and Intensive Care, Humanitas Research Hospital, Humanitas University, Milan, Italy
– sequence: 10
  givenname: Matthew
  surname: Churpek
  fullname: Churpek, Matthew
  organization: Department of Medicine, University of Wisconsin, Madison, WI
– sequence: 11
  givenname: Gilles
  surname: Clermont
  fullname: Clermont, Gilles
  organization: Department of Critical Care Medicine, CRISMA Laboratory, University of Pittsburgh, Pittsburgh, PA
– sequence: 12
  givenname: Mihaela
  surname: van der Schaar
  fullname: van der Schaar, Mihaela
  organization: Alan Turing Institute, London, United Kingdom
– sequence: 13
  givenname: Ari
  surname: Ercole
  fullname: Ercole, Ari
  organization: Data Science Section, European Society of Intensive Care Medicine, Brussels, Belgium
– sequence: 14
  givenname: Armand R J
  surname: Girbes
  fullname: Girbes, Armand R J
  organization: Executive Committee, European Society of Intensive Care Medicine, Brussels, Belgium
– sequence: 15
  givenname: Paul W G
  surname: Elbers
  fullname: Elbers, Paul W G
  organization: Data Science Section, European Society of Intensive Care Medicine, Brussels, Belgium
BackLink https://www.ncbi.nlm.nih.gov/pubmed/33625129$$D View this record in MEDLINE/PubMed
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PublicationYear 2021
References 34011836 - Crit Care Med. 2021 Jun 1;49(6):1003-1006
References_xml – reference: 34011836 - Crit Care Med. 2021 Jun 1;49(6):1003-1006
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Snippet Critical care medicine is a natural environment for machine learning approaches to improve outcomes for critically ill patients as admissions to ICUs generate...
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SubjectTerms Confidentiality - ethics
Confidentiality - legislation & jurisprudence
Confidentiality - standards
Databases, Factual - ethics
Databases, Factual - legislation & jurisprudence
Databases, Factual - standards
Health Information Exchange - ethics
Health Information Exchange - legislation & jurisprudence
Health Information Exchange - standards
Health Insurance Portability and Accountability Act
Hospitals, University - ethics
Hospitals, University - legislation & jurisprudence
Hospitals, University - standards
Humans
Intensive Care Units - organization & administration
Intensive Care Units - standards
Netherlands
Societies, Medical - standards
United States
Title 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
URI https://www.ncbi.nlm.nih.gov/pubmed/33625129
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Volume 49
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