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Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration
- Source :
- Thoral, P J, Peppink, J M, Driessen, R H, Sijbrands, E J G, Kompanje, E J O, Kaplan, L, Bailey, H, Kesecioglu, J, Cecconi, M, Churpek, M, Clermont, G, van der Schaar, M, Ercole, A, Girbes, A R J & Elbers, P W G 2021, ' 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, vol. 49, no. 6, pp. E563-E577 . https://doi.org/10.1097/CCM.0000000000004916, Critical Care Medicine, Critical Care Medicine, 49(6), E563-E577. Lippincott Williams and Wilkins, Critical Care Medicine, 49(6), E563-E577. Lippincott Williams & Wilkins
- Publication Year :
- 2021
- Publisher :
- Lippincott Williams & Wilkins, 2021.
-
Abstract
- Supplemental Digital Content is available in the text.<br />OBJECTIVES: 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. SETTING: University hospital ICU. SUBJECTS: Data from ICU patients admitted between 2003 and 2016. INTERVENTIONS: 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. MEASUREMENTS AND MAIN RESULTS: 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. CONCLUSIONS: 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.
- Subjects :
- medicine.medical_specialty
Health Information Exchange
Databases, Factual
Privacy laws of the United States
data anonymization
Audit
Critical Care and Intensive Care Medicine
computer.software_genre
Hospitals, University
03 medical and health sciences
0302 clinical medicine
big data
Medicine
Humans
Critical Care Outcomes
Intensive care medicine
database
Societies, Medical
Netherlands
Health Insurance Portability and Accountability Act
Data anonymization
Database
business.industry
Online Clinical Investigations
030208 emergency & critical care medicine
artificial intelligence
Data science
United States
Data sharing
Intensive Care Units
machine learning
030228 respiratory system
General Data Protection Regulation
ComputingMethodologies_DOCUMENTANDTEXTPROCESSING
data science
Privacy law
business
computer
Algorithms
Confidentiality
Subjects
Details
- Language :
- English
- ISSN :
- 15300293 and 00903493
- Volume :
- 49
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- Critical Care Medicine
- Accession number :
- edsair.doi.dedup.....8c4a50bd70787841558cc58672b63c9e
- Full Text :
- https://doi.org/10.1097/CCM.0000000000004916