1. Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration
- Author
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Mihaela van der Schaar, Patrick Thoral, Matthew M. Churpek, Ari Ercole, Armand R. J. Girbes, Eric J.G. Sijbrands, Lewis J. Kaplan, Erwin J. O. Kompanje, Maurizio Cecconi, Ronald H. Driessen, Jan M. Peppink, Gilles Clermont, Heatherlee Bailey, Paul W. G. Elbers, Jozef Kesecioglu, Intensive care medicine, ACS - Diabetes & metabolism, Internal Medicine, and Intensive Care
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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 - Abstract
Supplemental Digital Content is available in the text., 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.
- Published
- 2021
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