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.
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.
复制标题
在重症监护医学会/欧洲重症监护医学会联合数据科学协作下负责任地共享ICU患者数据：阿姆斯特丹大学医学中心数据库(AmsterDamUMCdb)的例子。
DOI：
10.1097/ccm.0000000000004916
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发表时间：
2021-06-01
影响因子：
8.8
通讯作者：
Amsterdam University Medical Centers Database (AmsterdamUMCdb) Collaborators and the SCCM/ESICM Joint Data Science Task Force
中科院分区：
文献类型：
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作者：
Thoral PJ;Peppink JM;Driessen RH;Sijbrands EJG;Kompanje EJO;Kaplan L;Bailey H;Kesecioglu J;Cecconi M;Churpek M;Clermont G;van der Schaar M;Ercole A;Girbes ARJ;Elbers PWG;Amsterdam University Medical Centers Database (AmsterdamUMCdb) Collaborators and the SCCM/ESICM Joint Data Science Task Force
补充数字内容可在正文中找到。重症监护医学是机器学习方法改善危重患者预后的自然环境，因为ICU的入院产生了大量数据。然而，到目前为止，技术、法律、伦理和隐私方面的担忧限制了重症监护医学界随时提供这些数据。重症监护医学会和欧洲重症监护医学会已将ICU患者数据共享确定为他们联合数据科学合作的优先事项之一。为了鼓励世界各地的ICU负责任地共享他们的患者数据，我们现在描述阿姆斯特丹大学医疗中心数据库(AmsterDamUMCdb)的开发和发布，作为共享复杂危重数据可行性的一个例子。阿姆斯特丹大学医疗中心数据库是第一个完全符合美国和欧洲隐私法的免费提供的危重数据库。大学医院重症监护室。2003年至2016年间收治的ICU患者的数据。我们使用了基于风险的身份识别策略来维护数据效用，同时保护隐私。此外，我们还实施了合同和治理流程，以及沟通策略。患者组织、支持医院以及伦理和隐私专家对这些过程和数据库进行了审计。AmsterdamUMCdb包含20,109名患者的23,106个入院数据中的大约10亿个临床数据点。隐私审计得出的结论是，重新识别身份的可能性不大，因此根据美国《健康保险可携带性和责任法案》和欧洲一般数据保护法规，AmsterdamUMCdb可以被视为匿名信息。道德审计的结论是，负责任的数据共享带来的负担最小，而潜在的好处却是巨大的。与负责任的数据共享相关的技术、法律、道德和隐私挑战可以使用多学科方法来解决。基于风险的身份识别策略符合美国和欧洲的隐私法规，应该是发布ICU患者数据的首选方法。这支持共享重症监护医学学会和欧洲重症监护医学学会的愿景，通过对海量和组合的ICU数据集进行科学查询来改善重症监护结果。
Supplemental Digital Content is available in the text. 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.