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.
Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands.
Crit Care Med. 2021 Jun 1;49(6):e563-e577. doi: 10.1097/CCM.0000000000004916.
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.
重症监护医学是机器学习方法改善危重症患者预后的天然环境,因为 ICU 入院会产生大量数据。然而,技术、法律、伦理和隐私问题使得重症监护医学界无法轻易地提供这些数据。为此,美国重症监护医学学会和欧洲危重病医学会已将 ICU 患者数据共享确定为其联合数据科学合作的优先事项之一。为鼓励全球 ICU 负责任地共享其患者数据,我们现以阿姆斯特丹大学医学中心数据库(AmsterdamUMCdb)的开发和发布为例,介绍如何在充分遵守美国和欧洲隐私法的前提下,创建首个完全合规的免费重症监护数据库,以此证明共享复杂重症监护数据的可行性。
大学医院 ICU。
2003 年至 2016 年期间收治的 ICU 患者的数据。
我们采用基于风险的去识别策略,在保护隐私的同时保持数据的实用性。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方面的专家对这些流程和数据库进行了审核。
AmsterdamUMCdb 包含约 23106 次入住 20109 名患者的 10 亿个临床数据点。隐私审核的结论是重新识别的可能性不大,因此,在符合美国《健康保险携带和责任法案》和欧洲《通用数据保护条例》的情况下,AmsterdamUMCdb 可以被视为匿名信息。道德审核的结论是负责任的数据共享造成的负担很小,但潜在的好处是巨大的。
使用多学科方法可以解决与负责任的数据共享相关的技术、法律、伦理和隐私挑战。基于风险的去识别策略,同时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。这支持了重症监护医学学会和欧洲危重病医学会的共同愿景,即通过对大量 ICU 数据集进行科学研究来改善重症监护的预后。