Centre for Medical and Health Science Education, University of Auckland, Auckland, New Zealand.
J Am Med Inform Assoc. 2013 Jan 1;20(1):180-3. doi: 10.1136/amiajnl-2012-001087. Epub 2012 Aug 4.
To provide a set of high-quality time-series physiologic and event data from anesthetic cases formatted in an easy-to-use structure.
With ethics committee approval, data from surgical operations under general anesthesia were collected, including physiologic data, drug administrations, events, and clinicians' comments. These data were de-identified, formatted in a combined CSV/XML structure and made publicly available.
Two separate datasets were collected containing physiologic time-series data and time-stamped events for 34 patients. For 20 patients, the data included 400 physiologic signals collected over 20 h, 274 events, and 597 drug administrations. For 14 patients, the data included 23 physiologic signals collected over 69 h, with 286 time stamped comments.
Data reuse potentially saves significant time and financial costs. However, there are few high-quality repositories for accessible physiologic data and clinical interventions from surgical cases. De-identifying records assists with overcoming problems of privacy and storing the data in a format which is easily manipulated with computing resources facilitates access by the wider research community. It is hoped that additional high-quality data will be added. Future work includes developing tools to explore and visualize the data more efficiently, and establishing quality control measures.
An approach to collecting and storing high-quality datasets from surgical operations under anesthesia such that they can be easily accessed by others for use in research has been demonstrated.
提供一套高质量的麻醉病例时间序列生理和事件数据,采用易于使用的结构。
获得伦理委员会批准后,收集全身麻醉手术中的生理数据、药物管理、事件和临床医生的评论。这些数据经过去标识处理,以 CSV/XML 格式组合并公开提供。
收集了两个独立的数据集,包含 34 名患者的生理时间序列数据和时间戳事件。对于 20 名患者,数据包括 400 个生理信号,采集时间超过 20 小时,274 个事件和 597 次药物管理。对于 14 名患者,数据包括 23 个生理信号,采集时间超过 69 小时,有 286 个时间戳注释。
数据重用可以节省大量的时间和财务成本。然而,很少有可访问的来自手术病例的高质量生理数据和临床干预措施的存储库。记录去标识有助于解决隐私问题,并以易于使用计算资源处理的格式存储数据,便于更广泛的研究社区访问。希望能添加更多高质量的数据。未来的工作包括开发工具,以更有效地探索和可视化数据,并建立质量控制措施。
已经证明了一种从麻醉手术中收集和存储高质量数据集的方法,以便其他人可以轻松访问这些数据集,用于研究。