From the Department of Anesthesiology, Perioperative Medicine and Pain Management, University of Miami, Miller School of Medicine, Sidney Kimmel Medical College at Thomas Jefferson University, Miami, Florida.
Department of Anesthesia, University of Iowa, Iowa City, Iowa.
Anesth Analg. 2018 Jul;127(1):105-114. doi: 10.1213/ANE.0000000000003324.
For this special article, we reviewed the computer code, used to extract the data, and the text of all 47 studies published between January 2006 and August 2017 using anesthesia information management system (AIMS) data from Thomas Jefferson University Hospital (TJUH). Data from this institution were used in the largest number (P = .0007) of papers describing the use of AIMS published in this time frame. The AIMS was replaced in April 2017, making this finite sample finite. The objective of the current article was to identify factors that made TJUH successful in publishing anesthesia informatics studies. We examined the structured query language used for each study to examine the extent to which databases outside of the AIMS were used. We examined data quality from the perspectives of completeness, correctness, concordance, plausibility, and currency. Our results were that most could not have been completed without external database sources (36/47, 76.6%; P = .0003 compared with 50%). The operating room management system was linked to the AIMS and was used significantly more frequently (26/36, 72%) than other external sources. Access to these external data sources was provided, allowing exploration of data quality. The TJUH AIMS used high-resolution timestamps (to the nearest 3 milliseconds) and created audit tables to track changes to clinical documentation. Automatic data were recorded at 1-minute intervals and were not editable; data cleaning occurred during analysis. Few paired events with an expected order were out of sequence. Although most data elements were of high quality, there were notable exceptions, such as frequent missing values for estimated blood loss, height, and weight. Some values were duplicated with different units, and others were stored in varying locations. Our conclusions are that linking the TJUH AIMS to the operating room management system was a critical step in enabling publication of multiple studies using AIMS data. Access to this and other external databases by analysts with a high degree of anesthesia domain knowledge was necessary to be able to assess the quality of the AIMS data and ensure that the data pulled for studies were appropriate. For anesthesia departments seeking to increase their academic productivity using their AIMS as a data source, our experiences may provide helpful guidance.
对于这篇特别文章，我们回顾了用于提取数据的计算机代码，并审查了 2006 年 1 月至 2017 年 8 月期间托马斯杰斐逊大学医院（TJUH）使用麻醉信息管理系统（AIMS）数据发布的 47 项研究的文本。该机构的数据用于描述在此时间段内使用 AIMS 发布的最大数量的论文（P =.0007）。2017 年 4 月，AIMS 被替换，因此这个有限的样本是有限的。本文的目的是确定使 TJUH 在发表麻醉信息学研究方面取得成功的因素。我们检查了每个研究使用的结构化查询语言，以检查使用 AIMS 以外的数据库的程度。我们从完整性、正确性、一致性、合理性和时效性的角度检查了数据质量。我们的结果是，没有外部数据库来源，大多数研究都无法完成（36/47，76.6%；P =.0003 与 50%相比）。手术室管理系统与 AIMS 相连，并且使用频率显著更高（26/36，72%）比其他外部来源。提供了对这些外部数据源的访问权限，允许对数据质量进行探索。TJUH AIMS 使用高分辨率时间戳（精确到最近 3 毫秒）并创建审计表来跟踪对临床文档的更改。自动数据以 1 分钟的间隔记录，并且不可编辑；在分析过程中进行数据清理。按预期顺序排列的少数配对事件顺序错误。尽管大多数数据元素质量很高，但也有一些明显的例外，例如失血量、身高和体重的频繁缺失值。一些值具有不同的单位，而其他值存储在不同的位置。我们的结论是，将 TJUH AIMS 链接到手术室管理系统是使用 AIMS 数据发表多项研究的关键步骤。分析员必须能够访问该系统和其他外部数据库，并且具有高度的麻醉领域知识，以便能够评估 AIMS 数据的质量，并确保为研究提取的数据是合适的。对于希望利用其作为数据源的 AIMS 来提高其学术生产力的麻醉部门，我们的经验可能提供有益的指导。
