Hofer Ira S, Gabel Eilon, Pfeffer Michael, Mahbouba Mohammed, Mahajan Aman
From the Departments of *Anesthesiology and Perioperative Medicine and †Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California; and ‡Office of Health Informatics and Analytics, David Geffen School of Medicine at UCLA, Los Angeles, California.
Anesth Analg. 2016 Jun;122(6):1880-4. doi: 10.1213/ANE.0000000000001201.
Extraction of data from the electronic medical record is becoming increasingly important for quality improvement initiatives such as the American Society of Anesthesiologists Perioperative Surgical Home. To meet this need, the authors have built a robust and scalable data mart based on their implementation of EPIC containing data from across the perioperative period. The data mart is structured in such a way so as to first simplify the overall EPIC reporting structure into a series of Base Tables and then create several Reporting Schemas each around a specific concept (operating room cases, obstetrics, hospital admission, etc.), which contain all of the data required for reporting on various metrics. This structure allows centralized definitions with simplified reporting by a large number of individuals who access only the Reporting Schemas. In creating the database, the authors were able to significantly reduce the number of required table identifiers from >10 to 3, as well as to correct errors in linkages affecting up to 18.4% of cases. In addition, the data mart greatly simplified the code required to extract data, making the data accessible to individuals who lacked a strong coding background. Overall, this infrastructure represents a scalable way to successfully report on perioperative EPIC data while standardizing the definitions and improving access for end users.
从电子病历中提取数据对于诸如美国麻醉医师协会围手术期手术之家等质量改进计划而言变得越来越重要。为满足这一需求,作者基于其对EPIC系统的实施构建了一个强大且可扩展的数据集市,该数据集市包含围手术期各阶段的数据。数据集市的构建方式是,首先将整个EPIC报告结构简化为一系列基础表,然后围绕特定概念(手术室病例、产科、住院等)创建几个报告模式,每个报告模式包含报告各种指标所需的所有数据。这种结构允许进行集中定义,使得大量仅访问报告模式的人员能够简化报告流程。在创建数据库时,作者能够将所需的表标识符数量从超过10个大幅减少到3个,同时纠正影响高达18.4%病例的链接错误。此外,数据集市极大地简化了提取数据所需的代码,使缺乏强大编码背景的人员也能访问数据。总体而言,这种基础设施代表了一种可扩展的方式,能够在标准化定义并改善终端用户访问权限的同时,成功报告围手术期的EPIC数据。