Department of BioHealth Informatics, School of Informatics and Computing at Indiana University-Purdue University Indianapolis, Walker Plaza (WK), 719 Indiana Avenue, WK 117, Indianapolis, IN 46202, United States.
Department of BioHealth Informatics, School of Informatics and Computing at Indiana University-Purdue University Indianapolis, Walker Plaza (WK), 719 Indiana Avenue, WK 117, Indianapolis, IN 46202, United States.
J Biomed Inform. 2017 Oct;74:123-129. doi: 10.1016/j.jbi.2017.09.001. Epub 2017 Sep 10.
Due to the nature of information generation in health care, clinical documents contain duplicate and sometimes conflicting information. Recent implementation of Health Information Exchange (HIE) mechanisms in which clinical summary documents are exchanged among disparate health care organizations can proliferate duplicate and conflicting information.
To reduce information overload, a system to automatically consolidate information across multiple clinical summary documents was developed for an HIE network. The system receives any number of Continuity of Care Documents (CCDs) and outputs a single, consolidated record. To test the system, a randomly sampled corpus of 522 CCDs representing 50 unique patients was extracted from a large HIE network. The automated methods were compared to manual consolidation of information for three key sections of the CCD: problems, allergies, and medications.
Manual consolidation of 11,631 entries was completed in approximately 150h. The same data were automatically consolidated in 3.3min. The system successfully consolidated 99.1% of problems, 87.0% of allergies, and 91.7% of medications. Almost all of the inaccuracies were caused by issues involving the use of standardized terminologies within the documents to represent individual information entries.
This study represents a novel, tested tool for de-duplication and consolidation of CDA documents, which is a major step toward improving information access and the interoperability among information systems. While more work is necessary, automated systems like the one evaluated in this study will be necessary to meet the informatics needs of providers and health systems in the future.
由于医疗保健信息生成的性质,临床文档包含重复且有时相互冲突的信息。最近在医疗信息交换(HIE)机制中的实施,其中临床总结文档在不同的医疗保健组织之间交换,可能会使重复和冲突的信息增多。
为了减少信息过载,为 HIE 网络开发了一种自动整合多个临床总结文档信息的系统。该系统接收任意数量的连续护理文档(CCD)并输出一个单一的、整合的记录。为了测试该系统,从一个大型 HIE 网络中提取了一个由 50 个独特患者组成的、包含 522 个 CCD 的随机抽样语料库。将自动化方法与 CCD 的三个关键部分的信息手动整合进行了比较:问题、过敏和药物。
手动整合了约 150 小时的 11631 条记录。相同的数据在 3.3 分钟内自动整合。该系统成功整合了 99.1%的问题、87.0%的过敏和 91.7%的药物。几乎所有的不准确都是由于文档中使用标准化术语来表示单个信息条目的问题引起的。
这项研究代表了一种新颖的、经过测试的 CDA 文档去重和整合工具,这是提高信息访问和信息系统之间互操作性的重要一步。虽然还需要做更多的工作,但像这项研究中评估的那样,自动化系统将是满足未来提供者和医疗系统信息学需求的必要条件。