Wagholikar Kavishwar, Sohn Sunghwan, Wu Stephen, Kaggal Vinod, Buehler Sheila, Greenes Robert A, Wu Tsung-Teh, Larson David, Liu Hongfang, Chaudhry Rajeev, Boardman Lisa
Biomedical Statistics and Informatics.
AMIA Jt Summits Transl Sci Proc. 2013 Mar 18;2013:269-73. eCollection 2013.
A major barrier for computer-based clinical decision support (CDS), is the difficulty in obtaining the patient information required for decision making. The information gap is often due to deficiencies in the clinical documentation. One approach to address this gap is to gather and reconcile data from related documents or data sources. In this paper we consider the case of a CDS system for colorectal cancer screening and surveillance. We describe the use of workflow analysis to design data reconciliation processes. Further, we perform a quantitative analysis of the impact of these processes on system performance using a dataset of 106 patients. Results show that data reconciliation considerably improves the performance of the system. Our study demonstrates that, workflow-based data reconciliation can play a vital role in designing new-generation CDS systems that are based on complex guideline models and use natural language processing (NLP) to obtain patient data.
基于计算机的临床决策支持（CDS）的一个主要障碍是难以获取决策所需的患者信息。信息差距往往是由于临床文档存在缺陷。解决这一差距的一种方法是从相关文档或数据源收集并核对数据。在本文中，我们考虑用于结直肠癌筛查和监测的CDS系统的情况。我们描述了如何使用工作流分析来设计数据核对流程。此外，我们使用106名患者的数据集对这些流程对系统性能的影响进行了定量分析。结果表明，数据核对显著提高了系统性能。我们的研究表明，基于工作流的数据核对在设计基于复杂指南模型并使用自然语言处理（NLP）来获取患者数据的新一代CDS系统中可以发挥至关重要的作用。
