Li Xiang, Liu Haifeng, Zhang Shilei, Mei Jing, Xie Guotong, Yu Yiqin, Li Jing, Lakshmanan Geetika T
IBM Research, Beijing, China.
IBM T. J. Watson Research Center, Hawthorne, NY, USA.
Stud Health Technol Inform. 2014;205:715-9.
A care pathway (CP) is a standardized process that consists of multiple care stages, clinical activities and their relations, aimed at ensuring and enhancing the quality of care. However, actual care may deviate from the planned CP, and analysis of these deviations can help clinicians refine the CP and reduce medical errors. In this paper, we propose a CP variance analysis method to automatically identify the deviations between actual patient traces in electronic medical records (EMR) and a multistage CP. As the care stage information is usually unavailable in EMR, we first align every trace with the CP using a hidden Markov model. From the aligned traces, we report three types of deviations for every care stage: additional activities, absent activities and violated constraints, which are identified by using the techniques of temporal logic and binomial tests. The method has been applied to a CP for the management of congestive heart failure and real world EMR, providing meaningful evidence for the further improvement of care quality.
护理路径（CP）是一个标准化的过程，它由多个护理阶段、临床活动及其关系组成，旨在确保和提高护理质量。然而，实际护理可能会偏离计划的护理路径，对这些偏差进行分析有助于临床医生完善护理路径并减少医疗差错。在本文中，我们提出了一种护理路径方差分析方法，以自动识别电子病历（EMR）中实际患者轨迹与多阶段护理路径之间的偏差。由于电子病历中通常没有护理阶段信息，我们首先使用隐马尔可夫模型将每条轨迹与护理路径进行对齐。从对齐的轨迹中，我们针对每个护理阶段报告三种类型的偏差：额外活动、缺失活动和违反的约束，这些偏差是通过使用时态逻辑和二项式检验技术来识别的。该方法已应用于充血性心力衰竭管理的护理路径和真实世界的电子病历，为进一步提高护理质量提供了有意义的证据。
