Lin Wei-Chun, Goldstein Isaac H, Hribar Michelle R, Huang Abigail, Chiang Michael F
Departments of Medical Informatics and Clinical Epidemiology, OHSU, Portland, OR.
Departments of Ophthalmology, OHSU, Portland, OR.
AMIA Annu Symp Proc. 2018 Dec 5;2018:1387-1394. eCollection 2018.
Electronic health record systems have dramatically transformed the process of medical care, but one challenge has been increased time requirements for physicians. In this study, we address this challenge by developing and validating analytic models for predicting patient encounter length based on secondary EHR data. Key findings from this study are: (1) Secondary use of EHR data may be captured to predict provider interaction time with patients; (2) Modeling results using secondary data may provide more accurate predictions of provider interaction time than an expert provide; (3) These findings suggest that secondary use of EHR data may be used to develop effective customized scheduling methods to improve clinical efficiency. In the future, this has the potential to contribute toward methods for improved clinical scheduling and efficiency.
电子健康记录系统极大地改变了医疗护理过程,但一个挑战是医生的时间需求增加了。在本研究中,我们通过开发和验证基于电子健康记录二次数据预测患者诊疗时长的分析模型来应对这一挑战。本研究的主要发现如下:(1)电子健康记录数据的二次利用可用于预测医疗服务提供者与患者的互动时间;(2)使用二次数据的建模结果可能比专家提供的预测更准确地预测医疗服务提供者的互动时间;(3)这些发现表明,电子健康记录数据的二次利用可用于开发有效的定制排班方法,以提高临床效率。未来,这有可能为改进临床排班和效率的方法做出贡献。