Cho Kyoung Won, Kim Seong Min, Chae Young Moon, Song Yong Uk
Department of Healthcare Administration, Kosin University, Busan, Korea.
Graduate School of Public Health, Yonsei University, Seoul, Korea.
Healthc Inform Res. 2017 Jan;23(1):35-42. doi: 10.4258/hir.2017.23.1.35. Epub 2017 Jan 31.
This research used queueing theory to analyze changes in outpatients' waiting times before and after the introduction of Electronic Medical Record (EMR) systems.
We focused on the exact drawing of two fundamental parameters for queueing analysis, arrival rate (λ) and service rate (µ), from digital data to apply queueing theory to the analysis of outpatients' waiting times. We used outpatients' reception times and consultation finish times to calculate the arrival and service rates, respectively.
Using queueing theory, we could calculate waiting time excluding distorted values from the digital data and distortion factors, such as arrival before the hospital open time, which occurs frequently in the initial stage of a queueing system. We analyzed changes in outpatients' waiting times before and after the introduction of EMR using the methodology proposed in this paper, and found that the outpatients' waiting time decreases after the introduction of EMR. More specifically, the outpatients' waiting times in the target public hospitals have decreased by rates in the range between 44% and 78%.
It is possible to analyze waiting times while minimizing input errors and limitations influencing consultation procedures if we use digital data and apply the queueing theory. Our results verify that the introduction of EMR contributes to the improvement of patient services by decreasing outpatients' waiting time, or by increasing efficiency. It is also expected that our methodology or its expansion could contribute to the improvement of hospital service by assisting the identification and resolution of bottlenecks in the outpatient consultation process.
本研究运用排队论分析电子病历(EMR)系统引入前后门诊患者等待时间的变化。
我们着重从数字数据中精确提取排队分析的两个基本参数,即到达率(λ)和服务率(µ),以便将排队论应用于门诊患者等待时间的分析。我们分别使用门诊患者的接待时间和会诊结束时间来计算到达率和服务率。
运用排队论,我们能够从数字数据以及诸如排队系统初始阶段频繁出现的医院开门前到达等失真因素中计算出排除失真值后的等待时间。我们使用本文提出的数据方法分析了EMR引入前后门诊患者等待时间的变化,发现引入EMR后门诊患者的等待时间有所减少。更具体地说,目标公立医院门诊患者的等待时间减少了44%至78%。
如果我们使用数字数据并应用排队论,就有可能在将影响会诊程序的输入错误和限制降至最低的同时分析等待时间。我们的结果证实,引入EMR通过减少门诊患者的等待时间或提高效率,有助于改善患者服务。预计我们的方法或其扩展将有助于通过协助识别和解决门诊会诊过程中的瓶颈问题来改善医院服务。