Pakdil Fatma, Azadeh-Fard Nasibeh, Esatoglu Afsun Ezel
Department of Business Administration, Eastern Connecticut State University, Willimantic, CT, USA.
Department of Industrial and Systems Engineering, Rochester Institute of Technology, Rochester, NY, USA.
Hosp Pract (1995). 2019 Oct;47(4):196-202. doi: 10.1080/21548331.2019.1664883. Epub 2019 Oct 3.
: Monitoring length of stay (LOS) can help medical decision makers identify areas of potential improvements and improve resource management, which results in better quality of care for patients. This study aims to monitor process performance at hospitals by implementing a statistical process control (SPC) approach on LOS.: The study focuses on diabetic inpatients admitted to hospitals in two national healthcare systems. The data used in this study were collected from two hospitals: (1) a 500-bed teaching hospital in Southwest Virginia in the U.S., and (2) a 1100-bed teaching and research hospital located in Ankara, Turkey. charts were used to analyze the datasets and monitor the variations of LOS.: The results of - charts showed that LOS was longer in Turkey than the U.S. LOS was skewed toward minimum values in the U.S. whereas it was spread out in Turkey. The average LOS was 3.27 days (STD = 2.30) in the U.S. while it was 7.28 days (STD = 4.56) in Turkey. The differences in two national healthcare systems may be reflected in the LOS variable.: This study implements a control chart-based approach to monitor LOS and detect prolonged hospitalization for diabetic patients. As presented in - charts, there are abnormal LOS observations in each data set. The decision makers and caregivers must analyze - charts to identify either common or special causes of variation. Each abnormal LOS requires a detailed patient-centric analysis. Care providers and decision makers can investigate the root causes of abnormal LOS for each patient by further exploring the characteristics of diabetic patients who had abnormal LOS at hospitals, such as age, preexisting conditions, or the type of medical procedure conducted on each patient.
监测住院时间（LOS）有助于医疗决策者识别潜在的改进领域并改善资源管理，从而为患者提供更高质量的护理。本研究旨在通过对住院时间实施统计过程控制（SPC）方法来监测医院的流程绩效。
该研究聚焦于两个国家医疗系统中住院的糖尿病患者。本研究使用的数据来自两家医院：（1）美国弗吉尼亚州西南部一家拥有500张床位的教学医院，以及（2）位于土耳其安卡拉的一家拥有1100张床位的教学与研究医院。使用控制图来分析数据集并监测住院时间的变化。
控制图的结果显示，土耳其的住院时间比美国长。美国的住院时间倾向于最小值，而在土耳其则分布较分散。美国的平均住院时间为3.27天（标准差=2.30），而土耳其为7.28天（标准差=4.56）。两个国家医疗系统的差异可能反映在住院时间变量上。
本研究采用基于控制图的方法来监测住院时间并检测糖尿病患者的住院时间延长情况。如控制图所示，每个数据集中都有异常的住院时间观察值。决策者和护理人员必须分析控制图以识别变异的常见或特殊原因。每个异常的住院时间都需要进行详细的以患者为中心的分析。护理提供者和决策者可以通过进一步探究在医院住院时间异常的糖尿病患者的特征，如年龄、既往疾病或对每个患者进行的医疗程序类型，来调查每个患者住院时间异常的根本原因。
