Using Statistical Process Control to Drive Improvement in Neonatal Care A Practical Introduction to Control Charts

被引：27
|
作者：
Gupta, Munish [1 ]
Kaplan, Heather C. [2 ,3 ]
机构：
[1] Beth Israel Deaconess Med Ctr, Dept Neonatol, 330 Brookline Ave, Boston, MA 02215 USA
[2] Univ Cincinnati, Sch Med, Cincinnati Childrens Hosp Med Ctr, Perinatal Inst, 3333 Burnet Ave,MLC 7009, Cincinnati, OH 45229 USA
[3] Univ Cincinnati, Sch Med, Cincinnati Childrens Hosp Med Ctr, James M Anderson Ctr Hlth Syst Excellence, 3333 Burnet Ave,MLC 7009, Cincinnati, OH 45229 USA
来源：
CLINICS IN PERINATOLOGY | 2017年 / 44卷 / 03期
关键词：
Control chart; Statistical process control; Quality improvement; Special cause variation; Common cause variation; HEALTH-CARE; TOOL;
D O I：
10.1016/j.clp.2017.05.011
中图分类号：
R71 [妇产科学];
学科分类号：
100211 ;
摘要：
Quality improvement requires the analysis of data measured over time and the ability to understand variation in that data in order to evaluate processes and guide change. Common cause variation is natural variation inherent to any process; special cause variation is unnatural variation owing to external factors. Control charts are tools within statistical process control (SPC) that provide a robust 1 method for understanding data over time and identifying common and special cause variation. Health care providers engaging in quality improvement should use SPC methods and control charts to help guide their
引用
收藏
页码：627 / +
页数：19
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