ITM Web Conf.
Volume 36, 2021The 16th IMT-GT International Conference on Mathematics, Statistics and their Applications (ICMSA 2020)
|Number of page(s)||23|
|Section||Statistics and Data Science|
|Published online||26 January 2021|
A study on the application of control chart in healthcare
Department of Mathematical and Actuarial Sciences, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, 43000 Kajang, Selangor, Malaysia
* Corresponding author: firstname.lastname@example.org
The most concerning issues in the healthcare system will always be quality control and quality improvement as they are significant to the health condition of the patient. A quality statistical tool such as statistical process control (SPC) charts will be efficient and highly effective in reducing the sources of variation within the healthcare process and in monitoring or controlling improvement of the process. The control chart is a statistical process control methodology designed to evaluate the process improvement or change in the manufacturing industry and is being implemented gradually in the healthcare sector. This will enable healthcare organizations to prevent unnecessary investment or spending in any changes that sound good but do not have any positive impact on real progress or improvement. When there is greater participation of humans in healthcare, the risks of error are also greater. Control charts help determine the source of error by differentiating the common and special cause of variation, each requiring a different response from healthcare management. This paper intends to deliver an overview of SPC theory and to explore the application of SPC charts by presenting a few examples of the implementation of control charts to common issues in the healthcare sector. After a brief overview of SPC in healthcare, the selection and construction of the two widely used control charts (Individuals and Moving Range chart, U chart) were adopted and illustrated by using the example from healthcare.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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