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Applications of control charts for quality improvement in health care / [electronic resource] Jerome Niyirora.

By: Material type: TextTextPublication details: Geneseo, NY : Open SUNY Textbooks, 2020.Description: 1 online resourceISBN:
  • 978-1-64176-080-5
Subject(s): Online resources: Summary: This textbook introduces students to the application methods of control charts to improve quality in health care. The textbook is written to be accessible to any student in the areas of health information management, health care informatics, and health care industrial engineering. Having a basic background in statistics would be beneficial, but such training is not a prerequisite to understanding how to apply the techniques discussed here. Several How-To sections are included to demonstrate the implementation of the given control charts using software such as Minitab and Excel. Additionally, samples of a Python code are included and can directly be accessed in a Jupyter Notebook at https://github.com/JeromeNN. The textbook starts with Chapter 1, which contains introductory concepts of quality improvement using control charts. Chapter 2 reviews the Shewhart model and the related charts. Chapter 3 shows how to apply time-weighted control charts to detect small shifts in the process. Chapter 4 appraises various techniques for adjusting control charts to account for factors such as autocorrelation and patient risk. Chapter 5 considers other quality improvement techniques that relate to control charts. The Appendix presents factors for constructing variable control charts. This textbook is not meant to be a comprehensive manuscript regarding quality improvement in health care. Instructors and students can supplement the chapter reading with additional resources, such as those referenced in the bibliography section of this text. The reader is also encouraged to consult a complementary textbook by the same author, titled Basic Tools for Quality Improvement in Health Care Informatics.
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This textbook introduces students to the application methods of control charts to improve quality in health care. The textbook is written to be accessible to any student in the areas of health information management, health care informatics, and health care industrial engineering. Having a basic background in statistics would be beneficial, but such training is not a prerequisite to understanding how to apply the techniques discussed here. Several How-To sections are included to demonstrate the implementation of the given control charts using software such as Minitab and Excel. Additionally, samples of a Python code are included and can directly be accessed in a Jupyter Notebook at https://github.com/JeromeNN. The textbook starts with Chapter 1, which contains introductory concepts of quality improvement using control charts. Chapter 2 reviews the Shewhart model and the related charts. Chapter 3 shows how to apply time-weighted control charts to detect small shifts in the process. Chapter 4 appraises various techniques for adjusting control charts to account for factors such as autocorrelation and patient risk. Chapter 5 considers other quality improvement techniques that relate to control charts. The Appendix presents factors for constructing variable control charts. This textbook is not meant to be a comprehensive manuscript regarding quality improvement in health care. Instructors and students can supplement the chapter reading with additional resources, such as those referenced in the bibliography section of this text. The reader is also encouraged to consult a complementary textbook by the same author, titled Basic Tools for Quality Improvement in Health Care Informatics.

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