It is appropriate for members of a problem solving team, those leading and facilitating process improvement activities to reduce variation in cares, and practitioners preparing to adopt process improvement to improve outcomes for patients in healthcare.
Learn the data analysis techniques necessary to assess if processes are on target, explore relationships between variables, and minimize defects using metrics such as cycle time, readmissions, ratings, and revenue. Statistical principles will be presented through realworld examples and exercises ― all supported by Minitab Statistical Software.
In this 2-day foundational course you will learn to minimize the time required for data analysis by using Minitab to import data, develop sound statistical approaches to exploring data, create and interpret compelling graphs, and export results. Analyze a variety of real world data sets to learn how to align your applications with the right statistical tool, and interpret statistical output to reveal problems with a process or evidence of an improvement. Learn the fundamentals of important statistical concepts, such as hypothesis testing and confidence intervals, and how to uncover and describe relationships between variables with statistical modeling tools.
This course places a strong emphasis on making sound decisions based upon the practical application of statistical techniques commonly used in healthcare.
Develop the necessary skills to successfully evaluate and certify your measurement systems. Learn the basic fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control your processes. Develop the skills to know when and where to use the various types of control charts available in Minitab. Learn how to utilize important capability analysis tools to evaluate your processes relative to internal and customer specifications.
The course emphasizes the teaching of quality tools as they pertain to the healthcare industry.