Using Data for Healthcare Improvement

In this module, you will learn about the importance of measuring quality of care and health outcomes in order to determine whether QI initiatives have achieved their aims. You will learn about how data is utilised to identify areas of improvement and the importance of using both quantitative and qualitative data in evaluating change. You will learn about the specific methods appropriate for improvement as distinct from methods more suited to research, including how to design measurement schemes suitable for improvement initiatives.

In this module you will learn how to use the methods of statistical process control to distinguish between

variation due to changes in the underlying process of care and variation that is part of this process, including how to distinguish when variation in a measure constitutes evidence of improvement in care. You will use the statistical software package R to analyse real time series data using Shewhart charts, and learn to interpret and act on the results. Example data is taken from a project screening for Atrial Fibrillation in an at risk population, and data on time spent in the accident and emergency department

In this module you will build on what you learnt previously, expanding the repertoire of methods to

cover additional types of data frequently encountered in quality improvement.