ABSTRACT
Improvement in healthcare fundamentally requires measurement. Measurement includes both the process and outcome data elements that are essential to improving a clinical or operational process. Too often, we are inundated by data that is not up to the task of improvement. To overcome this, you will need to collect and use data that has a specific and guiding purpose. Deming’s adage that the aim defines the system is critical here. Building these data systems in healthcare requires effort and discipline. Good design will justify the expense and the effort. Data systems are predicated on an understanding of foundational concepts. These include a basic understanding of conceptual models and the fundamentals of variation science.
This chapter provides the basic framework to understand and then build and use data systems that are effective in managing clinical and operational processes. Good data and design are at the heart of one of the fundamental questions from the Model for Improvement for otherwise how will we know that the change is an improvement? Notably, the Lean principle of ‘respect for people’ applies just as clearly to data design and reporting as in other areas related to Lean thinking and work.
