BACKGROUND: Those working in healthcare today are challenged more than ever before to quickly and efficiently learn from data to improve their services and delivery of care. There is broad agreement that healthcare professionals working on the front lines benefit greatly from the visual display of data presented in time order. AIM: To describe the run chart-an analytical tool commonly used by professionals in quality improvement but underutilised in healthcare. METHODS: A standard approach to the construction, use and interpretation of run charts for healthcare applications is developed based on the statistical process control literature. DISCUSSION: Run charts allow us to understand objectively if the changes we make to a process or system over time lead to improvements and do so with minimal mathematical complexity. This method of analyzing and reporting data is of greater value to improvement projects and teams than traditional aggregate summary statistics that ignore time order. Because of its utility and simplicity, the run chart has wide potential application in healthcare for practitioners and decision-makers. Run charts also provide the foundation for more sophisticated methods of analysis and learning such as Shewhart (control) charts and planned experimentation.
BACKGROUND: Those working in healthcare today are challenged more than ever before to quickly and efficiently learn from data to improve their services and delivery of care. There is broad agreement that healthcare professionals working on the front lines benefit greatly from the visual display of data presented in time order. AIM: To describe the run chart-an analytical tool commonly used by professionals in quality improvement but underutilised in healthcare. METHODS: A standard approach to the construction, use and interpretation of run charts for healthcare applications is developed based on the statistical process control literature. DISCUSSION: Run charts allow us to understand objectively if the changes we make to a process or system over time lead to improvements and do so with minimal mathematical complexity. This method of analyzing and reporting data is of greater value to improvement projects and teams than traditional aggregate summary statistics that ignore time order. Because of its utility and simplicity, the run chart has wide potential application in healthcare for practitioners and decision-makers. Run charts also provide the foundation for more sophisticated methods of analysis and learning such as Shewhart (control) charts and planned experimentation.
Authors: Courtney M Brown; Andrew F Beck; Wendy Steuerwald; Elizabeth Alexander; Zeina M Samaan; Robert S Kahn; Mona Mansour Journal: Clin Pediatr (Phila) Date: 2015-05-20 Impact factor: 1.168
Authors: Monte S Willis; Bruce A Cairns; Ashley Purdy; Andrey V Bortsov; Samuel W Jones; Shiara M Ortiz-Pujols; Tina M Schade Willis; Benny L Joyner Journal: Int J Burns Trauma Date: 2013-01-24