BMJ Quality & Safety · 2011 · 515 citations · 10 references
Healthcare providers face increasing pressure to use data quickly to improve care delivery. This paper describes the run chart, a simple analytical tool for visualizing time‑ordered data, and proposes a standard method for its construction, use, and interpretation in healthcare quality improvement. The authors base the run‑chart methodology on statistical process control principles, outlining steps for building and interpreting charts and noting that run charts underpin more advanced techniques such as Shewhart charts and planned experiments. Run charts provide greater insight for improvement teams than traditional aggregate statistics that ignore temporal order.
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.To describe the run chart-an analytical tool commonly used by professionals in quality improvement but underutilised in healthcare.A standard approach to the construction, use and interpretation of run charts for healthcare applications is developed based on the statistical process control literature.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.
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