To track patient satisfaction over time while distinguishing true changes from routine variation, the best tool to use is a(n):

To effectively track patient satisfaction over time while distinguishing true changes from routine variation, the most suitable tool is a control chart. Control charts are designed to monitor processes over time and help identify whether observed variations are due to common causes (natural fluctuations) or special causes (indicating a significant change in the process).

Control charts accomplish this by plotting data points in time order and adding control limits that define the expected range of variability. When data points fall outside these control limits, it signals that a true change might be occurring rather than just random variation. This makes control charts particularly useful in healthcare settings where understanding trends in patient satisfaction is essential for quality improvement.

Other tools, while useful in their own right, do not provide the same level of insight for tracking over time with the ability to detect true shifts in process performance versus normal variations. For instance, histograms visualize the distribution of satisfaction scores but do not illustrate trends over time. Scatter plots can show relationships between variables but lack the temporal aspect and control limits necessary for tracking changes in a single process. Box plots are effective for comparing distributions but don't track changes over time in a single series. Thus, control charts are the most appropriate tool for this specific task.