The measurement of arterial pressure (AP) is a key component of hemodynamic monitoring. A variety of different innovative AP monitoring technologies became recently available. The decision to use these technologies must be based on their measurement performance in validation studies. These studies are AP method comparison studies comparing a new method (“test method”) with a reference method. In these studies, different comparative statistical tests are used including correlation analysis, Bland-Altman analysis, and trending analysis. These tests provide information about the statistical agreement without adequately providing information about the clinical relevance of differences between the measurement methods. To overcome this problem, we, in this study, propose an “error grid analysis” for AP method comparison studies that allows illustrating the clinical relevance of measurement differences. We constructed smoothed consensus error grids with calibrated risk zones derived from a survey among 25 specialists in anesthesiology and intensive care medicine. Differences between measurements of the test and the reference method are classified into 5 risk levels ranging from “no risk” to “dangerous risk”; the classification depends on both the differences between the measurements and on the measurements themselves. Based on worked examples and data from the Multiparameter Intelligent Monitoring in Intensive Care II database, we show that the proposed error grids give information about the clinical relevance of AP measurement differences that cannot be obtained from Bland-Altman analysis. Our approach also offers a framework on how to adapt the error grid analysis for different clinical settings and patient populations.