Background: Dimensionality must be determined before adding item scores to represent the overall performance of a measure. The aim of this study is to help researchers identify the dimension tendency for a scale's validity toward a common entity. This in turn will improve inspecting aberrant responses for each item with individual item-by-item box plots of disclosure for patient views on healthcare service quality.Methods: We used the Rasch rating scale model to analyse the 2009 English inpatient questionnaire data regarding patient satisfactory perception, which were collected from 162 hospitals, examined unidimensionality, and developed a visual plot in Excel that depicts the satisfaction level of each hospital across questions and monitors aberrant responses with Rasch standardised residual for each item and outfit statistics for individual hospitals.Results: We found that (1) the Rasch_residual principal component analysis is able to check dimensionality. The dimension coefficient defined as the extent of dimensionality should report to readers. The five key domains of the 2009 English adult inpatient questionnaire data regarding patient experience measure a common entity and earn a dimension coefficient of 0.88, and (2) item-by-item chart plots along with Rasch's fit statistics (i.e., standardised residual and outfit statistics) can help organisations accomplish large improvements on a small number of key areas.Conclusion: Without removing misfit questions, we found that the 20-item inpatient questionnaire measured the same construct across types of hospitals. The visual chart plot in Excel provides an exemplary comparison of quality of healthcare for individual hospitals. The Rasch analysis allows intra- (using standardised residuals for each item) and inter- (using outfit statistics across hospitals) hospital performances to be easily, quickly and clearly compared.