The purpose of this study was to help hospitals effectively implement balanced scorecard (BSC) and detect aberrant responded indicators for further discussion and improvement. How to decide objectively cut-off values of thresholds is still controversial. The 14 items of customer satisfaction prospective implemented in a specified hospital were examined with the Rasch model (RM), rating scale model (RSM) and partial credit model (PCM) to check whether they constitute a one-dimensional construct and form an interval scored scale. The standardized residual analysis with a computer module was adopted to swiftly identify distorted indicators. The results show that those two items regarding complain frequency and messages in daily newspapers were deemed as mis-fitting to Rasch model’s requirement. The reliability derived from polytomous BSC was higher than that from dichotomous one. The PCM had a better fit and a higher reliability than the RSM. Volumes of operation onto customers should be excluded from the prospective of customer satisfaction of BSC to make the dimensional meaningful. It was suggested that practitioners can apply the PCM to fit BSC data and a computer module with the feature of Z-score detection can detect aberrant responses across indicators objectively at a very early stage. Future studies can focus on detecting differential item functioning among season groups, investigating scoring rubrics of item responses, and integrating the existing workflows via computer sciences. Analysis of other aspects of BSC is also recommended.