The main concern of the power system state estimation is to allow the establishment of a reliable data base to be used in real-time monitoring. Generally, the stored data are: active and reactive power injection and line flows, voltage magnitudes and the information about the system network configuration. This work presents an efficient methodology for detection, diagnostic and treatment of inconsistent data using a dynamic state estimation algorithm. The basic characteristic of the dynamic estimators is its capability of forecasting the system state (complex nodal voltages) and, consequently, the measurement set. Based on this characteristic, a scheme for detection of suspected information is built. The suspicions are caused by: gross measurement error, topological errors or forecasting erros due to sudden changes in the system operating point. The diagnostic about which anomaly is actualy present is carried out taken into account the results of the forecasting and filtering steps of the state estimator. The proposed debugging algorithm is tested using simulated data from a power system operating under normal and abnormal conditions and the results are discussed.