Objectives: This study aimed to develop and validate a new method for measuring injury severity, the excess mortality ratio-adjusted Injury Severity Score (EMR-ISS), using the International Classification of Diseases 10th Edition (ICD-10).Methods: An injury severity grade similar to the Abbreviated Injury Scale (AIS) was converted from the ICD-10 codes on the basis of quintiles of the EMR for each ICD-10 code. Like the New Injury Severity Score (NISS), the EMR-ISS was calculated from three maximum severity grades using data from the Korean National Injury Database. The EMR-ISS was then validated using the Hosmer-Lemeshow goodness-of-fit chi-square (HL chi-square, with lower values preferable), the area under the receiver operating characteristic curve (AUC-ROC), and the Pearson correlation coefficient to compare it with the International Classification of Diseases 9th Edition-based Injury Severity Score (ICISS). Nationwide hospital discharge abstract data (DAD) from stratified-sample general hospitals (n = 150) in 2004 were used for an external validation.Results: The total number of study subjects was 29,282,531, with five subgroups of particular interest identified for further study: traumatic brain injury (TBI, n = 3,768,670), traumatic chest injury (TCI, n = 1,169,828), poisoning (n = 251,565), burns (n = 869,020), and DAD (n = 26,374). The HL chi-square was lower for EMR-ISS than for ICISS in all groups: 42,410.8 versus 55,721.9 in total injury, 7,139.6 versus 20,653.9 in TBI,6,603.3 versus 4,531.8 Conclusions: The EMR-ISS showed better calibration and discrimination power for prediction of death than the ICISS in most injury groups. The EMR-ISS appears to be a feasible tool for passive injury surveillance of large data sets, such as insurance data sets or community injury registries containing diagnosis codes. Additional further studies for external validation on prospectively collected data sets should be considered.