Open-access programs for injury categorization using ICD-9 or ICD-10

Abstract

Abstract Background The article introduces Programs for Injury Categorization, using the International Classification of Diseases (ICD) and R statistical software (ICDPIC-R). Starting with ICD-8, methods have been described to map injury diagnosis codes to severity scores, especially the Abbreviated Injury Scale (AIS) and Injury Severity Score (ISS). ICDPIC was originally developed for this purpose using Stata, and ICDPIC-R is an open-access update that accepts both ICD-9 and ICD-10 codes. Methods Data were obtained from the National Trauma Data Bank (NTDB), Admission Year 2015. ICDPIC-R derives CDC injury mechanism categories and an approximate ISS (“RISS”) from either ICD-9 or ICD-10 codes. For ICD-9-coded cases, RISS is derived similar to the Stata package (with some improvements reflecting user feedback). For ICD-10-coded cases, RISS may be calculated in several ways: The “GEM” methods convert ICD-10 to ICD-9 (using General Equivalence Mapping tables from CMS) and then calculate ISS with options similar to the Stata package; a “ROCmax” method calculates RISS directly from ICD-10 codes, based on diagnosis-specific mortality in the NTDB, maximizing the C-statistic for predicting NTDB mortality while attempting to minimize the difference between RISS and ISS submitted by NTDB registrars (ISSAIS). Findings were validated using data from the National Inpatient Survey (NIS, 2015). Results NTDB contained 917,865 cases, of which 86,878 had valid ICD-10 injury codes. For a random 100,000 ICD-9-coded cases in NTDB, RISS using the GEM methods was nearly identical to ISS calculated by the Stata version, which has been previously validated. For ICD-10-coded cases in NTDB, categorized ISS using any version of RISS was similar to ISSAIS; for both NTDB and NIS cases, increasing ISS was associated with increasing mortality. Prediction of NTDB mortality was associated with C-statistics of 0.81 for ISSAIS, 0.75 for RISS using the GEM methods, and 0.85 for RISS using the ROCmax method; prediction of NIS mortality was associated with C-statistics of 0.75–0.76 for RISS using the GEM methods, and 0.78 for RISS using the ROCmax method. Instructions are provided for accessing ICDPIC-R at no cost. Conclusions The ideal methods of injury categorization and injury severity scoring involve trained personnel with access to injured persons or their medical records. ICDPIC-R may be a useful substitute when this ideal cannot be obtained.

Keywords

• Injury severity score
• Abbreviated injury score
• International classification of diseases
• ICDPIC