A population-based comparison of CIREN and NASS cases using similarity scoring.

Abstract

The Crash Injury Research and Engineering Network (CIREN) provides significant details on injuries, and data on patient outcomes that is unavailable in the National Automotive Sampling System (NASS). However, CIREN cases are selected from specific Level I trauma centers with different inclusion criteria than those used for NASS, and the assertion that a given case is similar to the population of NASS cases is often made qualitatively. A robust, quantitative method is needed to compare CIREN to weighted NASS populations. This would greatly improve the usefulness and applicability of research conducted with data from the CIREN database. Our objective is to outline and demonstrate the utility of such a system to compare CIREN and NASS cases. This study applies the Mahalanobis distance metric methodology to determine similarity between CIREN and NASS/CDS cases. The Mahalanobis distance method is a multivariate technique for population comparison. Independent variables considered were total delta V, age, weight, height, maximum AIS, ISS, model year, gender, maximum intrusion, number of lower and upper extremity injuries, and number of head and chest injuries. The technique provides a unit-independent quantitative score which can be used to identify similarity of CIREN and NASS cases. Weighted NASS data and CIREN data were obtained for the years 2001-2005. NASS cases with Maximum AIS 3 resulted in a subset of 1,869 NASS cases, and 2,819 CIREN cases.