Integrated model of simulated occupant injury risk and real medical costs

The purpose of this study was to develop an integrated methodology that links occupant injury risk functions, estimated in the laboratory, with real world medical treatment costs by using the abbreviated injury score (AIS). Using our model, the expected medical treatment costs for crash injuries to various body regions and of different severities can be investigated.

First, the simulation results are compared with NHTSA crash data. We used a modified kinematics simulation model that incorporates an F=E(b) function as a supplement to the previous Steffan's model to obtain a more accurate acceleration history a(t). Second, head injury criteria HIC(36) can be calculated from a(t), and we use the injury probability P as a function of HIC(36,) as proposed by Kuppa, to obtain the injury risk function for various AIS values. Third, medical treatment cost models for various AIS values can be calculated by using a regression cost model with real world data. Finally, the injury risk function and medical treatment cost models are linked through AIS values. We establish an integrated methodology and predict medical costs and car safety data using real world police reports, medical treatment costs, and laboratory simulation results.

Using head injuries in frontal crashes as an example, we focus on simulation parameters for different vehicle models, with and without airbags. We specifically examine impact closing speed, Delta-V, and impact directions.

Simulation results can be used to supplement insufficient real crash data, in particular DeltaV, and injury risk results from police crash reports.

The proposed integrated methodology may provide the vehicle industry with a new safety assessment method. Real crash data coupling provides consumers with more realistic and applicable information.