Identifying individual-based injury patterns in multi-trauma road users by using an association rule mining method.

In many road crashes the human body is exposed to high forces, commonly resulting in multiple injuries. This study of linked road crash data aimed to identify co-occurring injuries in multiple injured road users by using a novel application of a data mining technique commonly used in Market Basket Analysis. We expected that some injuries are statistically associated with each other and form Individual-Based Injury Patterns (IBIPs) and further that specific road users are associated with certain IBIPs.

Does injury pattern among major road trauma patients influence prehospital transport decisions regardless of the distance to the nearest trauma centre? - a retrospective study.

Background: Prehospital undertriage occurs when the required level of care for a major trauma patient is underestimated and the patient is transported to a lower-level emergency care facility. One possible reason is that the pattern of injuries exceeding a certain severity threshold is not easily recognizable in the field. The present study aims to examine whether the injury patterns of major road trauma patients are associated with trauma centre transport decisions in Sweden, controlling for the distance from the crash to the nearest trauma centre and other patient characteristics.

Comparing motor-vehicle crash risk of EU and US vehicles.

Objective: This study examined the hypotheses that passenger vehicles meeting European Union (EU) safety standards have similar crashworthiness to United States (US) -regulated vehicles in the US driving environment, and vice versa.

Methods: The first step involved identifying appropriate databases of US and EU crashes that include in-depth crash information, such as estimation of crash severity using Delta-V and injury outcome based on medical records. The next step was to harmonize variable definitions and sampling criteria so that the EU data could be combined and compared to the US data using the same or equivalent parameters.

Prehospital transportation decisions for patients sustaining major trauma in road traffic crashes in Sweden.

Objective: The objective of this study was to evaluate the proportion and characteristics of patients sustaining major trauma in road traffic crashes (RTCs) who could benefit from direct transportation to a trauma center (TC).

Methods: Currently, there is no national classification of TC in Sweden. In this study, 7 university hospitals (UHs) in Sweden were selected to represent a TC level I or level II.

On-Scene Injury Severity Prediction (OSISP) Algorithm for Truck Occupants.

Objective: The aim of this study is to develop an on-scene injury severity prediction (OSISP) algorithm for truck occupants using only accident characteristics that are feasible to assess at the scene of the accident. The purpose of developing this algorithm is to use it as a basis for a field triage tool used in traffic accidents involving trucks. In addition, the model can be valuable for recognizing important factors for improving triage protocols used in Sweden and possibly in other countries with similar traffic environments and prehospital procedures.

On scene injury severity prediction (OSISP) algorithm for car occupants.

Many victims in traffic accidents do not receive optimal care due to the fact that the severity of their injuries is not realized early on. Triage protocols are based on physiological and anatomical criteria and subsequently on mechanisms of injury in order to reduce undertriage. In this study the value of accident characteristics for field triage is evaluated by developing an on scene injury severity prediction (OSISP) algorithm using only accident characteristics that are feasible to assess at the scene of accident.

Identifying the causes of road crashes in Europe.

This research applies a recently developed model of accident causation, developed to investigate industrial accidents, to a specially gathered sample of 997 crashes investigated in-depth in 6 countries. Based on the work of Hollnagel the model considers a collision to be a consequence of a breakdown in the interaction between road users, vehicles and the organisation of the traffic environment. 54% of road users experienced interpretation errors while 44% made observation errors and 37% planning errors.

Exploring inattention and distraction in the SafetyNet Accident Causation Database.

Distraction and inattention are considered to be very important and prevalent factors in the causation of road accidents. There have been many recent research studies which have attempted to understand the circumstances under which a driver becomes distracted or inattentive and how distraction/inattention can be prevented. Both factors are thought to have become more important in recent times partly due to the evolution of in-vehicle information and communication technology.

A test-based method for the assessment of pre-crash warning and braking systems.

In this paper, a test-based assessment method for pre-crash warning and braking systems is presented where the effectiveness of a system is measured by its ability to reduce the number of injuries of a given type or severity in car-to-car rear-end collisions. Injuries with whiplash symptoms lasting longer than 1 month and MAIS2+ injuries in both vehicles involved in the crash are considered in the assessment. The injury reduction resulting from the impact speed reduction due to a pre-crash system is estimated using a method which has its roots in the dose-response model.

Fatal intersection crashes in Norway: patterns in contributing factors and data collection challenges.

Fatal motor vehicle intersection crashes occurring in Norway in the years 2005-2007 were analyzed to identify causation patterns among their underlying contributing factors, and also to assess if the data collection and documentation procedures used by the Norwegian in-depth investigation teams produces the information necessary to do causation pattern analysis. 28 fatal accidents were analyzed. Causation charts of contributing factors were first coded for each driver in each crash using the Driving Reliability and Error Analysis Method (DREAM).