The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform
Chandra R Bhat - One of the best experts on this subject based on the ideXlab platform.
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the joint analysis of Injury Severity of drivers in two vehicle crashes accommodating seat belt use endogeneity
Transportation Research Part B-methodological, 2013Co-Authors: Kibrom A Abay, Rajesh Paleti, Chandra R BhatAbstract:The current study contributes to the existing Injury Severity modeling literature by developing a multivariate probit model of Injury Severity and seat belt use decisions of both drivers involved in two-vehicle crashes. The modeling approach enables the joint modeling of the Injury Severity of multiple individuals involved in a crash, while also recognizing the endogeneity of seat belt use in predicting Injury Severity levels as well as accommodating unobserved heterogeneity in the effects of variables. The proposed model is applied to analyze the Injury Severity of drivers involved in two-vehicle road crashes in Denmark.
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a spatial generalized ordered response model to examine highway crash Injury Severity
Accident Analysis & Prevention, 2013Co-Authors: Marisol Castro, Rajesh Paleti, Chandra R BhatAbstract:Abstract This paper proposes a flexible econometric structure for Injury Severity analysis at the level of individual crashes that recognizes the ordinal nature of Injury Severity categories, allows unobserved heterogeneity in the effects of contributing factors, as well as accommodates spatial dependencies in the Injury Severity levels experienced in crashes that occur close to one another in space. The modeling framework is applied to analyze the Injury Severity sustained in crashes occurring on highway road segments in Austin, Texas. The sample is drawn from the Texas Department of Transportation (TxDOT) crash incident files from 2009 and includes a variety of crash characteristics, highway design attributes, driver and vehicle characteristics, and environmental factors. The results from our analysis underscore the value of our proposed model for data fit purposes as well as to accurately estimate variable effects. The most important determinants of Injury Severity on highways, according to our results, are (1) whether any vehicle occupant is ejected, (2) whether collision type is head-on, (3) whether any vehicle involved in the crash overturned, (4) whether any vehicle occupant is unrestrained by a seat-belt, and (5) whether a commercial truck is involved.
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Spatial Generalized Ordered-Response Model to Examine Highway Crash Injury Severity
2013Co-Authors: Marisol Castro, Rajesh Paleti, Chandra R BhatAbstract:This paper proposes a flexible econometric structure for Injury Severity analysis at the level of individual crashes that recognizes the ordinal nature of Injury Severity categories, allows unobserved heterogeneity in the effects of contributing factors, as well as accommodates spatial dependencies in the Injury Severity levels experienced in crashes that occur close to one another in space. The modeling framework is applied to analyze the Injury Severity sustained in crashes occurring on highway road segments in Austin, Texas. The results from our analysis underscore the value of our proposed model to accurately estimate variable effects.
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a joint econometric analysis of seat belt use and crash related Injury Severity
Accident Analysis & Prevention, 2007Co-Authors: Naveen Eluru, Chandra R BhatAbstract:This paper formulates a comprehensive econometric structure that recognizes two important issues in crash-related Injury Severity analysis. First, the impact of a factor on Injury Severity may be moderated by various observed and unobserved variables specific to an individual or to a crash. Second, seat belt use is likely to be endogenous to Injury Severity. That is, it is possible that intrinsically unsafe drivers do not wear seat belts and are the ones likely to be involved in high Injury Severity crashes because of their unsafe driving habits. The preceding issues are considered in the current research effort through the development of a comprehensive model of seat belt use and Injury Severity that takes the form of a joint correlated random coefficients binary-ordered response system. To our knowledge, this is the first instance of such a model formulation and application not only in the safety analysis literature, but in the econometrics literature in general. The empirical analysis is based on the 2003 General Estimates System (GES) data base. Several types of variables are considered to explain seat belt use and Injury Severity levels, including driver characteristics, vehicle characteristics, roadway design attributes, environmental factors, and crash characteristics. The results, in addition to confirming the effects of various explanatory variables, also highlight the importance of (a) considering the moderating effects of unobserved individual/crash-related factors on the determinants of Injury Severity and (b) seat belt use endogeneity. From a policy standpoint, the results suggest that seat belt non-users, when apprehended in the act, should perhaps be subjected to both a fine (to increase the chances that they wear seat belts) as well as mandatory enrollment in a defensive driving course (to attempt to change their aggressive driving behaviors).
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Joint Econometric Analysis of Seat Belt Use and Crash-Related Injury Severity
2006Co-Authors: Chandra R Bhat, Naveen EluruAbstract:This paper formulates a comprehensive econometric structure that recognizes two important issues in crash-related Injury Severity analysis. First, the impact of a factor on Injury Severity may be moderated by various observed and unobserved variables specific to an individual or to a crash. Second, seat belt use is likely to be endogenous to Injury Severity. That is, it is possible that intrinsically unsafe drivers do not wear seat belts and are the ones likely to be involved in high Injury Severity crashes because of their unsafe driving habits. The empirical analysis is based on the 2003 General Estimates System (GES) data base. Several types of variables are considered to explain seat belt use and Injury Severity levels, including driver characteristics, vehicle characteristics, roadway design attributes, environmental factors, and crash characteristics. The results, in addition to confirming the effects of various explanatory variables, also highlight the importance of (a) considering the moderating effects of unobserved individual/crash-related factors on the determinants of Injury Severity and (b) seat belt use endogeneity. From a policy standpoint, the results suggest that seat belt non-users, when apprehended in the act, should perhaps be subjected to both a fine (to increase the chances that they wear seat belts) as well as mandatory enrollment in a defensive driving course (to attempt to change their aggressive driving behaviors).
Patrick A. Dawson - One of the best experts on this subject based on the ideXlab platform.
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Injury Severity assessment in tibial plateau fractures.
Clinical orthopaedics and related research, 2004Co-Authors: Douglas R. Dirschl, Patrick A. DawsonAbstract:Assessment of Injury Severity is an integral component of the care of the patient with a fracture of the tibial plateau. Devising ways to reliably quantify Injury Severity, and to make predictive links between Injury Severity and outcome, however, has been difficult. Assessment of patient-related factors, such as age, functional capabilities, and medical comorbidities, are necessarily subjective, but certain of these factors clearly shape the treatment plan for a patient with a tibial plateau fracture. Clinical examination findings, such as extent of soft tissue Injury and mediolateral stability of the knee, also play an important role in determining treatment and predicting outcome. Radiographic classification of tibial plateau fractures also is an important determinant of treatment, but current classification systems have suffered from disappointing interobserver reliability. Although the Severity of Injury to the articular cartilage almost certainly affects outcome, there currently are no validated modalities to measure this important factor. More carefully validated tools are needed in many of these areas if we are to perfect our understanding of Injury Severity and establish more accurate correlations between Injury Severity and outcomes.
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Injury Severity assessment in tibial plateau fractures : Symposium
Clinical Orthopaedics and Related Research, 2004Co-Authors: Douglas R. Dirschl, Patrick A. DawsonAbstract:Assessment of Injury Severity is an integral component of the care of the patient with a fracture of the tibial plateau. Devising ways to reliably quantify Injury Severity, and to make predictive links between Injury Severity and outcome, however, has been difficult. Assessment of patient-related factors, such as age, functional capabilities, and medical comorbidities, are necessarily subjective, but certain of these factors clearly shape the treatment plan for a patient with a tibial plateau fracture. Clinical examination findings, such as extent of soft tissue Injury and mediolateral stability of the knee, also play an important role in determining treatment and predicting outcome. Radiographic classification of tibial plateau fractures also is an important determinant of treatment, but current classification systems have suffered from disappointing interobserver reliability. Although the Severity of Injury to the articular cartilage almost certainly affects outcome, there currently are no validated modalities to measure this important factor. More carefully validated tools are needed in many of these areas if we are to perfect our understanding of Injury Severity and establish more accurate correlations between Injury Severity and outcomes.
Douglas R. Dirschl - One of the best experts on this subject based on the ideXlab platform.
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Injury Severity assessment in tibial plateau fractures.
Clinical orthopaedics and related research, 2004Co-Authors: Douglas R. Dirschl, Patrick A. DawsonAbstract:Assessment of Injury Severity is an integral component of the care of the patient with a fracture of the tibial plateau. Devising ways to reliably quantify Injury Severity, and to make predictive links between Injury Severity and outcome, however, has been difficult. Assessment of patient-related factors, such as age, functional capabilities, and medical comorbidities, are necessarily subjective, but certain of these factors clearly shape the treatment plan for a patient with a tibial plateau fracture. Clinical examination findings, such as extent of soft tissue Injury and mediolateral stability of the knee, also play an important role in determining treatment and predicting outcome. Radiographic classification of tibial plateau fractures also is an important determinant of treatment, but current classification systems have suffered from disappointing interobserver reliability. Although the Severity of Injury to the articular cartilage almost certainly affects outcome, there currently are no validated modalities to measure this important factor. More carefully validated tools are needed in many of these areas if we are to perfect our understanding of Injury Severity and establish more accurate correlations between Injury Severity and outcomes.
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Injury Severity assessment in tibial plateau fractures : Symposium
Clinical Orthopaedics and Related Research, 2004Co-Authors: Douglas R. Dirschl, Patrick A. DawsonAbstract:Assessment of Injury Severity is an integral component of the care of the patient with a fracture of the tibial plateau. Devising ways to reliably quantify Injury Severity, and to make predictive links between Injury Severity and outcome, however, has been difficult. Assessment of patient-related factors, such as age, functional capabilities, and medical comorbidities, are necessarily subjective, but certain of these factors clearly shape the treatment plan for a patient with a tibial plateau fracture. Clinical examination findings, such as extent of soft tissue Injury and mediolateral stability of the knee, also play an important role in determining treatment and predicting outcome. Radiographic classification of tibial plateau fractures also is an important determinant of treatment, but current classification systems have suffered from disappointing interobserver reliability. Although the Severity of Injury to the articular cartilage almost certainly affects outcome, there currently are no validated modalities to measure this important factor. More carefully validated tools are needed in many of these areas if we are to perfect our understanding of Injury Severity and establish more accurate correlations between Injury Severity and outcomes.
Naveen Eluru - One of the best experts on this subject based on the ideXlab platform.
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Examining driver Injury Severity in two vehicle crashes - a copula based approach.
Accident; analysis and prevention, 2014Co-Authors: Shamsunnahar Yasmin, Naveen Eluru, Abdul Rawoof Pinjari, Richard TayAbstract:A most commonly identified exogenous factor that significantly affects traffic crash Injury Severity sustained is the collision type variable. Most studies consider collision type only as an explanatory variable in modeling Injury. However, it is possible that each collision type has a fundamentally distinct effect on Injury Severity sustained in the crash. In this paper, we examine the hypothesis that collision type fundamentally alters the Injury Severity pattern under consideration. Toward this end, we propose a joint modeling framework to study collision type and Injury Severity sustained as two dimensions of the Severity process. We employ a copula based joint framework that ties the collision type (represented as a multinomial logit model) and Injury Severity (represented as an ordered logit model) through a closed form flexible dependency structure to study the Injury Severity process. The proposed approach also accommodates the potential heterogeneity (across drivers) in the dependency structure. Further, the study incorporates collision type as a vehicle-level, as opposed to a crash-level variable as hitherto assumed in earlier research, while also examining the impact of a comprehensive set of exogenous factors on driver Injury Severity. The proposed modeling system is estimated using collision data from the province of Victoria, Australia for the years 2006 through 2010.
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a joint econometric analysis of seat belt use and crash related Injury Severity
Accident Analysis & Prevention, 2007Co-Authors: Naveen Eluru, Chandra R BhatAbstract:This paper formulates a comprehensive econometric structure that recognizes two important issues in crash-related Injury Severity analysis. First, the impact of a factor on Injury Severity may be moderated by various observed and unobserved variables specific to an individual or to a crash. Second, seat belt use is likely to be endogenous to Injury Severity. That is, it is possible that intrinsically unsafe drivers do not wear seat belts and are the ones likely to be involved in high Injury Severity crashes because of their unsafe driving habits. The preceding issues are considered in the current research effort through the development of a comprehensive model of seat belt use and Injury Severity that takes the form of a joint correlated random coefficients binary-ordered response system. To our knowledge, this is the first instance of such a model formulation and application not only in the safety analysis literature, but in the econometrics literature in general. The empirical analysis is based on the 2003 General Estimates System (GES) data base. Several types of variables are considered to explain seat belt use and Injury Severity levels, including driver characteristics, vehicle characteristics, roadway design attributes, environmental factors, and crash characteristics. The results, in addition to confirming the effects of various explanatory variables, also highlight the importance of (a) considering the moderating effects of unobserved individual/crash-related factors on the determinants of Injury Severity and (b) seat belt use endogeneity. From a policy standpoint, the results suggest that seat belt non-users, when apprehended in the act, should perhaps be subjected to both a fine (to increase the chances that they wear seat belts) as well as mandatory enrollment in a defensive driving course (to attempt to change their aggressive driving behaviors).
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Joint Econometric Analysis of Seat Belt Use and Crash-Related Injury Severity
2006Co-Authors: Chandra R Bhat, Naveen EluruAbstract:This paper formulates a comprehensive econometric structure that recognizes two important issues in crash-related Injury Severity analysis. First, the impact of a factor on Injury Severity may be moderated by various observed and unobserved variables specific to an individual or to a crash. Second, seat belt use is likely to be endogenous to Injury Severity. That is, it is possible that intrinsically unsafe drivers do not wear seat belts and are the ones likely to be involved in high Injury Severity crashes because of their unsafe driving habits. The empirical analysis is based on the 2003 General Estimates System (GES) data base. Several types of variables are considered to explain seat belt use and Injury Severity levels, including driver characteristics, vehicle characteristics, roadway design attributes, environmental factors, and crash characteristics. The results, in addition to confirming the effects of various explanatory variables, also highlight the importance of (a) considering the moderating effects of unobserved individual/crash-related factors on the determinants of Injury Severity and (b) seat belt use endogeneity. From a policy standpoint, the results suggest that seat belt non-users, when apprehended in the act, should perhaps be subjected to both a fine (to increase the chances that they wear seat belts) as well as mandatory enrollment in a defensive driving course (to attempt to change their aggressive driving behaviors).
Turner M Osler - One of the best experts on this subject based on the ideXlab platform.
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a comparison of the Injury Severity score and the trauma mortality prediction model
Journal of Trauma-injury Infection and Critical Care, 2014Co-Authors: Alan D Cook, Susan Pardee Baker, Jo Weddle, David W Hosmer, Laurent G Glance, Lee Friedman, Turner M OslerAbstract:BACKGROUND: Performance benchmarking requires accurate measurement of Injury Severity. Despite its shortcomings, the Injury Severity Score (ISS) remains the industry standard 40 years after its creation. A new Severity measure, the Trauma Mortality Prediction Model (TMPM), uses either the Abbreviated Injury Scale (AIS) or DRG International Classification of Diseases-9th Rev. (ICD-9) lexicons and may better quantify Injury Severity compared with ISS. We compared the performance of TMPM with ISS and other measures of Injury Severity in a single cohort of patients. METHODS: We included 337,359 patient records with injuries reliably described in both the AIS and the ICD-9 lexicons from the National Trauma Data Bank. Five Injury Severity measures (ISS, maximum AIS score, New Injury Severity Score [NISS], ICD-9-Based Injury Severity Score [ICISS], TMPM) were computed using either the AIS or ICD-9 codes. These measures were compared for discrimination (area under the receiver operating characteristic curve), an estimate of proximity to a model that perfectly predicts the outcome (Akaike information criterion), and model calibration curves. RESULTS: TMPM demonstrated superior receiver operating characteristic curve, Akaike information criterion, and calibration using either the AIS or ICD-9 lexicons. Calibration plots demonstrate the monotonic characteristics of the TMPM models contrasted by the nonmonotonic features of the other prediction models. CONCLUSION: Severity measures were more accurate with the AIS lexicon rather than ICD-9. NISS proved superior to ISS in either lexicon. Since NISS is simpler to compute, it should replace ISS when a quick estimate of Injury Severity is required for AIS-coded injuries. Calibration curves suggest that the nonmonotonic nature of ISS may undermine its performance. TMPM demonstrated superior overall mortality prediction compared with all other models including ISS whether the AIS or ICD-9 lexicons were used. Because TMPM provides an absolute probability of death, it may allow clinicians to communicate more precisely with one another and with patients and families. LEVEL OF EVIDENCE: Disagnostic study, level I; prognostic study, level II. Language: en
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Injury Severity Scoring
Journal of Intensive Care Medicine, 1999Co-Authors: Turner M Osler, Leila S. Nelson, Edward J. BedrickAbstract:The wish to predict outcome following Injury is as old as human history, but the actual measurement of Injury Severity began only 40 years ago. Tools are now available to measure both physical Injury [the Injury Severity Score (ISS)] and physiologic derangement [the Revised Trauma Score (RTS)], as well as their synergistic combination, into a probability of survival score (TRISS). Although these tools are in daily use in most trauma centers, their predictive power is only mediocre. While adequate for estimation of the trauma Severity in populations of patients, these measures have proven inadequate for predicting individual outcomes, and their usefulness in comparing trauma systems and centers has proven problematic. Better alternatives to these tools have been developed, but adoption has been slow because these incremental improvements in predictive power have not been sufficient to allow expanded uses for Injury scoring. We now face the possibility that Injury scoring can never be robust enough to be either clinically useful or the basis for meaningful comparisons between trauma centers. We should continue our quest for improved outcome prediction, but we must resist demands that Injury scoring systems be extended into realms where they may detract from intelligent discourse or damage clinical practice.
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Injury Severity scoring: Perspectives in development and future directions
The American Journal of Surgery, 1993Co-Authors: Turner M OslerAbstract:The impulse to catalogue injuries is as old as human history, but the actual measurement of Injury Severity began only 40 years ago. The rapid development of objective measures for trauma required enormous investments of time and money to accrue large enough data bases to validate these measures. Tools are now available to measure both physical Injury (Injury Severity score) and physiologic Injury (revised trauma score), as well as their synergistic combination into the probability of survival score, and these tools are in everyday use at most trauma centers. Nevertheless, it is likely that further improvement in outcome prediction is possible. The current Injury Severity scoring system is possible. The current Injury Severity scoring system is based on clinically assigned Injury Severity rather than measured outcome, and considers only one Injury per body region. Both of these shortcomings should be addressed. The advent of large computerized data bases will facilitate this process.
