A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data.
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ABSTRACT:
SUBMITTER: Ye X
PROVIDER: S-EPMC5965849 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
Publications
A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data.
Ye Xin X Wang Ke K Zou Yajie Y Lord Dominique D
PloS one 20180523 5
This paper develops a semi-nonparametric Poisson regression model to analyze motor vehicle crash frequency data collected from rural multilane highway segments in California, US. Motor vehicle crash frequency on rural highway is a topic of interest in the area of transportation safety due to higher driving speeds and the resultant severity level. Unlike the traditional Negative Binomial (NB) model, the semi-nonparametric Poisson regression model can accommodate an unobserved heterogeneity follow ...[more]
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Project description:BackgroundAdministrative healthcare databases, such as Medicare, are increasingly used to identify groups at risk of a crash. However, they only contain information on crash-related injuries, not all crashes. If the driver characteristics associated with crash and crash-related injury differ, conflating the two may result in ineffective or imprecise policy interventions.MethodsWe linked 10 years (2008-2017) of Medicare claims to New Jersey police crash reports to compare the demographics, clinical diagnoses, and prescription drug dispensings for crash-involved drivers ≥ 68 years with a police-reported crash to those with a claim for a crash-related injury. We calculated standardized mean differences to compare characteristics between groups.ResultsCrash-involved drivers with a Medicare claim for an injury were more likely than those with a police-reported crash to be female (62.4% vs. 51.8%, standardized mean difference [SMD] = 0.30), had more clinical diagnoses including Alzheimer's disease and related dementias (13.0% vs. 9.2%, SMD = 0.20) and rheumatoid arthritis/osteoarthritis (69.5% vs 61.4%, SMD = 0.20), and a higher rate of dispensing for opioids (33.8% vs 27.6%, SMD = 0.18) and antiepileptics (12.9% vs 9.6%, SMD = 0.14) prior to the crash. Despite documented inconsistencies in coding practices, findings were robust when restricted to claims indicating the injured party was the driver or was left unspecified.ConclusionsTo identify effective mechanisms for reducing morbidity and mortality from crashes, researchers should consider augmenting administrative datasets with information from police crash reports, and vice versa. When those data are not available, we caution researchers and policymakers against the tendency to conflate crash and crash-related injury when interpreting their findings.
| S-EPMC11318118 | biostudies-literature
Project description:To determine whether emergency physicians (EPs) and prehospital emergency medical services (EMS) personnel differ in their assessment of motor vehicle crash (MVC) severity and the potential for serious injury when viewing crash scene photographs.Attending and resident EPs, paramedics, and emergency medical technicians (EMTs) from a single emergency medicine system used a web-based survey platform to rate the severity of 100 crash photographs on a 10-point Likert scale (Crash Score) and the potential for serious injury on a 0-100% scale (Injury Score). Serious injury was defined as skull fracture or intracranial bleeding, spine fracture or spinal cord injury, intrathoracic or intraabdominal injury, or long bone fracture. Crash and Injury Scores were stratified into EP and paramedic/EMT (EMS) groups and the mean score was calculated for each photo. Spearman rank correlation coefficients with 95% confidence intervals (95% CI) and Bland-Altman plots were constructed to assess agreement. Secondary analyses were performed after categorizing data into quartiles based on participants' estimations of MVC severity.A total of 54 attending and 53 resident EPs, 156 paramedics, and 34 EMTs were invited to participate in the survey. Of these, 39 (72%) attending and 46 (87%) resident EPs, 107 (69%) paramedics, and 17 (50%) EMTs completed the survey. A total of 183 (88%) surveys were completed in full. The overall Crash Score correlation coefficient between EPs and EMS was 0.98 (95% CI, 0.97-0.99). The Crash Score correlation coefficients for each quartile were 0.86 (0.57-0.97), 0.93 (0.85-0.96), 0.58 (0.16-0.85), and 0.88 (0.66-0.97), respectively. The overall Injury Score correlation coefficient between EPs and EMS was 0.98 (0.88-0.97). The Injury Score correlation coefficients for each quartile were 0.94 (0.48-0.91), 0.76 (0.50-0.92), 0.80 (0.69-1.00), and 0.94 (0.57-0.97), respectively.Although overall agreement between EPs and EMS personnel was excellent, differences in estimation of crash severity and potential for injury were identified among crashes estimated to be moderate in severity.
| S-EPMC4915374 | biostudies-literature
Project description:ImportanceMotor vehicle crashes (MVCs) are an important public health concern. Recent trends suggest that introducing rideshare services has decreased the incidence of MVCs. However, detailed analyses linking rideshare volume, convictions for impaired driving, and nonfatal MVC traumas remain inconclusive.ObjectiveTo determine if there is an association between rideshare use and MVC traumas and convictions for impaired driving in Houston, Texas.Design, setting, and participantsThis multicenter cohort study was conducted between January 2007 and November 2019 with hospital data from the Red Duke Trauma Institute within the Memorial Hermann Hospital-Texas Medical Center and Ben Taub General Hospital. Rideshare data from Uber and Google covered trips taken within Houston, Texas, from February 2014 (the date of deployment of Uber to Houston) to December 2018. Impaired driving convictions included all indictments made by the Harris County, Texas, District Attorney's office from January 2007 to December 2018. All adults with MVC traumas evaluated at both centers in the study population (individuals >16 years with a mechanism of injury classified under "motor vehicle collision") were included. Impaired driving incidents were included only if the final legal outcome was conviction.Main outcomes and measuresThe primary study outcomes were the incident rate ratios for hourly MVC traumas and daily impaired driving convictions.ResultsA total of 23 491 MVC traumas (involving patients with a mean [SD] age of 37.9 [17.8] years and 14 603 male individuals [62.1%]), 93 742 impaired driving convictions, and more than 24 million Uber rides were analyzed. Following the introduction of Uber in February 2014, MVC traumas decreased by 23.8% (from a mean [SD] of 0.26 [0.04] to 0.21 [0.06] trauma incidents per hour) during peak trauma periods (Friday and Saturday nights). The incident rate ratio of MVC traumas following Uber deployment was 0.33 (95% CI, 0.17-0.67) per 1000 indexed rides (P = .002). Furthermore, rideshare use was associated with a significant, geographically linked reduction in impaired driving convictions between January 2014 to December 2019 (incidence rate ratio, 0.76 [95% CI, 0.73-0.78]; P < .001).Conclusions and relevanceIn this study, introducing rideshare services in the Houston metropolitan area was associated with significant reductions in MVC traumas and impaired driving convictions. Increased use of rideshares may be an effective means of reducing impaired driving and decreasing rate of MVC traumas.
| S-EPMC8190695 | biostudies-literature
Project description:OBJECTIVE:Characterization of the severity of injury should account for both mortality and disability. The objective of this study was to develop a disability metric for thoracic injuries in motor vehicle crashes (MVCs) and compare the functional outcomes between the pediatric and adult populations. METHODS:Disability risk (DR) was quantified using Functional Independence Measure (FIM) scores within the National Trauma Data Bank for the most frequently occurring Abbreviated Injury Scale (AIS) 2-5 thoracic injuries. Occupants with thoracic injury were classified as disabled or not disabled based on the FIM scale, and comparisons were made between the following age groups: pediatric, adult, middle-aged, and older occupants (ages 7-18, 19-45, 46-65, and 66+, respectively). For each age group, DR was calculated by dividing the number of patients who were disabled and sustained a given injury by the number of patients who sustained a given injury. To account for the effect of higher severity co-injuries, a maximum AIS adjusted DR (DRMAIS) was also calculated for each injury. DR and DRMAIS could range from 0 to 100% disability risk. RESULTS:The mean DRMAIS for MVC thoracic injuries was 20% for pediatric occupants, 22% for adults, 29% for middle-aged adults, and 43% for older adults. Older adults possessed higher DRMAIS values for diaphragm laceration/rupture, heart laceration, hemo/pneumothorax, lung contusion/laceration, and rib and sternum fracture compared to the other age groups. The pediatric population possessed a higher DRMAIS value for flail chest compared to the other age groups. CONCLUSION:Older adults had significantly greater overall disability than each of the other age groups for thoracic injuries. The developed disability metrics are important in quantifying the significant burden of injuries and loss of quality life years. Such metrics can be used to better characterize severity of injury and further the understanding of age-related differences in injury outcomes, which can influence future age-specific modifications to AIS.
| S-EPMC6233316 | biostudies-literature
Project description:OBJECTIVE:The objective of the study was to develop a disability-based metric for motor vehicle crash (MVC) injuries, with a focus on head injuries, and compare the functional outcomes between the pediatric and adult populations. METHODS:Disability risk (DR) was quantified using Functional Independence Measure (FIM) scores within the National Trauma Data Bank-Research Data System (NTDB-RDS) for the top 95% most frequently occurring Abbreviated Injury Scale (AIS) 3, 4, and 5 head injuries in NASS-CDS 2000-2011. Pediatric (ages 7-18), adult (19-45), middle-aged (46-65), and older adult (66+) patients with an FIM score available who were alive at discharge and had an AIS 3, 4, or 5 injury were included in the study. The NTDB-RDS contains a truncated form of the FIM instrument, including 3 items (self-feed, locomotion, and verbal expression), each graded on a scale of 1 (full functional dependence) to 4 (full functional independence). Patients within each age group were classified as disabled or not disabled based on the FIM scale. The DR was calculated for each age group by dividing the number of patients who sustained a specific injury and were disabled by the number of patients who sustained the specific injury. To account for the impact of more severe associated coinjuries, a maximum AIS (MAIS) adjusted DR (DRMAIS) was also calculated for each injury. DR and DRMAIS ranged from 0 (0% disability risk) to 1 (100% disability risk). RESULTS:An analysis of the most frequent FIM components associated with disabling MVC head injuries revealed that disability across all 3 items (self-feed, locomotion, and expression) was the most frequent for pediatric and adult patients. Only locomotion was the most frequent for middle-aged and older adults. The mean DRMAIS for MVC head injuries was 35% for pediatric patients, 36% for adults, 38% for middle-aged adults, and 44% for older adults. Further analysis was conducted by grouping the head injuries into 8 groups based on the structure of injury and injury type. The pediatric population possessed higher DRMAIS values for brain stem injuries as well as loss of consciousness injuries. Older adults possessed higher DRMAIS values for contusion/hemorrhage injuries, epidural hemorrhage, intracerebral hemorrhage, skull fracture, and subdural/subarachnoid hemorrhage. CONCLUSION:At-risk populations such as pediatric and older adult patients possessed higher DRMAIS values for different head injuries. Disability in pediatric patients is critical due to loss of quality life years. Disability risk can supplement severity metrics to improve the ability of such metrics to discriminate the severity of different injuries that do not lead to death. Understanding of age-related differences in injury outcomes when compared to adults could inform future age-specific modifications to the AIS.
| S-EPMC6211837 | biostudies-literature
Project description:PURPOSE:Although motor vehicle crashes are the leading cause of death for adolescents, there is a scarcity of research addressing adolescents' lack of pre-licensure practical driving experience, which is theorized to increase their post-licensure crash risk. METHODS:Utilizing police-reported crashes and survey data from a randomized and quasi-randomized trial (n?=?458 adolescents, 16 or 17 years of age at enrollment), the impact of a parent-directed supervised practice driving intervention and a comprehensive on-road driving assessment (ODA) with feedback was evaluated on adolescent drivers' motor vehicle crashes involvement. RESULTS:Compared with the control condition, a nonsignificant 20% relative reduction in risk was observed for the parent-directed intervention: adjusted hazard ratio ?=?.80 (95% confidence interval [CI] .44, 1.43); the unadjusted absolute risk reduction was 1.1% (95% CI -4.4, 7.1). Exposure to the ODA resulted in an 53% relative reduction of risk: adjusted hazard ratio ?=?.47 (95% CI .24, .91); the unadjusted absolute risk reduction was 5.4% (95% CI -.3, 10.7). CONCLUSIONS:Comprehensive ODA might be protective for adolescents; however, additional research is needed.
| S-EPMC5818292 | biostudies-literature
Project description:BACKGROUND:Law enforcement traffic stops are one of the most common entryways to the US justice system. Conventional frameworks suggest traffic stops promote public safety by reducing dangerous driving practices and non-vehicular crime. Law enforcement agencies have wide latitude in enforcement, including prioritization of stop types: (1) safety (e.g. moving violation) stops, (2) investigatory stops, or (3) economic (regulatory and equipment) stops. In order to prevent traffic crash fatalities and reduce racial disparities, the police department of Fayetteville, North Carolina significantly re-prioritized safety stops. METHODS:Annual traffic stop, motor vehicle crash, and crime data from 2002 to 2016 were combined to examine intervention (2013-2016) effects. Fayetteville was compared against synthetic control agencies built from 8 similar North Carolina agencies by weighted matching on pre-intervention period trends and comparison against post-intervention trends. RESULTS:On average over the intervention period as compared to synthetic controls, Fayetteville increased both the number of safety stops +?121% (95% confidence interval?+?17%, +?318%) and the relative proportion of safety stops (+?47%). Traffic crash and injury outcomes were reduced, including traffic fatalities -?28% (-?64%, +?43%), injurious crashes -?23% (-?49%, +?16%), and total crashes -?13% (-?48%, +?21%). Disparity measures were reduced, including Black percent of traffic stops -?7% (-?9%, -?5%) and Black vs. White traffic stop rate ratio?-?21% (-?29%, -?13%). In contrast to the Ferguson Effect hypothesis, the relative de-prioritization of investigatory stops was not associated with an increase in non-traffic crime outcomes, which were reduced or unchanged, including index crimes -?10% (-?25%, +?8%) and violent crimes -?2% (-?33%, +?43%). Confidence intervals were estimated using a different technique and, given small samples, may be asymmetrical. CONCLUSIONS:The re-prioritization of traffic stop types by law enforcement agencies may have positive public health consequences both for motor vehicle injury and racial disparity outcomes while having little impact on non-traffic crime.
| S-EPMC6970293 | biostudies-literature
Project description:Whiplash injury is a common consequence of motor vehicle crashes (MVC), yet it is also one of the most poorly understood. While more than 50% of those injured should expect to rapidly recover, others are not as fortunate with approximately 25% of those exposed to and injured in an MVC transitioning from acute to chronic pain and disability. The purpose of this prospective study was to determine if the severity and direction of collisions involving participants enrolled in a longitudinal study of recovery from whiplash are able to differentiate between different recovery groups based on the neck disability index (NDI) percentage scores at 3-months, and if these crash specific parameters are associated with known risk factors for recovery. Here, we examined objective collision data, repair invoices, and characteristics of the crash for 37 acutely injured participants consented and enrolled at their emergency department visit and further assessed at three time points; < 1 week, 2-weeks, and 3-months post MVC. Collision data were used to reconstruct and estimate the severity of the crash and determine if they aligned with the heterogeneity of whiplash injury recovery. Wilcoxon rank sum tests were used to determine if % scores on the Neck Disability Index (NDI) at 3-months post MVC were associated with the following variables: sex, head turned at time of impact, seatbelt use, whether or not airbags deployed, if the vehicle was struck while stopped or while turning, or the principle direction of force (PDOF). Spearman's correlation coefficients were used to determine if NDI at 3-months post MVC was associated with age, Body Mass Index, pain-related disability at baseline, signs of post-traumatic distress, intrusion/hyperarousal, negative affect, pain intensity, estimated speed change from the impact, and damage estimates (in US$). There was a significant positive association between self-reported neck disability at 3-months post MVC, post-traumatic distress, negative affect and uncontrolled pain. There was no direct effect of participant characteristics, arousal, intrusion/hyperarousal sub-score, damage, PDOF, speed change, or other crash characteristics. Established crash parameters were not associated with the heterogeneity of whiplash injury recovery in a small sample of injured participants.
| S-EPMC6892505 | biostudies-literature
Project description:Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.
| S-EPMC3024001 | biostudies-literature
Project description:Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.
| S-EPMC3288408 | biostudies-literature