862 resultados para transport-related injury
Resumo:
Ubiquitous access to patient medical records is an important aspect of caring for patient safety. Unavailability of sufficient medical information at the point-ofcare could possibly lead to a fatality. The U.S. Institute of Medicine has reported that between 44,000 and 98,000 people die each year due to medical errors, such as incorrect medication dosages, due to poor legibility in manual records, or delays in consolidating needed information to discern the proper intervention. In this research we propose employing emergent technologies such as Java SIM Cards (JSC), Smart Phones (SP), Next Generation Networks (NGN), Near Field Communications (NFC), Public Key Infrastructure (PKI), and Biometric Identification to develop a secure framework and related protocols for ubiquitous access to Electronic Health Records (EHR). A partial EHR contained within a JSC can be used at the point-of-care in order to help quick diagnosis of a patient’s problems. The full EHR can be accessed from an Electronic Health Records Centre (EHRC) when time and network availability permit. Moreover, this framework and related protocols enable patients to give their explicit consent to a doctor to access their personal medical data, by using their Smart Phone, when the doctor needs to see or update the patient’s medical information during an examination. Also our proposed solution would give the power to patients to modify the Access Control List (ACL) related to their EHRs and view their EHRs through their Smart Phone. Currently, very limited research has been done on using JSCs and similar technologies as a portable repository of EHRs or on the specific security issues that are likely to arise when JSCs are used with ubiquitous access to EHRs. Previous research is concerned with using Medicare cards, a kind of Smart Card, as a repository of medical information at the patient point-of-care. However, this imposes some limitations on the patient’s emergency medical care, including the inability to detect the patient’s location, to call and send information to an emergency room automatically, and to interact with the patient in order to get consent. The aim of our framework and related protocols is to overcome these limitations by taking advantage of the SIM card and the technologies mentioned above. Briefly, our framework and related protocols will offer the full benefits of accessing an up-to-date, precise, and comprehensive medical history of a patient, whilst its mobility will provide ubiquitous access to medical and patient information everywhere it is needed. The objective of our framework and related protocols is to automate interactions between patients, healthcare providers and insurance organisations, increase patient safety, improve quality of care, and reduce the costs.
Resumo:
In order to estimate the safety impact of roadway interventions engineers need to collect, analyze, and interpret the results of carefully implemented data collection efforts. The intent of these studies is to develop Accident Modification Factors (AMF's), which are used to predict the safety impact of various road safety features at other locations or in upon future enhancements. Models are typically estimated to estimate AMF's for total crashes, but can and should be estimated for crash outcomes as well. This paper first describes data collected with the intent estimate AMF's for rural intersections in the state of Georgia within the United Sates. Modeling results of crash prediction models for the crash outcomes: angle, head-on, rear-end, sideswipe (same direction and opposite direction) and pedestrian-involved crashes are then presented and discussed. The analysis reveals that factors such as the Annual Average Daily Traffic (AADT), the presence of turning lanes, and the number of driveways have a positive association with each type of crash, while the median width and the presence of lighting are negatively associated with crashes. The model covariates are related to crash outcome in different ways, suggesting that crash outcomes are associated with different pre-crash conditions.
Resumo:
A national-level safety analysis tool is needed to complement existing analytical tools for assessment of the safety impacts of roadway design alternatives. FHWA has sponsored the development of the Interactive Highway Safety Design Model (IHSDM), which is roadway design and redesign software that estimates the safety effects of alternative designs. Considering the importance of IHSDM in shaping the future of safety-related transportation investment decisions, FHWA justifiably sponsored research with the sole intent of independently validating some of the statistical models and algorithms in IHSDM. Statistical model validation aims to accomplish many important tasks, including (a) assessment of the logical defensibility of proposed models, (b) assessment of the transferability of models over future time periods and across different geographic locations, and (c) identification of areas in which future model improvements should be made. These three activities are reported for five proposed types of rural intersection crash prediction models. The internal validation of the model revealed that the crash models potentially suffer from omitted variables that affect safety, site selection and countermeasure selection bias, poorly measured and surrogate variables, and misspecification of model functional forms. The external validation indicated the inability of models to perform on par with model estimation performance. Recommendations for improving the state of the practice from this research include the systematic conduct of carefully designed before-and-after studies, improvements in data standardization and collection practices, and the development of analytical methods to combine the results of before-and-after studies with cross-sectional studies in a meaningful and useful way.
Resumo:
One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.
Resumo:
The Georgia Institute of Technology is currently performing research that will result in the development and deployment of three instrumentation packages that allow for automated capture of personal travel-related data for a given time period (up to 10 days). These three packages include: A handheld electronic travel diary (ETD) with Global Positioning System (GPS) capabilities to capture trip information for all modes of travel; A comprehensive electronic travel monitoring system (CETMS), which includes an ETD, a rugged laptop computer, a GPS receiver and antenna, and an onboard engine monitoring system, to capture all trip and vehicle information; and a passive GPS receiver, antenna, and data logger to capture vehicle trips only.
Resumo:
Travel surveys were conducted for collecting data related to school students’ travel at Kelvin Grove Urban Village (KGUV). Currently, KGUV has school students studying at grade 10 to 12. As a part of data collection process, travel surveys were undertaken for school students studying. This document contains the questionnaire form used to collect the demographic and travel data related to school students at KGUV. The surveys forms were hand delivered to the school and the responses were collected back via reply paid envelop provided with the questionnaire form.
Resumo:
Ubiquitous access to patient medical records is an important aspect of caring for patient safety. Unavailability of sufficient medical information at the patient point-of-care could possibly lead to a fatality. In this paper we propose employing emergent technologies such as Java SIM Cards (JSC),Smart Phones (SP), Next Generation Networks (NGN), Near Field Communications (NFC), Public Key Infrastructure (PKI), and Biometric Identification to develop a secure framework and related protocols for ubiquitous access to Electronic Health Records (EHRs). A partial EHR contained within a JSC can be used at the patient point-of-care in order to help quick diagnosis of a patient’s problems. The full EHR can be accessed from an Electronic Healthcare Records Centre (EHRC).
Resumo:
Earlier studies have shown that the influence of fixation stability on bone healing diminishes with advanced age. The goal of this study was to unravel the relationship between mechanical stimulus and age on callus competence at a tissue level. Using 3D in vitro micro-computed tomography derived metrics, 2D in vivo radiography, and histology, we investigated the influences of age and varying fixation stability on callus size, geometry, microstructure, composition, remodeling, and vascularity. Compared were four groups with a 1.5-mm osteotomy gap in the femora of Sprague–Dawley rats: Young rigid (YR), Young semirigid (YSR), Old rigid (OR), Old semirigid (OSR). Hypothesis was that calcified callus microstructure and composition is impaired due to the influence of advanced age, and these individuals would show a reduced response to fixation stabilities. Semirigid fixations resulted in a larger ΔCSA (Callus cross-sectional area) compared to rigid groups. In vitro μCT analysis at 6 weeks postmortem showed callus bridging scores in younger animals to be superior than their older counterparts (pb0.01). Younger animals showed (i) larger callus strut thickness (pb0.001), (ii) lower perforation in struts (pb0.01), and (iii) higher mineralization of callus struts (pb0.001). Callus mineralization was reduced in young animals with semirigid fracture fixation but remained unaffected in the aged group. While stability had an influence, age showed none on callus size and geometry of callus. With no differences observed in relative osteoid areas in the callus ROI, old as well as semirigid fixated animals showed a higher osteoclast count (pb0.05). Blood vessel density was reduced in animals with semirigid fixation (pb0.05). In conclusion, in vivo monitoring indicated delayed callus maturation in aged individuals. Callus bridging and callus competence (microstructure and mineralization) were impaired in individuals with an advanced age. This matched with increased bone resorption due to higher osteoclast numbers. Varying fixator configurations in older individuals did not alter the dominant effect of advanced age on callus tissue mineralization, unlike in their younger counterparts. Age-associated influences appeared independent from stability. This study illustrates the dominating role of osteoclastic activity in age-related impaired healing, while demonstrating the optimization of fixation parameters such as stiffness appeared to be less effective in influencing healing in aged individuals.
Resumo:
Dental pulp cells (DPCs) are capable of differentiating into odontoblasts that secrete reparative dentin after pulp injury. The molecular mechanisms governing reparative dentinogenesis are yet to be fully understood. Here we investigated the differential protein profile of human DPCs undergoing odontogenic induction for 7 days. Using two-dimensional differential gel electrophoresis coupled with matrix-assisted laser adsorption ionization time of flight mass spectrometry, 2 3 protein spots related to the early odontogenic differentiation were identified. These proteins included cytoskeleton proteins, nuclear proteins, cell membrane-bound molecules, proteins involved in matrix synthesis, and metabolic enzymes. The expression of four identified proteins, which were heteronuclear ribonuclear proteins C, annexin VI, collagen type VI, and matrilin-2, was confirmed by Western blot and real-time realtime polymerase chain reaction analyses. This study generated a proteome reference map during odontoblast- like differentiation of human DPCs, which will be valuable to better understand the underlying molecular mechanisms in odontoblast-like differentiation.
Resumo:
Introduction: Floods are the most common hazard to cause disasters and have led to extensive morbidity and mortality throughout the world. The impact of floods on the human community is related directly to the location and topography of the area, as well as human demographics and characteristics of the built environment. Objectives: The aim of this study is to identify the health impacts of disasters and the underlying causes of health impacts associated with floods. A conceptual framework is developed that may assist with the development of a rational and comprehensive approach to prevention, mitigation, and management. Methods: This study involved an extensive literature review that located >500 references, which were analyzed to identify common themes, findings, and expert views. The findings then were distilled into common themes. Results: The health impacts of floods are wide ranging, and depend on a number of factors. However, the health impacts of a particular flood are specific to the particular context. The immediate health impacts of floods include drowning, injuries, hypothermia, and animal bites. Health risks also are associated with the evacuation of patients, loss of health workers, and loss of health infrastructure including essential drugs and supplies. In the mediumterm, infected wounds, complications of injury, poisoning, poor mental health, communicable diseases, and starvation are indirect effects of flooding. In the long-term, chronic disease, disability, poor mental health, and poverty-related diseases including malnutrition are the potential legacy. Conclusions: This article proposes a structured approach to the classification of the health impacts of floods and a conceptual framework that demonstrates the relationships between floods and the direct and indirect health consequences.
Resumo:
Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites
Resumo:
Predicting safety on roadways is standard practice for road safety professionals and has a corresponding extensive literature. The majority of safety prediction models are estimated using roadway segment and intersection (microscale) data, while more recently efforts have been undertaken to predict safety at the planning level (macroscale). Safety prediction models typically include roadway, operations, and exposure variables—factors known to affect safety in fundamental ways. Environmental variables, in particular variables attempting to capture the effect of rain on road safety, are difficult to obtain and have rarely been considered. In the few cases weather variables have been included, historical averages rather than actual weather conditions during which crashes are observed have been used. Without the inclusion of weather related variables researchers have had difficulty explaining regional differences in the safety performance of various entities (e.g. intersections, road segments, highways, etc.) As part of the NCHRP 8-44 research effort, researchers developed PLANSAFE, or planning level safety prediction models. These models make use of socio-economic, demographic, and roadway variables for predicting planning level safety. Accounting for regional differences - similar to the experience for microscale safety models - has been problematic during the development of planning level safety prediction models. More specifically, without weather related variables there is an insufficient set of variables for explaining safety differences across regions and states. Furthermore, omitted variable bias resulting from excluding these important variables may adversely impact the coefficients of included variables, thus contributing to difficulty in model interpretation and accuracy. This paper summarizes the results of an effort to include weather related variables, particularly various measures of rainfall, into accident frequency prediction and the prediction of the frequency of fatal and/or injury degree of severity crash models. The purpose of the study was to determine whether these variables do in fact improve overall goodness of fit of the models, whether these variables may explain some or all of observed regional differences, and identifying the estimated effects of rainfall on safety. The models are based on Traffic Analysis Zone level datasets from Michigan, and Pima and Maricopa Counties in Arizona. Numerous rain-related variables were found to be statistically significant, selected rain related variables improved the overall goodness of fit, and inclusion of these variables reduced the portion of the model explained by the constant in the base models without weather variables. Rain tends to diminish safety, as expected, in fairly complex ways, depending on rain frequency and intensity.
Resumo:
Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.
Resumo:
National estimates of the prevalence of child abuse-related injuries are obtained from a variety of sectors including welfare, justice, and health resulting in inconsistent estimates across sectors. The International Classification of Diseases (ICD) is used as the international standard for categorising health data and aggregating data for statistical purposes, though there has been limited validation of the quality, completeness or concordance of these data with other sectors. This research study examined the quality of documentation and coding of child abuse recorded in hospital records in Queensland and the concordance of these data with child welfare records. A retrospective medical record review was used to examine the clinical documentation of over 1000 hospitalised injured children from 20 hospitals in Queensland. A data linkage methodology was used to link these records with records in the child welfare database. Cases were sampled from three sub-groups according to the presence of target ICD codes: Definite abuse, Possible abuse, unintentional injury. Less than 2% of cases coded as being unintentional were recoded after review as being possible abuse, and only 5% of cases coded as possible abuse cases were reclassified as unintentional, though there was greater variation in the classification of cases as definite abuse compared to possible abuse. Concordance of health data with child welfare data varied across patient subgroups. This study will inform the development of strategies to improve the quality, consistency and concordance of information between health and welfare agencies to ensure adequate system responses to children at risk of abuse.