10 resultados para Trauma oclusal

em DigitalCommons@The Texas Medical Center


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An understanding of interruptions in healthcare is important for the design, implementation, and evaluation of health information systems and for the management of clinical workflow and medical errors. The purpose of this study is to identify and classify the types of interruptions experienced by Emergency Department(ED) nurses working in a Level One Trauma Center. This was an observational field study of Registered Nurses (RNs) employed in a Level One Trauma Center using the shadowing method. Results of the study indicate that nurses were both recipients and initiators of interruptions. Telephones, pagers, and face-to-face conversations were the most common sources of interruptions. Unlike other industries, the healthcare community has not systematically studied interruptions in clinical settings to determine and weigh the necessity of the interruption against their sometimes negative results such as medical errors, decreased efficiency, and increased costs. Our study presented here is an initial step to understand the nature, causes, and effects of interruptions, thereby improving both the quality of healthcare and patient safety. We developed an ethnographic data collection technique and a data coding method for the capturing and analysis of interruptions. The interruption data we collected are systematic, comprehensive, and close to exhaustive. They confirmed the findings from earlier studies by other researchers that interruptions are frequent events in critical care and other healthcare settings. We are currently using these data to analyze the workflow dynamics of ED clinicians, to identify the bottlenecks of information flow, and to develop interventions to improve the efficiency of emergency care through the management of interruptions.

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An understanding of interruptions in healthcare is important for the design, implementation, and evaluation of health information systems and for the management of clinical workflow and medical errors. The purpose of this study is to identify and classify the types of interruptions experienced by ED nurses working in a Level One Trauma Center. This was an observational field study of Registered Nurses employed in a Level One Trauma Center using the shadowing method. Results of the study indicate that nurses were both recipients and initiators of interruptions. Telephone, pagers, and face-to-face conversations were the most common sources of interruptions. Unlike other industries, the outcomes caused by interruptions resulting in medical errors, decreased efficiency and increased cost have not been systematically studied in healthcare. Our study presented here is an initial step to understand the nature, causes, and effects of interruptions, and to develop interventions to manage interruptions to improve healthcare quality and patient safety. We developed an ethnographic data collection technique and a data coding method for the capturing and analysis of interruptions. The interruption data we collected are systematic, comprehensive, and close to exhaustive. They confirmed the findings from early studies by other researchers that interruptions are frequent events in critical care and other healthcare settings. We are currently using these data to analyze the workflow dynamics of ED clinicians, identify the bottlenecks of information flow, and develop interventions to improve the efficiency of emergency care through the management of interruptions.

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Efforts have been made to provide supplemental funding to emergency departments to offset the costs of uncompensated medical care. But a problem exists within the trauma system in Texas that has largely been overlooked by the state. This project will focus on the lack of funding available to physicians and on-call specialists who contract with hospitals to provide emergency care. ^ A lack of funding and reimbursement for emergency care is directly influencing the number of medical specialists willing to provide emergency treatment in hospitals on a contractual basis. A shortage of emergency physicians has an impact on the public health of all Texans who may need trauma care in a hospital. Specifically, a shortage of emergency physicians can lead to a complete denial of specialty emergency health care, a delay in patient treatment, and increased ambulance diversions. Quality and access barriers to emergency services undoubtedly threaten the stability of the trauma care system in Texas and the health status of its citizens. ^ In 2003, Texas took a significant step towards addressing the issue of uncompensated care provided by the trauma system and passed House Bill 3588, creating the Trauma Facilities and Emergency Medical Services Fund (“the Trauma Fund”). However, the primary shortfall to this legislation is that the Trauma Fund is only available to emergency medical service providers and hospitals. The Trauma Fund does little to help offset the cost incurred by contracting physicians and on-call specialists who provide emergency services to the uninsured. ^ This paper addresses how funding shortages for emergency department physicians negatively impact the trauma care system in Texas and the policy options available to create physician funding to offset the cost of uncompensated trauma care. Ultimately this paper concludes that although creating a new funding stream similar to the actions taken in other states would be a dramatic step towards addressing the problem, the political process in Texas may slow implementation of this option. Consequently, modifying existing legislation, although the weaker of the options, may be more attractive to those looking for immediate action. ^

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Objective. In 2003, the State of Texas instituted the Driver Responsibility Program (TDRP), a program consisting of a driving infraction point system coupled with a series of graded fines and annual surcharges for specific traffic violations such as driving while intoxicated (DWI). Approximately half of the revenues generated are earmarked to be disbursed to the state's trauma system to cover uncompensated trauma care costs. This study examined initial program implementation, the impact of trauma system funding, and initial impact on impaired driving knowledge, attitudes and behaviors. A model for targeted media campaigns to improve the program's deterrence effects was developed. ^ Methods. Data from two independent driver survey samples (conducted in 1999 and 2005), department of public safety records, state health department data and a state auditor's report were used to evaluate the program's initial implementation, impact and outcome with respect to drivers' impaired driving knowledge, attitudes and behavior (based on constructs of social cognitive theory) and hospital uncompensated trauma care funding. Survey results were used to develop a regression model of high risk drivers who should be targeted to improve program outcome with respect to deterring impaired driving. ^ Results. Low driver compliance with fee payment (28%) and program implementation problems were associated with lower surcharge revenues in the first two years ($59.5 million versus $525 million predicted). Program revenue distribution to trauma hospitals was associated with a 16% increase in designated trauma centers. Survey data demonstrated that only 28% of drivers are aware of the TDRP and that there has been no initial impact on impaired driving behavior. Logistical regression modeling suggested that target media campaigns highlighting the likelihood of DWI detection by law enforcement and the increased surcharges associated with the TDRP are required to deter impaired driving. ^ Conclusions. Although the TDRP raised nearly $60 million in surcharge revenue for the Texas trauma system over the first two years, this study did not find evidence of a change in impaired driving knowledge, attitudes or behaviors from 1999 to 2005. Further research is required to measure whether the program is associated with decreased alcohol-related traffic fatalities. ^

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Objective. The study reviewed one year of Texas hospital discharge data and Trauma Registry data for the 22 trauma services regions in Texas to identify regional variations in capacity, process of care and clinical outcomes for trauma patients, and analyze the statistical associations among capacity, process of care, and outcomes. ^ Methods. Cross sectional study design covering one year of state-wide Texas data. Indicators of trauma capacity, trauma care processes, and clinical outcomes were defined and data were collected on each indicator. Descriptive analyses were conducted of regional variations in trauma capacity, process of care, and clinical outcomes at all trauma centers, at Level I and II trauma centers and at Level III and IV trauma centers. Multilevel regression models were performed to test the relations among trauma capacity, process of care, and outcome measures at all trauma centers, at Level I and II trauma centers and at Level III and IV trauma centers while controlling for confounders such as age, gender, race/ethnicity, injury severity, level of trauma centers and urbanization. ^ Results. Significant regional variation was found among the 22 trauma services regions across Texas in trauma capacity, process of care, and clinical outcomes. The regional trauma bed rate, the average staffed bed per 100,000 varied significantly by trauma service region. Pre-hospital trauma care processes were significantly variable by region---EMS time, transfer time, and triage. Clinical outcomes including mortality, hospital and intensive care unit length of stay, and hospital charges also varied significantly by region. In multilevel regression analysis, the average trauma bed rate was significantly related to trauma care processes including ambulance delivery time, transfer time, and triage after controlling for age, gender, race/ethnicity, injury severity, level of trauma centers, and urbanization at all trauma centers. Transfer time only among processes of care was significant with the average trauma bed rate by region at Level III and IV. Also trauma mortality only among outcomes measures was significantly associated with the average trauma bed rate by region at all trauma centers. Hospital charges only among outcomes measures were statistically related to trauma bed rate at Level I and II trauma centers. The effect of confounders on processes and outcomes such as age, gender, race/ethnicity, injury severity, and urbanization was found significantly variable by level of trauma centers. ^ Conclusions. Regional variation in trauma capacity, process, and outcomes in Texas was extensive. Trauma capacity, age, gender, race/ethnicity, injury severity, level of trauma centers and urbanization were significantly associated with trauma process and clinical outcomes depending on level of trauma centers. ^ Key words: regionalized trauma systems, trauma capacity, pre-hospital trauma care, process, trauma outcomes, trauma performance, evaluation measures, regional variations ^

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Introduction. Injury mortality was classically described with a tri-modal distribution, with immediate deaths at the scene, early deaths due to hemorrhage, and late deaths from organ failure. We hypothesized that trauma systems development have improved pre-hospital care, early resuscitation, and critical care, and altered this pattern. ^ Methods. This is a population-based study of all trauma deaths in an urban county with a mature trauma system (n=678, median age 33 years, 81% male, 43% gunshot, 20% motor vehicle crashes). Deaths were classified as immediate (scene), early (in hospital, ≤ 4 hours from injury), or late (>4 hours post injury). Multinomial regression was used to identify independent predictors of immediate and early vs. late deaths, adjusted for age, gender, race, intention, mechanism, toxicology and cause of death. ^ Results. There were 416 (61%) immediate, 199 (29%) early, and 63 (10%) late deaths. Immediate deaths remained unchanged and early deaths occurred much earlier (median 52 minutes vs. 120). However, unlike the classic trimodal distribution, there was no late peak. Intentional injuries, alcohol intoxication, asphyxia, and injuries to the head and chest were independent predictors of immediate deaths. Alcohol intoxication and injuries to the chest were predictors of early deaths, while pelvic fractures and blunt assaults were associated with late deaths. ^ Conclusion. Trauma deaths now have a bimodal distribution. Elimination of the late peak likely represents advancements in resuscitation and critical care that have reduced organ failure. Further reductions in mortality will likely come from prevention of intentional injuries, and injuries associated with alcohol intoxication. ^

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Trauma is a leading cause of death worldwide, and is thus a major public health concern. Improving current resuscitation strategies may help to reduce morbidity and mortality from trauma, and clinical research plays an important role in addressing these issues. This thesis is a secondary analysis of data that was collected for a randomized clinical trial being conducted at Ben Taub General Hospital. The trial is designed to compare a hypotensive resuscitation strategy to standard fluid resuscitation for the early treatment of trauma patients in hemorrhagic shock. This thesis examines the clinical outcomes from the first 90 subjects enrolled in the study, with the primary aim of assessing the safety of hypotensive resuscitation within the trauma population. ^ Patients in hemorrhagic shock who required emergent surgery were randomized to one of two arms of the study. Those in the experimental (LMAP) arm were managed with a hypotensive resuscitation strategy in which the target mean arterial pressure was 50mmHg. Those in the control (HMAP) arm were managed with standard fluid resuscitation to a target mean arterial pressure of 65mmHg. Patients were followed for 30 days. Mortality, post-operative complications, and other clinical data were prospectively gathered by the Ben Taub surgical staff and then secondarily analyzed for the purpose of this thesis.^ Subjects in the LMAP group had significantly lower early post-operative mortality compared to those in the HMAP group. 30-day mortality was also lower in the LMAP group, although this did not reach statistical significance. There were no statistically significant differences between the two groups with regards to development of ischemic, hematologic or infectious complications, length of hospitalization, length of ICU stay or duration of mechanical ventilation. ^ Based upon the data presented in this thesis, it appears that hypotensive resuscitation is a safe strategy for use in the trauma population. Specifically, hypotensive resuscitation reduced the risk of early post-operative death from coagulopathic bleeding and did not result in an increased risk of ischemic or other post-operative complications. The preliminary results described in this thesis provide convincing evidence support the continued investigation and use of hypotensive resuscitation in a trauma setting.^

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Purpose. To evaluate trends in the utilization of head, abdominal, thoracic and other body regions CTs in the management of victims of MVC at a level I trauma center from 1996 to 2006.^ Method. From the trauma registry, I identified patients involved in MVC's in a level I trauma center and categorized them into three age groups of 13-18, 19-55 and ≥56. I used International Classification of Disease (ICD-9-CM) codes to find the type and number of CTs examinations performed for each patient. I plotted the mean number of CTs per patient against year of admission to find the crude estimate of change in utilization pattern for each type of CT. I used logistic regression to assess whether repetitive CTs (≥ 2) for head, abdomen, thorax and other body regions were associated with age group and year of admission for MVC patients. I adjusted the estimates for gender, ethnicity, insurance status, mechanism and severity of injury, intensive care unit admission status, patient disposition (dead or alive) and year of admission.^ Results. Utilization of head, abdominal, thoracic and other body regions CTs significantly increased over 11-year period. Utilization of head CT was greatest in the 13-18 age group, and increased from 0.58 CT/patient in 1996 to 1.37 CT/patient in 2006. Abdominal CTs were more common in the ≥56+ age group, and increased from 0.33 CT/patient in 1996 to 0.72 CT/patient in 2006. Utilization of thoracic CTs was higher in the 56+ age group, and increased from 0.01 CT/patient in 1996 to 0.42 CT/patient in 2006. Utilization of other CTs did not change materially during the study period for adolescents, adults or older adults. In the multivariable analysis, after adjustment for potential confounders, repetitive head CTs significantly increased in the 13-18 age group (95% CI: 1.29-1.87, p=<0.001) relative to the 19-55 age group. Repetitive thoracic CT use was lower in adolescents (95% CI: 0.22-0.70, p=<0.001) relative to the 19-55 age group.^ Conclusion. There has been a substantial increase in the utilization of head, abdominal, thoracic and other CTs in the management of MVC patients. Future studies need to identify if increased utilization of CTs have resulted in better health outcome for these patients. ^

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Trauma and severe head injuries are important issues because they are prevalent, because they occur predominantly in the young, and because variations in clinical management may matter. Trauma is the leading cause of death for those under age 40. The focus of this head injury study is to determine if variations in time from the scene of accident to a trauma center hospital makes a difference in patient outcomes.^ A trauma registry is maintained in the Houston-Galveston area and includes all patients admitted to any one of three trauma center hospitals with mild or severe head injuries. A study cohort, derived from the Registry, includes 254 severe head injury cases, for 1980, with a Glasgow Coma Score of 8 or less.^ Multiple influences relate to patient outcomes from severe head injury. Two primary variables and four confounding variables are identified, including time to emergency room, time to intubation, patient age, severity of injury, type of injury and mode of transport to the emergency room. Regression analysis, analysis of variance, and chi-square analysis were the principal statistical methods utilized.^ Analysis indicates that within an urban setting, with a four-hour time span, variations in time to emergency room do not provide any strong influence or predictive value to patient outcome. However, data are suggestive that at longer time periods there is a negative influence on outcomes. Age is influential only when the older group (55-64) is included. Mode of transport (helicopter or ambulance) did not indicate any significant difference in outcome.^ In a multivariate regression model, outcomes are influenced primarily by severity of injury and age which explain 36% (R('2)) of variance. Inclusion of time to emergency room, time to intubation, transport mode and type injury add only 4% (R('2)) additional contribution to explaining variation in patient outcome.^ The research concludes that since the group most at risk to head trauma is the young adult male involved in automobile/motorcycle accidents, more may be gained by modifying driving habits and other preventive measures. Continuous clinical and evaluative research are required to provide updated clinical wisdom in patient management and trauma treatment protocols. A National Institute of Trauma may be required to develop a national public policy and evaluate the many medical, behavioral and social changes required to cope with the country's number 3 killer and the primary killer of young adults.^

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Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^