Motor vehicle crashes are the leading cause of death for all teenagers, and each year a far greater number of teens are hospitalized with non-fatal injuries. This retrospective cohort study used the National Inpatient Sample data to examine hospitalizations from the years 2002 to 2007 for 15-18-year-old teenagers who had been admitted due to a motor vehicle crash. More than 23,000 teens were hospitalized for motor vehicle-related crash injuries each year, for a total of 139,880 over the 6-year period. Total hospital charges exceeded $1 billion almost every year, with a median hospital charge of more than $25,000. Older teens, boys, those with fractures, internal injuries or intracranial injuries, and Medicaid/Medicare as a payer were associated with higher hospital charges and longer lengths of stay. These high charges and hospitalization periods pose a significant burden on teens, their families, and the health care system.
[Show abstract][Hide abstract] ABSTRACT: The adolescent Latino male mortality profile is an anomaly when compared to an otherwise more favorable overall U.S. Latino population mortality profile. Motor vehicle crash fatalities bear a considerable proportion of mortality burden in this vulnerable population. Friend influence and relational connection are two contextual domains that may mediate crash injury risk behavior in these adolescents. Our study goal was to assess the role of friend influence over time and relational connections associated with crash injury risk behavior (CIRB) in adolescent Latino males. Waves I and II data from the National Longitudinal Study of Adolescent Health were used. Scale of CIRB, and three relational connections; school connectedness, parent connectedness, and expectation of academic success were developed and tested. Friend nomination data were available and the index student responses were linked to friend responses. Linear regression was used to assess the relationship of relational connections and friend CIRB on index student CIRB at wave I and II. Longitudinal analysis did not show significant evidence for friend influence among adolescent Latino males on CIRB. The best predictor of CIRB at wave II for adolescent Latino males was their CIRB at wave I. Relational connections were important yet exaggerated cross-sectionally but their effect was substantially attenuated longitudinally. The lack of friend influence on CIRB for adolescent Latino males may be specific to this demographic group or characteristic of the sample studied. Prevention strategies that focus on modulating friend influence in adolescent Latino males may not yield the desired prevention effects on CIRB.
Annals of advances in automotive medicine 01/2011; 55:41-50.
[Show abstract][Hide abstract] ABSTRACT: In this paper, the authors' goal was to report the outcome of patients with unruptured intracranial aneurysms undergoing endovascular treatment under conscious sedation (local anesthesia).
Between November 5, 2001, and February 5, 2009, the authors treated 340 patients with 358 unruptured aneurysms by using neurointerventional procedures at Millard Fillmore Gates Hospital (Buffalo, New York). The data were retrospectively reviewed for periprocedural safety and long-term follow-up.
A total of 496 procedures were performed under local anesthesia. Of those, 370 procedures (74.6%) were completed successfully. In 82 procedures (16.5%), an associated medical or technical event occurred. Forty-four procedures (8.9%) were aborted. Rates of overall procedure-related morbidity and mortality were 1.2% (6 of 496) and 0.6% (3 of 496), respectively. The average hospital stay was 1.5 ± 2.5 days. Long-term follow-up was available in 261 (82.1%) of 318 patients whose procedures were performed with local anesthesia. Of those, 246 patients (94.3%) had a good outcome (modified Rankin Scale score ≤ 2), 6 patients (2.3%) had an unfavorable outcome, not related to the procedure, and 9 patients (3.4%) had a poor outcome (modified Rankin Scale score > 2) as a result of the intervention.
Interventional treatment under conscious sedation (local anesthesia) can be effectively performed in most patients with unruptured intracranial aneurysms and is associated with a short hospital stay and low morbidity and mortality.
Journal of Neurosurgery 01/2011; 114(1):120-8. DOI:10.3171/2010.3.JNS091384 · 3.74 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Emergency department (ED) and hospital charges obtained from administrative data sets are useful descriptors of injury severity and the burden to EDs and the health care system. However, charges are typically positively skewed due to costly procedures, long hospital stays, and complicated or prolonged treatment for few patients. The median is not affected by extreme observations and is useful in describing and comparing distributions of hospital charges. A least-squares analysis employing a log transformation is one approach for estimating median hospital charges, corresponding confidence intervals (CIs), and differences between groups; however, this method requires certain distributional properties. An alternate method is quantile regression, which allows estimation and inference related to the median without making distributional assumptions.
The objective was to compare the log-transformation least-squares method to the quantile regression approach for estimating median hospital charges, differences in median charges between groups, and associated CIs.
The authors performed simulations using repeated sampling of observed statewide ED and hospital charges and charges randomly generated from a hypothetical lognormal distribution. The median and 95% CI and the multiplicative difference between the median charges of two groups were estimated using both least-squares and quantile regression methods. Performance of the two methods was evaluated.
In contrast to least squares, quantile regression produced estimates that were unbiased and had smaller mean square errors in simulations of observed ED and hospital charges. Both methods performed well in simulations of hypothetical charges that met least-squares method assumptions. When the data did not follow the assumed distribution, least-squares estimates were often biased, and the associated CIs had lower than expected coverage as sample size increased.
Quantile regression analyses of hospital charges provide unbiased estimates even when lognormal and equal variance assumptions are violated. These methods may be particularly useful in describing and analyzing hospital charges from administrative data sets.
Academic Emergency Medicine 07/2012; 19(7):866-75. DOI:10.1111/j.1553-2712.2012.01388.x · 2.01 Impact Factor
Sohail Zangenehpour, Jillian Strauss, Luis F Miranda-Moreno, Nicolas Saunier,
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