8 resultados para Statistical performance indexes
em DigitalCommons@The Texas Medical Center
Resumo:
Background. Research into methods for recovery from fatigue due to exercise is a popular topic among sport medicine, kinesiology and physical therapy. However, both the quantity and quality of studies and a clear solution of recovery are lacking. An analysis of the statistical methods in the existing literature of performance recovery can enhance the quality of research and provide some guidance for future studies. Methods: A literature review was performed using SCOPUS, SPORTDiscus, MEDLINE, CINAHL, Cochrane Library and Science Citation Index Expanded databases to extract the studies related to performance recovery from exercise of human beings. Original studies and their statistical analysis for recovery methods including Active Recovery, Cryotherapy/Contrast Therapy, Massage Therapy, Diet/Ergogenics, and Rehydration were examined. Results: The review produces a Research Design and Statistical Method Analysis Summary. Conclusion: Research design and statistical methods can be improved by using the guideline from the Research Design and Statistical Method Analysis Summary. This summary table lists the potential issues and suggested solutions, such as, sample size calculation, sports specific and research design issues consideration, population and measure markers selection, statistical methods for different analytical requirements, equality of variance and normality of data, post hoc analyses and effect size calculation.^
Resumo:
The main goal of this study was to relate physical changes in image quality measured by Modulation Transfer Function (MTF) to diagnostic accuracy.^ One Hundred and Fifty Kodak Min-R screen/film combination conventional craniocaudal mammograms obtained with the Pfizer Microfocus Mammographic system were selected from the files of the Department of Radiology, at M.D. Anderson Hospital and Tumor Institute.^ The mammograms included 88 cases with a variety of benign diagnosis and 62 cases with a variety of malignant biopsy diagnosis. The average age of the patient population was 55 years old. 70 cases presented calcifications with 30 cases having calcifications smaller than 0.5mm. 46 cases presented irregular bordered masses larger than 1 cm. 30 cases presented smooth bordered masses with 20 larger than 1 cm.^ Four separated copies of the original images were made each having a different change in the MTF using a defocusing technique whereby copies of the original were obtained by light exposure through different thicknesses (spacing) of transparent film base.^ The mammograms were randomized, and evaluated by three experienced mammographers for the degree of visibility of various anatomical breast structures and pathological lesions (masses and calicifications), subjective image quality, and mammographic interpretation.^ 3,000 separate evaluations were anayzed by several statistical techniques including Receiver Operating Characteristic curve analysis, McNemar test for differences between proportions and the Landis et al. method of agreement weighted kappa for ordinal categorical data.^ Results from the statistical analysis show: (1) There were no statistical significant differences in the diagnostic accuracy of the observers when diagnosing from mammograms with the same MTF. (2) There were no statistically significant differences in diagnostic accuracy for each observer when diagnosing from mammograms with the different MTF's used in the study. (3) There statistical significant differences in detail visibility between the copies and the originals. Detail visibility was better in the originals. (4) Feature interpretations were not significantly different between the originals and the copies. (5) Perception of image quality did not affect image interpretation.^ Continuation and improvement of this research ca be accomplished by: using a case population more sensitive to MTF changes, i.e., asymptomatic women with minimum breast cancer, more observers (including less experienced radiologists and experienced technologists) must collaborate in the study, and using a minimum of 200 benign and 200 malignant cases.^
Resumo:
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 ^
Resumo:
Bayesian adaptive randomization (BAR) is an attractive approach to allocate more patients to the putatively superior arm based on the interim data while maintains good statistical properties attributed to randomization. Under this approach, patients are adaptively assigned to a treatment group based on the probability that the treatment is better. The basic randomization scheme can be modified by introducing a tuning parameter, replacing the posterior estimated response probability, setting a boundary to randomization probabilities. Under randomization settings comprised of the above modifications, operating characteristics, including type I error, power, sample size, imbalance of sample size, interim success rate, and overall success rate, were evaluated through simulation. All randomization settings have low and comparable type I errors. Increasing tuning parameter decreases power, but increases imbalance of sample size and interim success rate. Compared with settings using the posterior probability, settings using the estimated response rates have higher power and overall success rate, but less imbalance of sample size and lower interim success rate. Bounded settings have higher power but less imbalance of sample size than unbounded settings. All settings have better performance in the Bayesian design than in the frequentist design. This simulation study provided practical guidance on the choice of how to implement the adaptive design. ^
Resumo:
Much of the current healthcare financial literature addresses the concern of government officials, the public, and healthcare providers regarding the need for control of health care costs. The literature suggests that attitudes of hospital department managers toward their role in financial management affects their ability to effect favorable financial results.^ There were several objectives of the dissertation: (1) To identify whether or not there exists a relationship between the attitude/role perception of hospital managers and the financial performance of their departments. (2) To compile a descriptive survey data base of key factors identified in the financial literature from individual hospitals. (3) To compile a brief descriptive survey of hospital managers' financial management background and training (both formal and informal). (4) To conduct an attitude assessment/role perception survey regarding the importance or relevance of a suggested financial management role set (i.e., issues discussed in the current literature) as viewed by the selected hospital managers and their matched administrators. (5) To propose plausible theoretical models and statistical tests of seven proposed hypotheses.^ The statistical results of a variety of methods generally suggested, for the sample population, that the null hypothesis should not be rejected concerning the relationships between a department manager's financial attitudes and role perceptions and the resultant financial performance.^ The fact that the results of this study did not suggest that there was a significant relationship which existed between role perception and financial performance does not necessarily indicate that the theories supporting such a relationship in literature are false, not that such a relationship does not exist. Several alternative theories were postulated to explain the apparent lack of statistical relationship, and suggestions for refinement and/or improvement of further research were discussed. ^
Resumo:
Mixed longitudinal designs are important study designs for many areas of medical research. Mixed longitudinal studies have several advantages over cross-sectional or pure longitudinal studies, including shorter study completion time and ability to separate time and age effects, thus are an attractive choice. Statistical methodology used in general longitudinal studies has been rapidly developing within the last few decades. Common approaches for statistical modeling in studies with mixed longitudinal designs have been the linear mixed-effects model incorporating an age or time effect. The general linear mixed-effects model is considered an appropriate choice to analyze repeated measurements data in longitudinal studies. However, common use of linear mixed-effects model on mixed longitudinal studies often incorporates age as the only random-effect but fails to take into consideration the cohort effect in conducting statistical inferences on age-related trajectories of outcome measurements. We believe special attention should be paid to cohort effects when analyzing data in mixed longitudinal designs with multiple overlapping cohorts. Thus, this has become an important statistical issue to address. ^ This research aims to address statistical issues related to mixed longitudinal studies. The proposed study examined the existing statistical analysis methods for the mixed longitudinal designs and developed an alternative analytic method to incorporate effects from multiple overlapping cohorts as well as from different aged subjects. The proposed study used simulation to evaluate the performance of the proposed analytic method by comparing it with the commonly-used model. Finally, the study applied the proposed analytic method to the data collected by an existing study Project HeartBeat!, which had been evaluated using traditional analytic techniques. Project HeartBeat! is a longitudinal study of cardiovascular disease (CVD) risk factors in childhood and adolescence using a mixed longitudinal design. The proposed model was used to evaluate four blood lipids adjusting for age, gender, race/ethnicity, and endocrine hormones. The result of this dissertation suggest the proposed analytic model could be a more flexible and reliable choice than the traditional model in terms of fitting data to provide more accurate estimates in mixed longitudinal studies. Conceptually, the proposed model described in this study has useful features, including consideration of effects from multiple overlapping cohorts, and is an attractive approach for analyzing data in mixed longitudinal design studies.^
Resumo:
In light of the new healthcare regulations, hospitals are increasingly reevaluating their IT integration strategies to meet expanded healthcare information exchange requirements. Nevertheless, hospital executives do not have all the information they need to differentiate between the available strategies and recognize what may better fit their organizational needs. ^ In the interest of providing the desired information, this study explored the relationships between hospital financial performance, integration strategy selection, and strategy change. The integration strategies examined – applied as binary logistic regression dependent variables and in the order from most to least integrated – were Single-Vendor (SV), Best-of-Suite (BoS), and Best-of-Breed (BoB). In addition, the financial measurements adopted as independent variables for the models were two administrative labor efficiency and six industry standard financial ratios designed to provide a broad proxy of hospital financial performance. Furthermore, descriptive statistical analyses were carried out to evaluate recent trends in hospital integration strategy change. Overall six research questions were proposed for this study. ^ The first research question sought to answer if financial performance was related to the selection of integration strategies. The next questions, however, explored whether hospitals were more likely to change strategies or remain the same when there was no external stimulus to change, and if they did change, they would prefer strategies closer to the existing ones. These were followed by a question that inquired if financial performance was also related to strategy change. Nevertheless, rounding up the questions, the last two probed if the new Health Information Technology for Economic and Clinical Health (HITECH) Act had any impact on the frequency and direction of strategy change. ^ The results confirmed that financial performance is related to both IT integration strategy selection and strategy change, while concurred with prior studies that suggested hospital and environmental characteristics are associated factors as well. Specifically this study noted that the most integrated SV strategy is related to increased administrative labor efficiency and the hybrid BoS strategy is associated with improved financial health (based on operating margin and equity financing ratios). On the other hand, no financial indicators were found to be related to the least integrated BoB strategy, except for short-term liquidity (current ratio) when involving strategy change. ^ Ultimately, this study concluded that when making IT integration strategy decisions hospitals closely follow the resource dependence view of minimizing uncertainty. As each integration strategy may favor certain organizational characteristics, hospitals traditionally preferred not to make strategy changes and when they did, they selected strategies that were more closely related to the existing ones. However, as new regulations further heighten revenue uncertainty while require increased information integration, moving forward, as evidence already suggests a growing trend of organizations shifting towards more integrated strategies, hospitals may be more limited in their strategy selection choices.^
Resumo:
Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^