998 resultados para CEO selection


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© 2014, The International Biometric Society.A potential venue to improve healthcare efficiency is to effectively tailor individualized treatment strategies by incorporating patient level predictor information such as environmental exposure, biological, and genetic marker measurements. Many useful statistical methods for deriving individualized treatment rules (ITR) have become available in recent years. Prior to adopting any ITR in clinical practice, it is crucial to evaluate its value in improving patient outcomes. Existing methods for quantifying such values mainly consider either a single marker or semi-parametric methods that are subject to bias under model misspecification. In this article, we consider a general setting with multiple markers and propose a two-step robust method to derive ITRs and evaluate their values. We also propose procedures for comparing different ITRs, which can be used to quantify the incremental value of new markers in improving treatment selection. While working models are used in step I to approximate optimal ITRs, we add a layer of calibration to guard against model misspecification and further assess the value of the ITR non-parametrically, which ensures the validity of the inference. To account for the sampling variability of the estimated rules and their corresponding values, we propose a resampling procedure to provide valid confidence intervals for the value functions as well as for the incremental value of new markers for treatment selection. Our proposals are examined through extensive simulation studies and illustrated with the data from a clinical trial that studies the effects of two drug combinations on HIV-1 infected patients.

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The process of determining the level of care and specific postacute care facility for stroke patients has not been adequately studied. The objective of this study was to better understand the factors that influence postacute care decisions by surveying stroke discharge planners. Requests were sent to discharge planners at 471 hospitals in the Northeast United States to complete an online survey regarding the factors impacting the selection of postacute care. Seventy-seven (16%) discharge planners completed the online survey. Respondents were mainly nurses and social workers and 73% reported ≥20 years healthcare experience. Patients and families were found to be significantly more influential than physicians (P < 0.001) and other clinicians (P = 0.04) in influencing postdischarge care. Other clinicians were significantly more influential than physicians (P < 0.001). Insurance and quality of postacute care were the factors likely to most affect the selection of postacute care facility. Insurance was also identified as the greatest barrier in the selection of level of postacute care (70%; P < 0.001) and specific postacute care facility (46%; P = 0.02). More than half reported that pressure to discharge patients quickly impacts a patients' final destination. Nonclinical factors are perceived by discharge planners to have a major influence on postacute stroke care decision making.

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Objective Describe the methodology and selection of quality indicators (QI) to be implemented in the EFFECT (EFFectiveness of Endometrial Cancer Treatment) project. EFFECT aims to monitor the variability in Quality of Care (QoC) of uterine cancer in Belgium, to compare the effectiveness of different treatment strategies to improve the QoC and to check the internal validity of the QI to validate the impact of process indicators on outcome. Methods A QI list was retrieved from literature, recent guidelines and QI databases. The Belgian Healthcare Knowledge Center methodology was used for the selection process and involved an expert's panel rating the QI on 4 criteria. The resulting scores and further discussion resulted in a final QI list. An online EFFECT module was developed by the Belgian Cancer Registry including the list of variables required for measuring the QI. Three test phases were performed to evaluate the relevance, feasibility and understanding of the variables and to test the compatibility of the dataset. Results 138 QI were considered for further discussion and 82 QI were eligible for rating. Based on the rating scores and consensus among the expert's panel, 41 QI were considered measurable and relevant. Testing of the data collection enabled optimization of the content and the user-friendliness of the dataset and online module. Conclusions This first Belgian initiative for monitoring the QoC of uterine cancer indicates that the previously used QI selection methodology is reproducible for uterine cancer. The QI list could be applied by other research groups for comparison. © 2013 Elsevier Inc.

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Journal Article

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This paper presents results from a questionnaire study of participant exit awareness and suggested exit selection in the event of emergency evacuations involving narrow body aircraft. The study involved 459 participants with varying flight experience. The results of this study supports the hypothesis that poor understanding by passengers of aircraft exit location and configuration may be a contributory factor in the resulting poor exit selection decisions made by passengers in emergency situations. These results have important safety implications for airlines and also provide important insight to evacuation model developers regarding the decision making process in agent exit selection.

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Counter-current chromatography (CCC) is a technique that shows a lot of potential for large scale purification. Its usefulness in a "research and development" pharmaceutical environment has been investigated, and the conclusions are shown in this article. The use of CCC requires the development of an appropriate solvent system (a parameter of critical importance), a process which can be tedious. This article presents a novel strategy, combining a statistical approach and fast HPLC to generate a three-dimensional partition coefficient map and rapidly predict an optimal solvent system. This screen is performed in half a day and involves 9 experiments per solvent mixture. Test separations were performed using that screen to ensure the validity of the method.

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Here we describe a new trait-based model for cellular resource allocation that we use to investigate the relative importance of different drivers for small cell size in phytoplankton. Using the model, we show that increased investment in nonscalable structural components with decreasing cell size leads to a trade-off between cell size, nutrient and light affinity, and growth rate. Within the most extreme nutrient-limited, stratified environments, resource competition theory then predicts a trend toward larger minimum cell size with increasing depth. We demonstrate that this explains observed trends using a marine ecosystem model that represents selection and adaptation of a diverse community defined by traits for cell size and subcellular resource allocation. This framework for linking cellular physiology to environmental selection can be used to investigate the adaptive response of the marine microbial community to environmental conditions and the adaptive value of variations in cellular physiology.