886 resultados para Earned Value Management
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OBJECTIVE: Antitumor necrosis factor a agents have significantly improved the management of Crohn's disease (CD), but not all patients benefit from this therapy. We used data from the Swiss Inflammatory Bowel Disease Cohort Study and predefined appropriateness criteria to examine the appropriateness of use of infliximab (IFX) in CD patients. METHODS: EPACT II (European Panel on the Appropriateness of CD Therapy, 2007; www.epact.ch) appropriateness criteria have been developed using a formal explicit panel process combining evidence from the published literature and expert opinion. Questionnaires relating to EPACT II criteria were used at enrollment and follow-up of all Swiss Inflammatory Bowel Disease Cohort Study patients. A step-by-step analysis of all possible indications for IFX therapy in a given patient allowed identification of the most appropriate indication and final classification in a single appropriateness category (appropriate, uncertain, inappropriate). RESULTS: Eight hundred and twenty-one CD patients were prospectively enrolled between November 2006 and March 2009. IFX was administered to 146 patients (18%) at enrollment and was most frequently used for complex fistulizing disease and for the maintenance of remission induced by biological therapy. IFX therapy was considered appropriate in 44%, uncertain in 44%, and inappropriate in 10% of patients. CONCLUSION: In this cohort, 9 out of 10 indications for IFX therapy were clinically generally acceptable (appropriate or uncertain) according to EPACT II criteria. Uncertain indications resulted mainly from the current more liberal use of IFX in clinical practice as compared with the EPACT II criteria.
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ABSTRACT: INTRODUCTION: Biomarkers, such as C-reactive protein [CRP] and procalcitonin [PCT], are insufficiently sensitive or specific to stratify patients with sepsis. We investigate the prognostic value of pancreatic stone protein/regenerating protein (PSP/reg) concentration in patients with severe infections. METHODS: PSP/reg, CRP, PCT, tumor necrosis factor-alpha (TNF-α), interleukin 1 beta (IL1-β), IL-6 and IL-8 were prospectively measured in cohort of patients ≥ 18 years of age with severe sepsis or septic shock within 24 hours of admission in a medico-surgical intensive care unit (ICU) of a community and referral university hospital, and the ability to predict in-hospital mortality was determined. RESULTS: We evaluated 107 patients, 33 with severe sepsis and 74 with septic shock, with in-hospital mortality rates of 6% (2/33) and 25% (17/74), respectively. Plasma concentrations of PSP/reg (343.5 vs. 73.5 ng/ml, P < 0.001), PCT (39.3 vs. 12.0 ng/ml, P < 0.001), IL-8 (682 vs. 184 ng/ml, P < 0.001) and IL-6 (1955 vs. 544 pg/ml, P < 0.01) were significantly higher in patients with septic shock than with severe sepsis. Of note, median PSP/reg was 13.0 ng/ml (IQR: 4.8) in 20 severely burned patients without infection. The area under the ROC curve for PSP/reg (0.65 [95% CI: 0.51 to 0.80]) was higher than for CRP (0.44 [0.29 to 0.60]), PCT 0.46 [0.29 to 0.61]), IL-8 (0.61 [0.43 to 0.77]) or IL-6 (0.59 [0.44 to 0.75]) in predicting in-hospital mortality. In patients with septic shock, PSP/reg was the only biomarker associated with in-hospital mortality (P = 0.049). Risk of mortality increased continuously for each ascending quartile of PSP/reg. CONCLUSIONS: Measurement of PSP/reg concentration within 24 hours of ICU admission may predict in-hospital mortality in patients with septic shock, identifying patients who may benefit most from tailored ICU management.
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Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). While a number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently is fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behaviour, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause FIE, with effects accumulating over time. Consequently, FIE may alter the utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons. An important reason this is not happening is the lack of an appropriate assessment framework. We therefore describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary consequences of fishing and evaluating the predicted evolutionary outcomes of alternative management options. EvoIA can contribute to EAF by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries.
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Biological reference points are important tools for fisheries management. Reference points are not static, but may change when a population's environment or the population itself changes. Fisheries-induced evolution is one mechanism that can alter population characteristics, leading to "shifting" reference points by modifying the underlying biological processes or by changing the perception of a fishery system. The former causes changes in "true" reference points, whereas the latter is caused by changes in the yardsticks used to quantify a system's status. Unaccounted shifts of either kind imply that reference points gradually lose their intended meaning. This can lead to increased precaution, which is safe, but potentially costly. Shifts can also occur in more perilous directions, such that actual risks are greater than anticipated. Our qualitative analysis suggests that all commonly used reference points are susceptible to shifting through fisheries-induced evolution, including the limit and "precautionary" reference points for spawning-stock biomass, Blim and Bpa, and the target reference point for fishing mortality, F0.1. Our findings call for increased awareness of fisheries-induced changes and highlight the value of always basing reference points on adequately updated information, to capture all changes in the biological processes that drive fish population dynamics.
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By the end of the 1970s, contaminated sites had emerged as one of the most complex and urgent environmental issues affecting industrialized countries. The authors show that small and prosperous Switzerland is no exception to the pervasive problem of sites contamination, the legacy of past practices in waste management having left some 38,000 contaminated sites throughout the country. This book outlines the problem, offering evidence that open and polycentric environmental decision-making that includes civil society actors is valuable. They propose an understanding of environmental management of contaminated sites as a political process in which institutions frame interactions between strategic actors pursuing sometimes conflicting interests. In the opening chapter, the authors describe the influences of politics and the power relationships between actors involved in decision-making in contaminated sites management, which they term a "wicked problem." Chapter Two offers a theoretical framework for understanding institutions and the environmental management of contaminated sites. The next five chapters present a detailed case study on environmental management and contaminated sites in Switzerland, focused on the Bonfol Chemical Landfill. The study and analysis covers the establishment of the landfill under the first generation of environmental regulations, its closure and early remediation efforts, and the gambling on the remediation objectives, methods and funding in the first decade of the 21st Century. The concluding chapter discusses the question of whether the strength of environmental regulations, and the type of interactions between public, private, and civil society actors can explain the environmental choices in contaminated sites management. Drawing lessons from research, the authors debate the value of institutional flexibility for dealing with environmental issues such as contaminated sites.
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Abstract OBJECTIVE To identify informatics abilities essential to decision making in nursing management. METHOD Survey study with specialist nurses in health informatics and management. An electronic questionnaire was built based on the competencies Information Literacy (five categories; 40 abilities) and Information Management (nine categories; 69 abilities) of the TIGER - Technology Informatics Guiding Education Reform - initiative, with the guiding question: Which informatics abilities are essential to decision making in management? Answers were sorted in a Likert scale, ranging from 1 to 5. Rasch analysis was conducted with the software WINSTEPS ®. Results were presented in logits, with cutoff value zero. RESULTS Thirty-two specialists participated, coming from all regions of Brazil. In the information literacy competency, 18 abilities were considered essential and in Information Management, 38; these were sorted according to their degree of essentiality. CONCLUSION It is believed that the incorporation of these abilities in teaching can support the education of nurse managers and contribute to evidence-based practice, incorporation of information and communication technologies in health and information management.
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Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.
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Models incorporating more realistic models of customer behavior, as customers choosing from an offerset, have recently become popular in assortment optimization and revenue management. The dynamicprogram for these models is intractable and approximated by a deterministic linear program called theCDLP which has an exponential number of columns. When there are products that are being consideredfor purchase by more than one customer segment, CDLP is difficult to solve since column generationis known to be NP-hard. However, recent research indicates that a formulation based on segments withcuts imposing consistency (SDCP+) is tractable and approximates the CDLP value very closely. In thispaper we investigate the structure of the consideration sets that make the two formulations exactly equal.We show that if the segment consideration sets follow a tree structure, CDLP = SDCP+. We give acounterexample to show that cycles can induce a gap between the CDLP and the SDCP+ relaxation.We derive two classes of valid inequalities called flow and synchronization inequalities to further improve(SDCP+), based on cycles in the consideration set structure. We give a numeric study showing theperformance of these cycle-based cuts.
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The network revenue management (RM) problem arises in airline, hotel, media,and other industries where the sale products use multiple resources. It can be formulatedas a stochastic dynamic program but the dynamic program is computationallyintractable because of an exponentially large state space, and a number of heuristicshave been proposed to approximate it. Notable amongst these -both for their revenueperformance, as well as their theoretically sound basis- are approximate dynamic programmingmethods that approximate the value function by basis functions (both affinefunctions as well as piecewise-linear functions have been proposed for network RM)and decomposition methods that relax the constraints of the dynamic program to solvesimpler dynamic programs (such as the Lagrangian relaxation methods). In this paperwe show that these two seemingly distinct approaches coincide for the network RMdynamic program, i.e., the piecewise-linear approximation method and the Lagrangianrelaxation method are one and the same.
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The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.
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In today s highly competitive and global marketplace the pressure onorganizations to find new ways to create and deliver value to customersgrows ever stronger. In the last two decades, logistics and supply chainhas moved to the center stage. There has been a growing recognition thatit is through an effective management of the logistics function and thesupply chain that the goal of cost reduction and service enhancement canbe achieved. The key to success in Supply Chain Management (SCM) requireheavy emphasis on integration of activities, cooperation, coordination andinformation sharing throughout the entire supply chain, from suppliers tocustomers. To be able to respond to the challenge of integration there isthe need of sophisticated decision support systems based on powerfulmathematical models and solution techniques, together with the advancesin information and communication technologies. The industry and the academiahave become increasingly interested in SCM to be able to respond to theproblems and issues posed by the changes in the logistics and supply chain.We present a brief discussion on the important issues in SCM. We then arguethat metaheuristics can play an important role in solving complex supplychain related problems derived by the importance of designing and managingthe entire supply chain as a single entity. We will focus specially on theIterated Local Search, Tabu Search and Scatter Search as the ones, but notlimited to, with great potential to be used on solving the SCM relatedproblems. We will present briefly some successful applications.
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This paper examines the value of connections between German industry andthe Nazi movement in early 1933. Drawing on previously unused contemporarysources about management and supervisory board composition and stock returns,we find that one out of seven firms, and a large proportion of the biggest companies,had substantive links with the National Socialist German Workers Party. Firmssupporting the Nazi movement experienced unusually high returns, outperformingunconnected ones by 5% to 8% between January and March 1933. These resultsare not driven by sectoral composition and are robust to alternative estimatorsand definitions of affiliation.
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The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.
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The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.
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BackgroundDespite the intrinsic value of scientific disciplines, such as Economics, it is appropriate to gauge the impact of its applications on social welfare, or at least Health Economics (HE) case- its influence on health policy and management.MethodsThe three relevant features of knowledge (production, diffusion and application) are analyzed, more from an emic perspective the one used in Anthropology relying on the experience of the members of a culture- than from an etic approach seated on material descriptions and dubious statistics.ResultsThe soundness of the principles and results of HE depends on its disciplinary foundations,whereas its relevance than does not imply translation into practice- is more linked with the problems studied. Important contributions from Economics to the health sphere are recorded.HE in Spain ranks seventh in the world despite the relatively minor HE contents of its clinical and health services research journals.HE has in Spain more presence than influence, having failed to impregnate sufficiently thedaily events.ConclusionsHE knowledge required by a politician, a health manager or a clinician is rather limited; the main impact of HE could be to develop their intuition and awareness.