搜索结果：avoid

BACKGROUND: Readmissions to hospital are increasingly being used as an indicator of quality of care. However, this approach is valid only when we know what proportion of readmissions are avoidable. We conducted a systematic review of studies that measured the proportion of readmissions deemed avoidable. We examined how such readmissions were measured and estimated their prevalence. METHODS: We searched the MEDLINE and EMBASE databases to identify all studies published from 1966 to July 2010 that reviewed hospital readmissions and that specified how many were classified as avoidable. RESULTS: Our search strategy identified 34 studies. Three of the studies used combinations of administrative diagnostic codes to determine whether readmissions were avoidable. Criteria used in the remaining studies were subjective. Most of the studies were conducted at single teaching hospitals, did not consider information from the community or treating physicians, and used only one reviewer to decide whether readmissions were avoidable. The median proportion of readmissions deemed avoidable was 27.1% but varied from 5% to 79%. Three study-level factors (teaching status of hospital, whether all diagnoses or only some were considered, and length of follow-up) were significantly associated with the proportion of admissions deemed to be avoidable and explained some, but not all, of the heterogeneity between the studies. INTERPRETATION: All but three of the studies used subjective criteria to determine whether readmissions were avoidable. Study methods had notable deficits and varied extensively, as did the proportion of readmissions deemed avoidable. The true proportion of hospital readmissions that are potentially avoidable remains unclear.

BACKGROUND: Many causes of vision impairment can be prevented or treated. With an ageing global population, the demands for eye health services are increasing. We estimated the prevalence and relative contribution of avoidable causes of blindness and vision impairment globally from 1990 to 2020. We aimed to compare the results with the World Health Assembly Global Action Plan (WHA GAP) target of a 25% global reduction from 2010 to 2019 in avoidable vision impairment, defined as cataract and undercorrected refractive error. METHODS: We did a systematic review and meta-analysis of population-based surveys of eye disease from January, 1980, to October, 2018. We fitted hierarchical models to estimate prevalence (with 95% uncertainty intervals [UIs]) of moderate and severe vision impairment (MSVI; presenting visual acuity from <6/18 to 3/60) and blindness (<3/60 or less than 10° visual field around central fixation) by cause, age, region, and year. Because of data sparsity at younger ages, our analysis focused on adults aged 50 years and older. FINDINGS: Global crude prevalence of avoidable vision impairment and blindness in adults aged 50 years and older did not change between 2010 and 2019 (percentage change -0·2% [95% UI -1·5 to 1·0]; 2019 prevalence 9·58 cases per 1000 people [95% IU 8·51 to 10·8], 2010 prevalence 96·0 cases per 1000 people [86·0 to 107·0]). Age-standardised prevalence of avoidable blindness decreased by -15·4% [-16·8 to -14·3], while avoidable MSVI showed no change (0·5% [-0·8 to 1·6]). However, the number of cases increased for both avoidable blindness (10·8% [8·9 to 12·4]) and MSVI (31·5% [30·0 to 33·1]). The leading global causes of blindness in those aged 50 years and older in 2020 were cataract (15·2 million cases [9% IU 12·7-18·0]), followed by glaucoma (3·6 million cases [2·8-4·4]), undercorrected refractive error (2·3 million cases [1·8-2·8]), age-related macular degeneration (1·8 million cases [1·3-2·4]), and diabetic retinopathy (0·86 million cases [0·59-1·23]). Leading causes of MSVI were undercorrected refractive error (86·1 million cases [74·2-101·0]) and cataract (78·8 million cases [67·2-91·4]). INTERPRETATION: Results suggest eye care services contributed to the observed reduction of age-standardised rates of avoidable blindness but not of MSVI, and that the target in an ageing global population was not reached. FUNDING: Brien Holden Vision Institute, Fondation Théa, The Fred Hollows Foundation, Bill & Melinda Gates Foundation, Lions Clubs International Foundation, Sightsavers International, and University of Heidelberg.

Traditionally, theorists have described motivation in terms of approach and avoidance tendencies. In contrast, goal orientation research has focused primarily on 2 approach goals: demonstrating ability (performance-approach) and developing ability (task). A scale to assess the goal of avoiding the demonstration of lack of ability (performance-avoid) was included with scales assessing approach goals in a survey given to 703 6th graders. Factor analysis supported the differentiation among the 3 scales. The performance scales were moderately positively correlated and exhibited low correlations with the task scale. With all 3 goals in regression equations, task goals predicted academic efficacy, self-regulated learning, and lower levels of avoiding seeking academic help in the classroom. Performance-avoid goals negatively predicted academic efficacy and positively predicted avoiding seeking help and test anxiety. Performance-approach goals did not emerge as the most significant predictor of any of these educationally relevant outcomes.

This study was designed to provide insights into why people avoid advertising on the Internet. Recent negative trends in Internet advertising, such as "banner blindness" and extremely low click-through rates, make it imperative to study various factors affecting Internet ad avoidance. Accordingly, this study builds a comprehensive theoretical model explaining advertising avoidance on the Internet. We examined three latent variables of Internet ad avoidance: perceived goal impediment, perceived ad clutter, and prior negative experience. We found that these constructs successfully explain why people cognitively, affectively, and behaviorally avoid advertising messages on the Internet. Perceived goal impediment is found to be the most significant antecedent explaining advertising avoidance on the Internet.

&lt;p&gt;The self-avoiding walk is a mathematical model that has important applications in statistical mechanics and polymer science. In spite of its simple definition—a path on a lattice that does not visit the same site more than once—it is difficult to analyze mathematically. &lt;i&gt;The Self-Avoiding Walk&lt;/i&gt; provides the first unified account of the known rigorous results for the self-avoiding walk, with particular emphasis on its critical behavior. Its goals are to give an account of the current mathematical understanding of the model, to indicate some of the applications of the concept in physics and in chemistry, and to give an introduction to some of the nonrigorous methods used in those fields. &lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;Topics covered in the book include: the lace expansion and its application to the self-avoiding walk in more than four dimensions where most issues are now resolved; an introduction to the nonrigorous scaling theory; classical work of Hammersley and others; a new exposition of Kesten’s pattern theorem and its consequences; a discussion of the decay of the two-point function and its relation to probabilistic renewal theory; analysis of Monte Carlo methods that have been used to study the self-avoiding walk; the role of the self-avoiding walk in physical and chemical applications. Methods from combinatorics, probability theory, analysis, and mathematical physics play important roles. The book is highly accessible to both professionals and graduate students in mathematics, physics, and chemistry.​ &lt;/p&gt;

Abstract The book discusses the diversity of mechanisms by which prey can avoid or survive attacks by predators, both from ecological and evolutionary perspectives. There is a particular focus on sensory mechanisms by which prey can avoid being detected, avoid being identified, signal (perhaps sometimes dishonestly) to predators that they are defended or unpalatable. The book is divided into three sections. The first considers detection avoidance through, for example, background matching, disruptive patterning, countershading and counterillumination, or transparency and reflective silvering. The second section considers avoiding or surviving an attack if detection and identification by the predator has already taken place (i.e., secondary defences). The key mechanism of this section is aposematism: signals that warn the predator that a particular prey type is defended. One particularly interesting aspect of this is the sharing of the same signal by more than one defended species (the phenomenon of Mullerian mimicry). The final section considers deception of predators. This may involve an undefended prey mimicking a defended species (Batesian mimicry), or signals that deflect predator’s attention or signals that startle predators. The book provides the first comprehensive survey of adaptive coloration in a predator-prey context in thirty years.

Recent reports in the business press allege that managers take actions to avoid negative earnings surprises. I hypothesize that certain firm characteristics are associated with greater incentives to avoid negative surprises. I find that firms with higher transient institutional ownership, greater reliance on implicit claims with their stakeholders, and higher value-relevance of earnings are more likely to meet or exceed expectations at the earnings announcement. I also examine whether firms manage earnings upward or guide analysts' forecasts downward to avoid missing expectations at the earnings announcement. I examine the relation between firm characteristics and the probability (conditional on meeting analysts' expectations) of having (1) positive abnormal accruals, and (2) forecasts that are lower than expected (using a model of prior earnings changes). Overall, the results suggest that both mechanisms play a role in avoiding negative earnings surprises.

Nina Eliasoph's vivid portrait of American civic life reveals an intriguing culture of political avoidance. Despite the importance for democracy of open-ended political conversation among ordinary citizens, many Americans try hard to avoid appearing to care about politics. To discover how, where and why Americans create this culture of avoidance, the author accompanied suburban volunteers, activists, and recreation club members for over two years, listening to them talk - and avoid talking - about the wider world, together and in encounters with government, media, and corporate authorities. She shows how citizens create and express ideas in everyday life, contrasting their privately expressed convictions with their lack of public political engagement. Her book challenges received ideas about culture, power and democracy, while exposing the hard work of producing apathy.

1. While teaching statistics to ecologists, the lead authors of this paper have noticed common statistical problems. If a random sample of their work (including scientific papers) produced before doing these courses were selected, half would probably contain violations of the underlying assumptions of the statistical techniques employed. 2. Some violations have little impact on the results or ecological conclusions; yet others increase type I or type II errors, potentially resulting in wrong ecological conclusions. Most of these violations can be avoided by applying better data exploration. These problems are especially troublesome in applied ecology, where management and policy decisions are often at stake. 3. Here, we provide a protocol for data exploration; discuss current tools to detect outliers, heterogeneity of variance, collinearity, dependence of observations, problems with interactions, double zeros in multivariate analysis, zero inflation in generalized linear modelling, and the correct type of relationships between dependent and independent variables; and provide advice on how to address these problems when they arise. We also address misconceptions about normality, and provide advice on data transformations. 4. Data exploration avoids type I and type II errors, among other problems, thereby reducing the chance of making wrong ecological conclusions and poor recommendations. It is therefore essential for good quality management and policy based on statistical analyses.

Evidence that the various common types of cancer are largely avoidable diseases is reviewed. Life-style and other environmental factors are divided into a dozen categories, and for each category the evidence relating those particular factors to cancer onset rates is summarized. Where possible, an estimate is made of the percentage of current U.S. cancer mortality that might have been caused or avoided by that category of factors. These estimates are based chiefly on evidence from epidemiology, as the available evidence from animal and other laboratory studies cannot provide reliable human risk assessments. By far the largest reliably known percentage is the 30% of current U.S. cancer deaths that are due to tobacco, although it is possible that some nutritional factor(s) may eventually be found to be of comparable importance. The percentage of U.S. cancer deaths that are due to tobacco is still increasing, and must be expected to continue to increase for some years yet due to the delayed effects of the adoption of cigarettes in earlier decades. Trends in mortality and in onset rates for many separate types of cancer are studied in detail in appendixes to this paper. Biases in the available data on registration of new cases produce apparent trends in cancer incidence which are spurious. Biases also produce spurious trends in cancer death certification rates, especially among old people. In (and before) middle age, where the biases are smaller, there appear to be a few real increases and a few real decreases in mortality from some particular types of cancer, but there is no evidence of any generalized increase other than that due to tobacco. Moderate increases or decreases due to some new agent(s) or habit(s) might of course be overlooked in such large-scale analyses. But, such analyses do suggest that, apart from cancer of the respiratory tract, the types of cancer that are currently common are not peculiarly modern diseases and are likely to depend chiefly on some longestablished factor(s). (A prospective study utilizing both questionnaires and stored blood and other biological materials might help elucidate these factors.) The proportion of current U.S. cancer deaths attributed to occupational factors is provisionally estimated as 4% (lung cancer being the major contributor to this). This is far smaller than has recently been suggested by various U.S. Government agencies. The matter could be resolved directly by a “case-control” study of lung cancer two or three times larger than the recently completed U.S. National Bladder Cancer Study but similar to it in methodology and unit costs; there are also other reasons for such a study. A fuller summary of conclusions and recommendations comprises the final section of this report.

OBJECTIVE: To determine whether uninsured and Medicaid patients have higher rates of avoidable hospitalizations than do insured patients. DESIGN: We used 1987 computerized hospital discharge data to select a cross-sectional sample of hospitalized patients. Population estimates from the Current Population Survey were used to estimate rates of admission, standardized for age and sex. SETTING: Nonfederal acute care hospitals in Massachusetts and Maryland. PATIENTS: All patients under 65 years of age who were uninsured, privately insured, or insured by Medicaid. Hospitalizations for obstetric and psychiatric conditions were excluded. MAIN OUTCOME MEASURES: Relative risk of admission for 12 avoidable hospital conditions (AHCs) identified by a physician panel. RESULTS: Uninsured and Medicaid patients were more likely than insured patients to be hospitalized for AHCs. Rates for uninsured patients were significantly greater than for privately insured patients in Massachusetts for 10 of 12 individual AHCs, and in Maryland for five of 12 AHCs. After adjustment for baseline utilization, the results were statistically significant for 10 of 12 AHCs in Massachusetts and seven of 12 AHCs in Maryland. For Medicaid patients, rates were significantly greater than for privately insured patients for all AHCs in each state before adjustment, and for nine of 12 and seven of 12 AHCs in each state, respectively, after adjustment for baseline utilization. CONCLUSION: Our findings suggest that patients who are uninsured or who have Medicaid coverage have higher rates of hospitalization for conditions that can often be treated out of hospital or avoided altogether. Our approach is potentially useful for routine monitoring of access and quality of care for selected groups of patients.

暂无摘要（点击查看原文获取完整内容）

Natural disasters, labor disputes, terrorism and more mundane risks can seriously disrupt or delay the flow of material, information and cash through an organization's supply chain. The authors assert that how well a company fares against such threats will depend on its level of preparedness, and the type of disruption. Each supply-chain risk to forecasts, information systems, intellectual property, procurement, inventory and capacity has its own drivers and effective mitigation strategies. To avoid lost sales, increased costs or both, managers need to tailor proven risk-reduction strategies to their organizations. Managing supply-chain risk is difficult, however. Dell, Toyota, Motorola and other leading manufacturers excel at identifying and neutralizing supply-chain risks through a delicate balancing act: keeping inventory, capacity and related elements at appropriate levels across the entire supply chain in a rapidly changing environment. Organizations can prepare for or avoid delays by smart sizing their capacity and inventory. The manager serves as a kind of financial portfolio manager, seeking to achieve the highest achievable profits (reward) for varying levels of supply-chain risk. The authors recommend a powerful what if? team exercise called stress testing to identify potentially weak links in the supply chain. Armed with this shared understanding, companies can then select the best mitigation strategy: holding reserves, pooling inventory, using redundant suppliers, balancing capacity and inventory, implementing robust backup and recovery systems, adjusting pricing and incentives, bringing or keeping production in-house, and using Continuous Replenishment Programs (CRP), Collaborative Planning, Forecasting and Replenishment (CPFR) and other supply-chain initiatives.

Research on automatic attitude activation has documented a pervasive tendency to nonconsciously classify most if not all incoming stimuli as either good or bad. Two experiments tested a functional explanation for this effect. The authors hypothesized that automatic evaluation results directly in behavioral predispositions toward the stimulus, such that positive evaluations produce immediate approach tendencies, and negative evaluations produce immediate avoidance tendencies. Participants responded to attitude object stimuli either by pushing or by pulling a lever. Consistent with the hypothesis, participants were faster to respond to negatively valenced stimuli when pushing the lever away (avoid) than when pulling it toward them (approach) but were faster to respond to positive stimuli by pulling than by pushing the lever. This pattern held even when evaluation of the stimuli was irrelevant to the participants’ conscious task. The automatic classification of stimuli as either good or bad appears to have direct behavioral consequences.

We offer suggestions to avoid misuse of information-theoretic methods in wildlife laboratory and field studies. Our suggestions relate to basic science issues and the need to ask deeper questions (4 problems are noted), errors in the way that analytical methods are used (7 problems), and outright mistakes seen commonly in the published literature (5 problems). We assume that readers are familiar with the information-theoretic approaches and provide several examples of misuse. Any method can be misused-our purpose here is to suggest constructive ways to avoid misuse.

Abstract. Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be a misleading indicator of average error, and thus the MAE would be a better metric for that purpose. While some concerns over using RMSE raised by Willmott and Matsuura (2005) and Willmott et al. (2009) are valid, the proposed avoidance of RMSE in favor of MAE is not the solution. Citing the aforementioned papers, many researchers chose MAE over RMSE to present their model evaluation statistics when presenting or adding the RMSE measures could be more beneficial. In this technical note, we demonstrate that the RMSE is not ambiguous in its meaning, contrary to what was claimed by Willmott et al. (2009). The RMSE is more appropriate to represent model performance than the MAE when the error distribution is expected to be Gaussian. In addition, we show that the RMSE satisfies the triangle inequality requirement for a distance metric, whereas Willmott et al. (2009) indicated that the sums-of-squares-based statistics do not satisfy this rule. In the end, we discussed some circumstances where using the RMSE will be more beneficial. However, we do not contend that the RMSE is superior over the MAE. Instead, a combination of metrics, including but certainly not limited to RMSEs and MAEs, are often required to assess model performance.

The immune system generally avoids horror autotoxicus or autoimmunity, an attack against the body's own constituents. This avoidance requires that self-reactive T cells be actively silenced or tolerized. We propose that dendritic cells (DCs) play a critical role in establishing tolerance, especially in the periphery, after functioning T cells have been produced in the thymus. In the steady state, meaning in the absence of acute infection and inflammation, DCs are in an immature state and not fully differentiated to carry out their known roles as inducers of immunity. Nevertheless, immature DCs continuously circulate through tissues and into lymphoid organs, capturing self antigens as well as innocuous environmental proteins. Recent experiments have provided direct evidence that antigen-loaded immature DCs silence T cells either by deleting them or by expanding regulatory T cells. This capacity of DCs to induce peripheral tolerance can work in two opposing ways in the context of infection. In acute infection, a beneficial effect should occur. The immune system would overcome the risk of developing autoimmunity and chronic inflammation if, before infection, tolerance were induced to innocuous environmental proteins as well as self antigens captured from dying infected cells. For chronic or persistent pathogens, a second but dire potential could take place. Continuous presentation of a pathogen by immature DCs, HIV-1 for example, may lead to tolerance and active evasion of protective immunity. The function of DCs in defining immunologic self provides a new focus for the study of autoimmunity and chronic immune-based diseases.

Archimedes said, “Give me the place to stand, and a lever long enough, and I will move the Earth.” Economists have their own powerful lever: the instrumental variable estimator. The instrumental variable estimator can avoid the bias that ordinary least squares suffers when an explanatory variable in a regression is correlated with the regression's disturbance term. But, like Archimedes' lever, instrumental variable estimation requires both a valid instrument on which to stand and an instrument that isn't too short (or “too weak”). This paper briefly reviews instrumental variable estimation, discusses classic strategies for avoiding invalid instruments (instruments themselves correlated with the regression's disturbances), and describes recently developed strategies for coping with weak instruments (instruments only weakly correlated with the offending explanator).

Adult bone marrow derived mesenchymal stem cells offer the potential to open a new frontier in medicine. Regenerative medicine aims to replace effete cells in a broad range of conditions associated with damaged cartilage, bone, muscle, tendon and ligament. However the normal process of immune rejection of mismatched allogeneic tissue would appear to prevent the realisation of such ambitions. In fact mesenchymal stem cells avoid allogeneic rejection in humans and in animal models. These finding are supported by in vitro co-culture studies. Three broad mechanisms contribute to this effect. Firstly, mesenchymal stem cells are hypoimmunogenic, often lacking MHC-II and costimulatory molecule expression. Secondly, these stem cells prevent T cell responses indirectly through modulation of dendritic cells and directly by disrupting NK as well as CD8+ and CD4+ T cell function. Thirdly, mesenchymal stem cells induce a suppressive local microenvironment through the production of prostaglandins and interleukin-10 as well as by the expression of indoleamine 2,3,-dioxygenase, which depletes the local milieu of tryptophan. Comparison is made to maternal tolerance of the fetal allograft, and contrasted with the immune evasion mechanisms of tumor cells. Mesenchymal stem cells are a highly regulated self-renewing population of cells with potent mechanisms to avoid allogeneic rejection.