Data envelopment analysis in the presence of measurement error: case study from the National Database of Nursing Quality Indicators® (NDNQI®)

Data envelopment analysis (DEA) is the most commonly used approach for evaluating healthcare efficiency [B. Hollingsworth, The measurement of efficiency and productivity of health care delivery. Health Economics 17(10) (2008), pp. 1107–1128], but a long-standing concern is that DEA assumes that data are measured without error. This is quite unlikely, and DEA and other efficiency analysis techniques may yield biased efficiency estimates if it is not realized [B.J. Gajewski, R. Lee, M. Bott, U. Piamjariyakul, and R.L. Taunton, On estimating the distribution of data envelopment analysis efficiency scores: an application to nursing homes’ care planning process. Journal of Applied Statistics 36(9) (2009), pp. 933–944; J. Ruggiero, Data envelopment analysis with stochastic data. Journal of the Operational Research Society 55 (2004), pp. 1008–1012]. We propose to address measurement error systematically using a Bayesian method (Bayesian DEA). We will apply Bayesian DEA to data from the National Database of Nursing Quality Indicators^® to estimate nursing units’ efficiency. Several external reliability studies inform the posterior distribution of the measurement error on the DEA variables. We will discuss the case of generalizing the approach to situations where an external reliability study is not feasible.     

‘It’s all bollocks!’ and other critical standpoints on the UK Government’s vision of global citizenship

The UK Government’s International Citizen Service (ICS) sends volunteers abroad to ‘fight global poverty’ as ‘global citizens’. Perhaps unsurprisingly, the construction of development on the ICS programme forecloses important political and historical contexts, resulting in a model of global citizenship we might term ‘soft’. This article presents data from interviews with ICS volunteers with a specific methodological concern of recognizing the agency of young people and allowing their responses to lead discussion. The outcome is a range of themes across the data that critique the Government’s model of citizenship and, I argue, shows the volunteers to be ‘critical’ global citizens. I then ask whether we can consider this a mode of resistance. I conclude with a final data set that – the case is made – presents an imperative to allow these volunteers to have their perspectives on historical and contemporary North–South relations recognized as a critical mode of global citizenship.     

A Comparative Pharmacokinetic Estimate of Mercury in U.S. Infants Following Yearly Exposures to Inactivated Influenza Vaccines Containing Thimerosal

The use of thimerosal preservative in childhood vaccines has been largely eliminated over the past decade in the United States because vaccines have been reformulated in single‐dose vials that do not require preservative. An exception is the inactivated influenza vaccines, which are formulated in both multidose vials requiring preservative and preservative‐free single‐dose vials. As part of an ongoing evaluation by USFDA of the safety of biologics throughout their lifecycle, the infant body burden of mercury following scheduled exposures to thimerosal preservative in inactivated influenza vaccines in the United States was estimated and compared to the infant body burden of mercury following daily exposures to dietary methylmercury at the reference dose established by the USEPA. Body burdens were estimated using kinetic parameters derived from experiments conducted in infant monkeys that were exposed episodically to thimerosal or MeHg at identical doses. We found that the body burden of mercury (AUC) in infants (including low birth weight) over the first 4.5 years of life following yearly exposures to thimerosal was two orders of magnitude lower than that estimated for exposures to the lowest regulatory threshold for MeHg over the same time period. In addition, peak body burdens of mercury following episodic exposures to thimerosal in this worst‐case analysis did not exceed the corresponding safe body burden of mercury from methylmercury at any time, even for low‐birth‐weight infants. Our pharmacokinetic analysis supports the acknowledged safety of thimerosal when used as a preservative at current levels in certain multidose infant vaccines in the United States.     

Is ethnic prejudice declining in Britain? Change in social distance attitudes among ethnic majority and minority Britons

Most literature on racial prejudice deals with the racial attitudes of the ethnic majority and ethnic minorities separately. This paper breaks this tradition. We examine the social distance attitudes of white and non‐white British residents to test if these attitudes follow the same trends over time, whether they are driven by the same social processes and whether they are inter‐related. We have three main findings. Firstly, social distance from other ethnic groups has declined over time for both white and ethnic minority Britons. For the white majority there are both period and cohort elements to this decline. Secondly, we see some evidence that social distance between the majority and minority groups is reciprocal. Specifically, minorities who experience rejection by the white British feel a greater sense of distance from them. Thirdly, we find that all groups share the perception of the same ethnic hierarchy. We see evidence of particularly widespread hostility towards Muslim Britons from all ethnic groups suggesting that Muslims are singled out for negative attention from many British residents of all other backgrounds, including a large number who do not express hostility to other groups.     

Comparison of dichotomized and distributional approaches in rare event clinical trial design: a fixed Bayesian design

This research was motivated by our goal to design an efficient clinical trial to compare two doses of docosahexaenoic acid supplementation for reducing the rate of earliest preterm births (ePTB) and/or preterm births (PTB). Dichotomizing continuous gestational age (GA) data using a classic binomial distribution will result in a loss of information and reduced power. A distributional approach is an improved strategy to retain statistical power from the continuous distribution. However, appropriate distributions that fit the data properly, particularly in the tails, must be chosen, especially when the data are skewed. A recent study proposed a skew-normal method. We propose a three-component normal mixture model and introduce separate treatment effects at different components of GA. We evaluate operating characteristics of mixture model, beta-binomial model, and skew-normal model through simulation. We also apply these three methods to data from two completed clinical trials from the USA and Australia. Finite mixture models are shown to have favorable properties in PTB analysis but minimal benefit for ePTB analysis. Normal models on log-transformed data have the largest bias. Therefore we recommend finite mixture model for PTB study. Either finite mixture model or beta-binomial model is acceptable for ePTB study.     

Understanding the Dynamics of the Individual Donor’s Trust Damage in the Philanthropic Sector

Although trust is long known to be critical to predict behaviors in a charitable context, little research has examined trust damage and its effects on giving behavior. Trust damage is an intermediate state between trust and distrust, rather than a simple reversal or extension, and can change over time. Our research explores individual donor’s trust damage through a dynamic evolution. Across the longitudinal survey, we conclude that the trust damage of pre-giving, giving, and post-giving stage plays different roles in the decision-making process. Trust damage does not play a direct role in the giving intention, but it can indirectly affect giving intention through its impact on perceived benefit and perceived risk. Individual donor’s satisfaction has a strong effect on post-giving trust or continual trust damage, which in turn positively affects future giving intention and behavior. Several important insights for practitioners in the nonprofit sector are also discussed.     

Building a Values‐Informed Mental Model for New Orleans Climate Risk Management

Individuals use values to frame their beliefs and simplify their understanding when confronted with complex and uncertain situations. The high complexity and deep uncertainty involved in climate risk management (CRM) lead to individuals’ values likely being coupled to and contributing to their understanding of specific climate risk factors and management strategies. Most mental model approaches, however, which are commonly used to inform our understanding of people's beliefs, ignore values. In response, we developed a “Values‐informed Mental Model” research approach, or ViMM, to elicit individuals’ values alongside their beliefs and determine which values people use to understand and assess specific climate risk factors and CRM strategies. Our results show that participants consistently used one of three values to frame their understanding of risk factors and CRM strategies in New Orleans: (1) fostering a healthy economy, wealth, and job creation, (2) protecting and promoting healthy ecosystems and biodiversity, and (3) preserving New Orleans’ unique culture, traditions, and historically significant neighborhoods. While the first value frame is common in analyses of CRM strategies, the latter two are often ignored, despite their mirroring commonly accepted pillars of sustainability. Other values like distributive justice and fairness were prioritized differently depending on the risk factor or strategy being discussed. These results suggest that the ViMM method could be a critical first step in CRM decision‐support processes and may encourage adoption of CRM strategies more in line with stakeholders’ values.