LEARNING FROM NEAR MISSES IN MEDICATION ERRORS: A BAYESIAN APPROACH

Medical errors originating in health care facilities are a significant source of preventable morbidity, mortality, and healthcare costs. Voluntary error report systems that collect information on the causes and contributing factors of medi- cal errors regardless of the resulting harm may be useful for developing effective harm prevention strategies. Some patient safety experts question the utility of data from errors that did not lead to harm to the patient, also called near misses. A near miss (a.k.a. close call) is an unplanned event that did not result in injury to the patient. Only a fortunate break in the chain of events prevented injury. We use data from a large voluntary reporting system of 836,174 medication errors from 1999 to 2005 to provide evidence that the causes and contributing factors of errors that result in harm are similar to the causes and contributing factors of near misses. We develop Bayesian hierarchical models for estimating the log odds of selecting a given cause (or contributing factor) of error given harm has occurred and the log odds of selecting the same cause given that harm did not occur. The posterior distribution of the correlation between these two vectors of log-odds is used as a measure of the evidence supporting the use of data from near misses and their causes and contributing factors to prevent medical errors. In addition, we identify the causes and contributing factors that have the highest or lowest log-odds ratio of harm versus no harm. These causes and contributing factors should also be a focus in the design of prevention strategies. This paper provides important evidence on the utility of data from near misses, which constitute the vast majority of errors in our data.

On the Behaviour of Marginal and Conditional Akaike Information Criteria in Linear Mixed Models

In linear mixed models, model selection frequently includes the selection of random effects. Two versions of the Akaike information criterion (AIC) have been used, based either on the marginal or on the conditional distribution. We show that the marginal AIC is no longer an asymptotically unbiased estimator of the Akaike information, and in fact favours smaller models without random effects. For the conditional AIC, we show that ignoring estimation uncertainty in the random effects covariance matrix, as is common practice, induces a bias that leads to the selection of any random effect not predicted to be exactly zero. We derive an analytic representation of a corrected version of the conditional AIC, which avoids the high computational cost and imprecision of available numerical approximations. An implementation in an R package is provided. All theoretical results are illustrated in simulation studies, and their impact in practice is investigated in an analysis of childhood malnutrition in Zambia.

Designs in Partially Controlled Studies: Messages from a Review

The ability to evaluate effects of factors on outcomes is increasingly important for a class of studies that control some but not all of the factors. Although important advances have been made in methods of analysis for such partially controlled studies,work on designs for such studies has been relatively limited. To help understand why, we review main designs that have been used for such partially controlled studies. Based on the review, we give two complementary reasons that explain the limited work on such designs, and suggest a new direction in this area.

A CASE STUDY IN PHARMACOLOGIC IMAGING USING PRINCIPAL CURVES IN SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY

In this manuscript we are concerned with functional imaging of the colon to assess the kinetics of a microbicide lubricant. The overarching goal is to understand the distribution of the lubricant in the colon. Such information is crucial for understanding the potential impact of the microbicide on HIV viral transmission. The experiment was conducted by imaging a radiolabeled lubricant distributed in the subject’s colon. The tracer imaging was conducted via single photon emission computed tomography (SPECT), a non-invasive, in-vivo functional imaging technique. We develop a novel principal curve algorithm to construct a three dimensional curve through the colon images. The developed algorithm is tested and debugged on several difficult two dimensional images of familiar curves where the original principal curve algorithm does not apply. The final curve fit to the colon data is compared with experimental sigmoidoscope collection.

Reduced Bayesian Hierarchical Models: Estimating Health Effects of Simultaneous Exposure to Multiple Pollutants

Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.

USING THE R PACKAGE crlmm FOR GENOTYPING AND COPY NUMBER ESTIMATION

Genotyping platforms such as Affymetrix can be used to assess genotype-phenotype as well as copy number-phenotype associations at millions of markers. While genotyping algorithms are largely concordant when assessed on HapMap samples, tools to assess copy number changes are more variable and often discordant. One explanation for the discordance is that copy number estimates are susceptible to systematic differences between groups of samples that were processed at different times or by different labs. Analysis algorithms that do not adjust for batch effects are prone to spurious measures of association. The R package crlmm implements a multilevel model that adjusts for batch effects and provides allele-specific estimates of copy number. This paper illustrates a workflow for the estimation of allele-specific copy number, develops markerand study-level summaries of batch effects, and demonstrates how the marker-level estimates can be integrated with complimentary Bioconductor software for inferring regions of copy number gain or loss. All analyses are performed in the statistical environment R. A compendium for reproducing the analysis is available from the author’s website (http://www.biostat.jhsph.edu/~rscharpf/crlmmCompendium/index.html).

Self-Reported Memory Symptoms with Coronary Artery Disease: A Prospective of CABG Patients and Nonsurgical Controls

Background. Subjective memory complaints are common after coronary artery bypass grafting (CABG), but previous studies have concluded that such symptoms are more closely associated with depressed mood than objective cognitive dysfunction. We compared the incidence of self-reported memory symptoms at 3 and 12 months after CABG with that of a control group of patients with comparable risk factors for coronary artery disease but without surgery. Methods. Patients undergoing CABG (n = 140) and a demographically similar nonsurgical control group with coronary artery disease (n = 92) were followed prospectively at 3 and 12 months. At each follow-up time, participants were asked about changes since the previous evaluation in areas of memory, calculations, reading, and personality. A Functional Status Questionnaire (FSQ) and self-report measure of symptoms of depression (CES-D) were also completed. Results. The frequency of self-reported changes in memory, personality, and reading at 3 months was significantly higher among CABG patients than among nonsurgical controls. By contrast, there were no differences in the frequency of self-reported symptoms relating to calculations or overall rating of functional status. After adjusting for a measure of depression (CES-D rating score), the risk for self-reported memory changes remained nearly 5 times higher among the CABG patients than control subjects. The relative risk of developing new self-reported memory symptoms between 3 and 12 months was 2.5 times higher among CABG patients than among nonsurgical controls (CI 1.24 – 5.02), and the overall prevalence of memory symptoms at 12 months was also higher among CABG patients (39%) than controls (14%). Conclusions. The frequency of self-reported memory symptoms 3 and 12 months after baseline is significantly higher among CABG patients than control patients with comparable risk factors for coronary and cerebrovascular disease. These differences could not be accounted for by symptoms of depression. The self-reported cognitive symptoms appear to be relatively specific for memory, and may reflect aspects of memory functioning that are not captured by traditional measures of new verbal learning and memory. The etiology of these self-reported memory symptoms remains unclear, but our findings as well as those of others, may implicate factors other than cardiopulmonary bypass itself.

Causal Inference in Observational Studies with Outcome-Dependent Sampling

In this paper, we consider estimation of the causal effect of a treatment on an outcome from observational data collected in two phases. In the first phase, a simple random sample of individuals are drawn from a population. On these individuals, information is obtained on treatment, outcome, and a few low-dimensional confounders. These individuals are then stratified according to these factors. In the second phase, a random sub-sample of individuals are drawn from each stratum, with known, stratum-specific selection probabilities. On these individuals, a rich set of confounding factors are collected. In this setting, we introduce four estimators: (1) simple inverse weighted, (2) locally efficient, (3) doubly robust and (4)enriched inverse weighted. We evaluate the finite-sample performance of these estimators in a simulation study. We also use our methodology to estimate the causal effect of trauma care on in-hospital mortality using data from the National Study of Cost and Outcomes of Trauma.

Differences between dual X-ray absorptiometry using pencil beam and fan beam modes and their determinants in vivo and in vitro

The aim of this study was to determine the influence of individual factors on differences in bone mineral density (BMD) using dual X-ray absorptiometry pencil beam (PB) and fan beam (FB) modes in vivo and in vitro. PB.BMD and FB.BMD of 63 normal Caucasian females ages 21-80 yr were measured at the lumbar spine and hip. Residuals of the FB/PB regression were used to assess the impact of height, weight, adiposity index (AI) (= weight/height(3/2)), back tissue thickness, and PB.BMD, respectively, on FB/PB difference. The Hologic Anthropomorphic Spine Phantom (ASP) was measured using the PB and FB modes at two different levels to assess the impact of scanning mode and focus distance. The European Spine Phantom (ESP) prototype, a geometrically well-defined phantom with known vertebral densities, was measured using PB and FB modes and analyzed manually to determine the impact of bone density on FB/PB difference and automatically to determine the impact of edge detection on FB/PB difference. Population BMD results were perfectly correlated, but significantly overestimated by 1.5% at the lumbar spine and underestimated by 0.7% at the neck, 1.8% at the trochanter, and 2.0% at the total hip, respectively, when using the FB compared with PB mode. At the lumbar spine, the FB/PB residual correlated negatively with height (r = 0.34, p < 0.01) and PB.BMD (r = 0.48, p <: 0. 0001) and positively with AI (r = 0.26, p < 0.05). At the hip, residual of trochanter correlated positively with weight (r = 0.36, p < 0.01) and AI (r = 0.36, p < 0.01). The FB mode significantly increased ASP BMD by 0.7% compared with PB. Using the FB mode, increasing focus distance significantly (p < 0.001) decreased area and bone mineral content, but not BMD. By contrast, increasing focus distance significantly decreased PB.BMD by 0.7%. With the ESP, the PB mode supplied accurate projected are of the bone (AREA) results but significant underestimation of specified BMD in the manual analysis. The FB mode significantly underestimated PB. AREA by 2.9% but fitted specified BMD quite well. FB/PB overestimation was larger for the low-density (+8.7%) than for the high-density vertebra (+4. 9%). The automated analysis resulted in more than 14% underestimation of PB. AREA (low-density vertebra) and an almost 13% overestimation of PB.BMD (high-density vertebra) using FB. In conclusion, FB and PB measurements are highly correlated at the lumbar spine and hip with small but significant BMD differences related to height, adiposity, and BMD. In clinical practice, it can be erroneous to switch from one method to another, especially in women with low bone density.

VHB-JOURQUAL2: Method, Results, and Implications of the German Academic Association for Business Research's Journal Ranking

VHB-JOURQUAL represents the official journal ranking of the German Academic Association for Business Research. Since its introduction in 2003, the ranking has become the most influential journal evaluation approach in German-speaking countries, impacting several key managerial decisions of German, Austrian, and Swiss business schools. This article reports the methodological approach of the ranking’s second edition. It also presents the main results and additional analyses on the validity of the rating and the underlying decision processes of the respondents. Selected implications for researchers and higher-education institutions are discussed.

EU trade agreements and their impacts on human rights: study commissioned by the German Federal Ministry for Economic Cooperation and Development (BMZ)

The European Union’s (EU) trade policy has a strong influence on economic development and the human rights situation in the EU’s partner countries, particularly in developing countries. The present study was commissioned by the German Federal Ministry for Economic Cooperation and Development (BMZ) as a contribution to further developing appropriate methodologies for assessing human rights risks in development-related policies, an objective set in the BMZ’s 2011 strategy on human rights. The study offers guidance for stakeholders seeking to improve their knowledge of how to assess, both ex ante and ex post, the impact of Economic Partnership Agreements on poverty reduction and the right to food in ACP countries. Currently, human rights impacts are not yet systematically addressed in the trade sustainability impact assessments (trade SIAs) that the European Commission conducts when negotiating trade agreements. Nor do they focus specifically on disadvantaged groups or include other benchmarks relevant to human rights impact assessments (HRIAs). The EU itself has identified a need for action in this regard. In June 2012 it presented an Action Plan on Human Rights and Democracy that calls for the inclusion of human rights in all impact assessments and in this context explicitly refers to trade agreements. Since then, the EU has begun to slightly adapt its SIA methodology and is working to define more adequate human rights–consistent procedures. It is hoped that readers of this study will find inspiration to help contribute to this process and help improve human rights consistency of future trade options.

Periodising globalisation: Mauritian integration into the sugar commodity chain (1825-2005)

Using the case study of Mauritius, and its integration into the international sugar commodity chain, this paper shows that the analysis of commodity chains can be fruitfully employed to respond to recent calls in the field of global/world history for a periodisation of globalisation. The entry of Mauritius into the British Empire brought about a particular kind of integration of the island into the capitalist world system. Central to this integration was the production of sugar under the West Indian Sugar Protocol, with this ultimately turning Mauritius from a free port into a plantation economy. This shaped the island's economic and political practice, and brought the formation of a range of institutions that sustained a high degree of inequality among Mauritians by finding ever newer ways of conciliating socio-economic mobility with exploitation. The paper discusses Mauritian history through the framework of bilateral and multilateral trading agreements that had a significant impact on the sugar industry, and kept the island economically dependent on this single crop. This only changed when the postcolonial state succeeded in diversifying the Mauritian economy during the 1970s and 1980s.

Role of Urbanization, Land-Use Diversity, and Livestock Intensification in Zoonotic Emerging Infectious Diseases

Emerging infectious diseases (EIDs) continue to significantly threaten human and animal health. While there has been some progress in identifying underlying proximal driving forces and causal mechanisms of disease emergence, the role of distal factors is most poorly understood. This article focuses on analyzing the statistical association between highly pathogenic avian influenza (HPAI) H5N1 and urbanization, land-use diversity and poultry intensification. A special form of the urban transition—peri-urbanization—was hypothesized as being associated with ‘hot-spots’ of disease emergence. Novel metrics were used to characterize these distal risk factors. Our models, which combined these newly proposed risk factors with previously known natural and human risk factors, had a far higher predictive performance compared to published models for the first two epidemiological waves in Viet Nam. We found that when relevant risk factors are taken into account, urbanization is generally not a significant independent risk factor. However, urbanization spatially combines other risk factors leading to peri-urban places being the most likely ‘hot-spots’. The work highlights that peri-urban areas have highest levels of chicken density, duck and geese flock size diversity, fraction of land under rice, fraction of land under aquaculture compared to rural and urban areas. Land-use diversity, which has previously never been studied in the context of HPAI H5N1, was found to be a significant risk factor. Places where intensive and extensive forms of poultry production are collocated were found to be at greater risk.

Erbschaften und Schenkungen im Kanton Bern, Steuerjahre 2002 bis 2012

Anhand von Steuerdaten der Jahre 2002 bis 2012 des Kantons Bern werden einige Ergebnisse zur Verteilung von Erbschaften und Schenkungen präsentiert. Aufgezeigt wird, (1) wie sich Erbschaften und Schenkungen über die Zeit entwickelt haben, (2) wie Erbschaften und Schenkungen nach Höhe der erhaltenen Beträge verteilt sind, (3) wie hoch die statistische Wahrscheinlichkeit ist, Erbschaften und Schenkungen bestimmten Umfangs zu erhalten, (4) wie sich Erbschaften und Schenkungen über Alter der empfangenden Steuersubjekte verteilen und (5) welcher Zusammenhang zwischen den bisherigen ökonomischen Ressourcen (Einkommen, Vermögen) und dem Erhalt von Erbschaften und Schenkungen besteht. Zentrale Ergebnisse sind unter anderem, dass Erbschaften und Schenkungen extrem schief verteilt sind und folglich die Wahrscheinlichkeit, grössere Beträge zu erben oder geschenkt zu erhalten, nur gering ist. Nur ein kleiner Teil der Bevölkerung wird je in den Genuss von Erbschaften oder Schenkungen kommen, die nach Annahme der Erbschaftssteuerinitiative zu einer Besteuerung führen würden. Weiterhin sind Erbschaften und Schenkungen hinsichtlich der bisherigen ökonomischen Position der empfangenden Steuersubjekte extrem ungleich verteilt. Grössere Erbschaften und Schenkungen gehen in erster Linie an diejenigen, die bereits zuvor die höchsten Einkommen und grössten Vermögen aufweisen.

Corruption and Growth Under Weak Identification

The goal of this paper is to revisit the influential work of Mauro [1995] focusing on the strength of his results under weak identification. He finds a negative impact of corruption on investment and economic growth that appears to be robust to endogeneity when using two-stage least squares (2SLS). Since the inception of Mauro [1995], much literature has focused on 2SLS methods revealing the dangers of estimation and thus inference under weak identification. We reproduce the original results of Mauro [1995] with a high level of confidence and show that the instrument used in the original work is in fact 'weak' as defined by Staiger and Stock [1997]. Thus we update the analysis using a test statistic robust to weak instruments. Our results suggest that under Mauro's original model there is a high probability that the parameters of interest are locally almost unidentified in multivariate specifications. To address this problem, we also investigate other instruments commonly used in the corruption literature and obtain similar results.