Editorial: Interruptions and medication: Is 'Do not disturb' the answer?

Abstract

Medication errors in hospitals: A literature review of disruptions to nursing practice during medication administration

© 2015 John Wiley & Sons Ltd. Aims and objectives: The purpose of this review was to explore what is known about interruptions and distractions on medication administration in the context of undergraduate nurse education. Background: Incidents and errors during the process of medication administration continue to be a substantial patient safety issue in health care settings internationally. Interruptions to the medication administration process have been identified as a leading cause of medication error. Literature recognises that some interruptions are unavoidable therefore in an effort to reduce errors, it is essential understand how undergraduate nurses learn to manage interruptions to the medication administration process. Design: Systematic, critical literature review. Methods: Utilising the electronic databases, of Medline, Scopus, PubMed and CINAHL, and recognised quality assessment guidelines, 19 articles met the inclusion criteria. Search terms included: nurses, medication incidents or errors, interruptions, disruption, distractions and multitasking. Results: Researchers have responded to the impact of interruptions and distractions on the medication administration by attempting to eliminate them. Despite the introduction of quality improvements, little is known about how nurses manage interruptions and distractions during medication administration or how they learn to do so. A significant gap in the literature exists in relation to innovative sustainable strategies that assist undergraduate nurses to learn how to safely and confidently manage interruptions in the clinical environment. Conclusions: Study findings highlight the need for further exploration into the way nurses learn to manage interruptions and distractions during medication administration. This is essential given the critical relationship between interruptions and medication error rates. Relevance to clinical practice: Better preparing nurses to safely fulfil the task of medication administration in the clinical environment, with increased confidence in the face of interruptions, could lead to a reduction in errors and concomitant improvements to patient safety

Nurse interrupted: Development of a realistic medication administration simulation for undergraduate nurses

© 2015 Elsevier Ltd. Background: Medication errors are a global phenomenon. Each year Australia-wide there are up to 96,000 preventable medication errors and in the United States there are approximately 450,000 preventable medication errors. One of the leading causes of errors is interruption yet some interruptions are unavoidable. In the interest of patient safety, nurses need to not only understand the impact of interruptions, but also be empowered with the knowledge and skills required to develop effective interruption management strategies. Well-planned simulation experiences have the potential to expose students to authentic clinical cases, otherwise unavailable to them, building critical thinking and clinical reasoning skills and preparing them for practice. Aim: This paper describes a simulated role-play experience that was developed to enable undergraduate nurses to experience, reflect on and analyse their responses to interruptions during medication administration. Methods: The simulation design presented in this paper was underpinned by both nursing and educational theorists, in combination with established simulation frameworks. Setting and Participants: Embedded within a clinical subject in 2013, the simulation experience was run over two campuses within a large Australian University. Participants included 528 second year undergraduate nursing students and 8 academic teaching staff. Outcome Mapping: To stimulate reflective learning debriefing immediately followed the simulation experience. Written reflections were completed and submitted over the following 4 weeks to extend the reflective learning process and review the impact of the experience from the student perspective. Conclusions: Undergraduate student nurses often have limited experiential background from which to draw knowledge and develop sound clinical judgements. Through exposure to clinical experiences in a safe environment, simulation technologies have been shown to create positive learning experiences and improve deductive reasoning and analysis. The heightened awareness of interruptions and their impacts on the medication administration process, along with techniques to manage interruptions more effectively serves to better prepare nurses for practice

Pondering practice: Enhancing the art of reflection

© 2017 John Wiley & Sons Ltd Aims and objectives: The aim of this study was to describe the effect that immersive simulation experiences and guided reflection can have on the undergraduate nurses' understanding of how stressful environments impact their emotions, performance and ability to implement safe administration of medications. Background: Patient safety can be jeopardised if nurses are unsure of how to appropriately manage and respond to interruptions. Medication administration errors are a major patient safety issue and often occur as a consequence of ineffective interruption management. The skills associated with medication administration are most often taught to, and performed by, undergraduate nurses in a controlled environment. However, the clinical environment in which nurses are expected to administer medications is often highly stressed and nurses are frequently interrupted. Design/Methods: This study used role-play simulation and written reflections to facilitate deeper levels of student self-awareness. A qualitative approach was taken to explore students' understanding of the effects of interruptions on their ability to undertake safe medication administration. Convenience sampling of second-year undergraduate nursing students enrolled in a medical–surgical subject was used in this study. Data were obtained from 451:528 (85.42%) of those students and analysed using thematic analysis. Results: Students reported increasing consciousness and the importance of reflection for evaluating performance and gaining self-awareness. They described self-awareness, effective communication, compassion and empathy as significant factors in facilitating self-efficacy and improved patient care outcomes. Conclusions: Following a role-play simulation experience, student nurses reported new knowledge and skill acquisition related to patient safety, and new awareness of the need for empathetic and compassionate care during medication administration. Practicing medication administration in realistic settings adds to current strategies that aim to reduce medication errors by allowing students to reflect on and in practice and develop strategies to ensure patient safety. Relevance to clinical practice: Experiencing clinical scenarios within the safety of simulated environments, offers undergraduate student nurses an opportunity to reflect on practice to provide safer, more empathetic and compassionate care for patients in the future

Calm to chaos: Engaging undergraduate nursing students with the complex nature of interruptions during medication administration

© 2017 John Wiley & Sons Ltd Aims and Objectives: To describe undergraduate student nurse responses to a simulated role-play experience focussing on managing interruptions during medication administration. Background: Improving patient safety requires that we find creative and innovative methods of teaching medication administration to undergraduate nurses in real-world conditions. Nurses are responsible for the majority of medication administrations in health care. Incidents and errors associated with medications are a significant patient safety issue and often occur as a result of interruptions. Undergraduate nursing students are generally taught medication administration skills in a calm and uninterrupted simulated environment. However, in the clinical environment medication administration is challenged by multiple interruptions. Design/Methods: A qualitative study using convenience sampling was used to examine student perceptions of a simulated role-play experience. Data were collected from 451 of a possible 528 student written reflective responses and subject to thematic analysis. Results: Students reported an increased understanding of the impacts of interruptions while administering medications and an improved awareness of how to manage disruptions. This study reports on one of three emergent themes: “Calm to chaos: engaging with the complex nature of clinical practice.”. Conclusions: Interrupting medication administration in realistic and safe settings facilitates awareness, allows for students to begin to develop management strategies in relation to interruption and increases their confidence. Students were given the opportunity to consolidate and integrate prior and new knowledge and skills through this role-play simulation

Fitting and validating the genomic evaluation model to Polish Holstein-Friesian cattle

The aim of the study was to fit the genomic evaluation model to Polish Holstein-Friesian dairy cattle. A training data set for the estimation of additive effects of single nucleotide polymorphisms (SNPs) consisted of 1227 Polish Holstein-Friesian bulls. Genotypes were obtained by the use of Illumina BovineSNP50 Genotyping BeadChip. Altogether 29 traits were considered: milk-, fat- and protein- yields, somatic cell score, four female fertility traits, and 21 traits describing conformation. The prediction of direct genomic values was based on a mixed model containing deregressed national proofs as a dependent variable and random SNP effects as independent variables. The correlations between direct genomic values and conventional estimated breeding values estimated for the whole data set were overall very high and varied between 0.98 for production traits and 0.78 for non return rates for cows. For the validation data set of 232 bulls the corresponding correlations were 0.38 for milk-, 0.37 for protein-, and 0.32 for fat yields, while the correlations between genomic enhanced breeding values and conventional estimated breeding values for the four traits were: 0.43, 0.44, 0.31, and 0.35. This model was able to pass the interbull validation criteria for genomic selection, which indicates that it is realistic to implement genomic selection in Polish Holstein-Friesian cattle

Use of partial least squares regression to impute SNP genotypes in Italian Cattle breeds

Background The objective of the present study was to test the ability of the partial least squares regression technique to impute genotypes from low density single nucleotide polymorphisms (SNP) panels i.e. 3K or 7K to a high density panel with 50K SNP. No pedigree information was used. Methods Data consisted of 2093 Holstein, 749 Brown Swiss and 479 Simmental bulls genotyped with the Illumina 50K Beadchip. First, a single-breed approach was applied by using only data from Holstein animals. Then, to enlarge the training population, data from the three breeds were combined and a multi-breed analysis was performed. Accuracies of genotypes imputed using the partial least squares regression method were compared with those obtained by using the Beagle software. The impact of genotype imputation on breeding value prediction was evaluated for milk yield, fat content and protein content. Results In the single-breed approach, the accuracy of imputation using partial least squares regression was around 90 and 94% for the 3K and 7K platforms, respectively; corresponding accuracies obtained with Beagle were around 85% and 90%. Moreover, computing time required by the partial least squares regression method was on average around 10 times lower than computing time required by Beagle. Using the partial least squares regression method in the multi-breed resulted in lower imputation accuracies than using single-breed data. The impact of the SNP-genotype imputation on the accuracy of direct genomic breeding values was small. The correlation between estimates of genetic merit obtained by using imputed versus actual genotypes was around 0.96 for the 7K chip. Conclusions Results of the present work suggested that the partial least squares regression imputation method could be useful to impute SNP genotypes when pedigree information is not available

The role of defensive information processing in population-based colorectal cancer screening uptake

BACKGROUND: Internationally, colorectal cancer screening participation remains low despite the availability of home-based testing and numerous interventions to increase uptake. To be effective, interventions should be based on an understanding of what influences individuals’ decisions about screening participation. This study investigates the association of defensive information processing (DIP) with fecal immunochemical test (FIT)–based colorectal cancer screening uptake. METHODS: Regression modeling of data from a cross-sectional survey within a population-based FIT screening program was conducted. The survey included the seven subdomains of the McQueen DIP measure. The primary outcome variable was the uptake status (screening user or nonuser). Multivariable logistic regression was used to estimate the odds ratio (OR) for screening nonuse by DIP (sub)domain score, with adjustments made for sociodemographic and behavioral factors associated with uptake. RESULTS: Higher scores (equating to greater defensiveness) on all DIP domains were significantly associated with lower uptake in the model adjusted for sociodemographic factors. In the model with additional adjustments for behavioral factors, the suppression subdomains of “deny immediacy to be tested” (OR, 0.53; 95% confidence interval [CI], 0.43–0.65; p < .001) and “self-exemption” (OR, 0.80; 95% CI, 0.68–0.96; p < .001) independently predicted nonuse of FIT-based screening. CONCLUSIONS: This is the first study outside the United States that has identified DIP as a barrier to colorectal cancer screening uptake, and it is the first focused specifically on FIT-based screening. The findings suggest that two suppression barriers, namely denying the immediacy to be tested and self-exempting oneself from screening, may be promising targets for future interventions to improve uptake

Accuracy of genomic breeding values in multi-breed dairy cattle populations

<p>Abstract</p> <p>Background</p> <p>Two key findings from genomic selection experiments are 1) the reference population used must be very large to subsequently predict accurate genomic estimated breeding values (GEBV), and 2) prediction equations derived in one breed do not predict accurate GEBV when applied to other breeds. Both findings are a problem for breeds where the number of individuals in the reference population is limited. A multi-breed reference population is a potential solution, and here we investigate the accuracies of GEBV in Holstein dairy cattle and Jersey dairy cattle when the reference population is single breed or multi-breed. The accuracies were obtained both as a function of elements of the inverse coefficient matrix and from the realised accuracies of GEBV.</p> <p>Methods</p> <p>Best linear unbiased prediction with a multi-breed genomic relationship matrix (GBLUP) and two Bayesian methods (BAYESA and BAYES_SSVS) which estimate individual SNP effects were used to predict GEBV for 400 and 77 young Holstein and Jersey bulls respectively, from a reference population of 781 and 287 Holstein and Jersey bulls, respectively. Genotypes of 39,048 SNP markers were used. Phenotypes in the reference population were de-regressed breeding values for production traits. For the GBLUP method, expected accuracies calculated from the diagonal of the inverse of coefficient matrix were compared to realised accuracies.</p> <p>Results</p> <p>When GBLUP was used, expected accuracies from a function of elements of the inverse coefficient matrix agreed reasonably well with realised accuracies calculated from the correlation between GEBV and EBV in single breed populations, but not in multi-breed populations. When the Bayesian methods were used, realised accuracies of GEBV were up to 13% higher when the multi-breed reference population was used than when a pure breed reference was used. However no consistent increase in accuracy across traits was obtained.</p> <p>Conclusion</p> <p>Predicting genomic breeding values using a genomic relationship matrix is an attractive approach to implement genomic selection as expected accuracies of GEBV can be readily derived. However in multi-breed populations, Bayesian approaches give higher accuracies for some traits. Finally, multi-breed reference populations will be a valuable resource to fine map QTL.</p

Extension of the bayesian alphabet for genomic selection

<p>Abstract</p> <p>Background</p> <p>Two Bayesian methods, BayesC<it>π </it>and BayesD<it>π</it>, were developed for genomic prediction to address the drawback of BayesA and BayesB regarding the impact of prior hyperparameters and treat the prior probability <it>π </it>that a SNP has zero effect as unknown. The methods were compared in terms of inference of the number of QTL and accuracy of genomic estimated breeding values (GEBVs), using simulated scenarios and real data from North American Holstein bulls.</p> <p>Results</p> <p>Estimates of <it>π </it>from BayesC<it>π</it>, in contrast to BayesD<it>π</it>, were sensitive to the number of simulated QTL and training data size, and provide information about genetic architecture. Milk yield and fat yield have QTL with larger effects than protein yield and somatic cell score. The drawback of BayesA and BayesB did not impair the accuracy of GEBVs. Accuracies of alternative Bayesian methods were similar. BayesA was a good choice for GEBV with the real data. Computing time was shorter for BayesC<it>π </it>than for BayesD<it>π</it>, and longest for our implementation of BayesA.</p> <p>Conclusions</p> <p>Collectively, accounting for computing effort, uncertainty as to the number of QTL (which affects the GEBV accuracy of alternative methods), and fundamental interest in the number of QTL underlying quantitative traits, we believe that BayesC<it>π </it>has merit for routine applications.</p