Never events in gastrointestinal nursing

Gastrointestinal diseases and disorders frequently require interventions that can lead to serious consequences for patients when an organization has not put in place the correct systems and processes to prevent incidents from happening, procedures have not been followed (generally due to poor observation), or when an individual disregards protocol (generally due to lack of judgment). It has been identified that over 400,000 patients suffer potentially preventable harmful events each year (Emslie, 2002). In this article, Carol Cox describes the types of risks that can lead to never events and factors that increase the potential for error

Intelligent power system protection data management

The Power Flow is the most important issue to ensure an efficient yet affordable system. To maintain a low failure electrical breakdown or blackout analysis of faults leads to appropriate protection settings which can be computed in order to select suitable fuse, circuit breaker size and type of relay. The studies and detection of these faults is necessary to ensure that the reliability and stability of the power system do not suffer a decrement as a result of a critical event such a fault. This project will analyze a power systems under fault conditions

Developing a model to predict aircraft maintenance performance

[Abstract]: A three-pronged approach was adopted to the investigation of causes of maintenance errors in army aviation. In the first phase of the research, analysis of maintenance incident reports suggested that individuals were mostly at fault, making errors because they failed to follow procedures and were inadequately supervised. Interviews with maintenance technicians, on the other hand, put the spotlight on organisational variables, such as pressures created by poor planning. In the third phase, a survey instrument administered to 448 maintenance workers was used to develop a structural model that predicted 34% of the variance in psychological health, 16% of the variance in turnover intentions, and 16% of the variance in self-reported maintenance errors. Implications of these findings are discussed

Classification and reduction of pilot error

Human error is a primary or contributing factor in about two-thirds of commercial aviation accidents worldwide. With the ultimate goal of reducing pilot error accidents, this contract effort is aimed at understanding the factors underlying error events and reducing the probability of certain types of errors by modifying underlying factors such as flight deck design and procedures. A review of the literature relevant to error classification was conducted. Classification includes categorizing types of errors, the information processing mechanisms and factors underlying them, and identifying factor-mechanism-error relationships. The classification scheme developed by Jens Rasmussen was adopted because it provided a comprehensive yet basic error classification shell or structure that could easily accommodate addition of details on domain-specific factors. For these purposes, factors specific to the aviation environment were incorporated. Hypotheses concerning the relationship of a small number of underlying factors, information processing mechanisms, and error types types identified in the classification scheme were formulated. ASRS data were reviewed and a simulation experiment was performed to evaluate and quantify the hypotheses

How do trainee doctors learn about research? Content analysis of Australian specialist colleges' intended research curricula

Objectives: Patients do better in research-intense environments. The importance of research is reflected in the accreditation requirements of Australian clinical specialist colleges. The nature of college-mandated research training has not been systematically explored. We examined the intended research curricula of Australian trainee doctors described by specialist colleges, their constructive alignment and the nature of scholarly project requirements. Design: We undertook content analysis of publicly available documents to characterise college research training curricula. Setting: We reviewed all publicly accessible information from the websites of Australian specialist colleges and their subspecialty divisions. We retrieved curricula, handbooks and assessment-related documents. Participants: Fifty-eight Australian specialist colleges and their subspecialty divisions. Primary and secondary outcome measures: Two reviewers extracted and coded research-related activities as learning outcomes, activities or assessments, by research stage (using, participating in or leading research) and competency based on Bloom’s taxonomy (remembering, understanding, applying, analysing, evaluating, creating). We coded learning and assessment activities by type (eg, formal research training, publication) and whether it was linked to a scholarly project. Requirements related to project supervisors’ research experience were noted. Results: Fifty-five of 58 Australian college subspecialty divisions had a scholarly project requirement. Only 11 required formal research training; two required an experienced research supervisor. Colleges emphasised a role for trainees in leading research in their learning outcomes and assessments, but not learning activities. Less emphasis was placed on using research, and almost no emphasis on participation. Most learning activities and assessments mapped to the ‘creating’ domain of Bloom’s taxonomy, whereas most learning outcomes mapped to the ‘evaluating’ domain. Overall, most research learning and assessment activities were related to leading a scholarly project. Conclusions: Australian specialist college research curricula appear to emphasise a role for trainees in leading research and producing research deliverables, but do not mandate formal research training and supervision by experienced researchers

From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood

Our goal is to learn a semantic parser that maps natural language utterances into executable programs when only indirect supervision is available: examples are labeled with the correct execution result, but not the program itself. Consequently, we must search the space of programs for those that output the correct result, while not being misled by spurious programs: incorrect programs that coincidentally output the correct result. We connect two common learning paradigms, reinforcement learning (RL) and maximum marginal likelihood (MML), and then present a new learning algorithm that combines the strengths of both. The new algorithm guards against spurious programs by combining the systematic search traditionally employed in MML with the randomized exploration of RL, and by updating parameters such that probability is spread more evenly across consistent programs. We apply our learning algorithm to a new neural semantic parser and show significant gains over existing state-of-the-art results on a recent context-dependent semantic parsing task.Comment: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (2017

Using e-learning to support international students' dissertation preparation

Purpose: A research paper on the design and implementation of an e-learning resource responding to the globalisation of education. The purpose of this paper is to focus on the challenges presented in learning and teaching on how to support international postgraduate (PG) students undertaking the specific task of a dissertation. Design/methodology/approach: Using findings from 250 PG students, 40 supervisors and two module tutors the research identified the content and language issues faced by students and recognised the need to design an enabler supporting the latter as independent learners and the academic staff delivering support. Findings: The e-learning tool provides an independent learning tool which addresses student concerns relating to the process and content of structuring a dissertation and the function of language. Initial responses have been positive from both staff and students in respect to providing a source of student support and feedback. Originality/value: The research shows how the Dissertation Game Model (DGM), evolved into an e-learning resource supporting student understanding of the content, structure, planning and writing of a dissertation. The e-learning tool focuses on helping international students understand what the generic contents of each chapter of a dissertation should contain and supports them in engaging in research as a transferable skill