3,254 research outputs found

    Introduction: Revisiting the Roles and Responsibilities of Trade Associations

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    We explain that the reasons for this Dialog stem from the enduring gaps in our understanding of what trade associations are, how they work, and what impact they have on members, industries, markets, and societies. The Dialog includes an opening paper by Thomas Lawton, Tazeeb Rajwani and Amy Minto and is followed by contributions from Michael Barnett, Steven Kahl, Lyn Spillman, and Howard Aldrich. Building on previous and ongoing research, each author reflected on the key questions driving this Dialogue: Do trade associations matter and if so, how? We argue that not only do they matter but more attention needs to be given to their roles and responsibilities

    Environmental modeling and recognition for an autonomous land vehicle

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    An architecture for object modeling and recognition for an autonomous land vehicle is presented. Examples of objects of interest include terrain features, fields, roads, horizon features, trees, etc. The architecture is organized around a set of data bases for generic object models and perceptual structures, temporary memory for the instantiation of object and relational hypotheses, and a long term memory for storing stable hypotheses that are affixed to the terrain representation. Multiple inference processes operate over these databases. Researchers describe these particular components: the perceptual structure database, the grouping processes that operate over this, schemas, and the long term terrain database. A processing example that matches predictions from the long term terrain model to imagery, extracts significant perceptual structures for consideration as potential landmarks, and extracts a relational structure to update the long term terrain database is given

    Biodesalination: an emerging technology for targeted removal of Na+and Cl−from seawater by cyanobacteria

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    Although desalination by membrane processes is a possible solution to the problem of freshwater supply, related cost and energy demands prohibit its use on a global scale. Hence, there is an emerging necessity for alternative, energy and cost-efficient methods for water desalination. Cyanobacteria are oxygen-producing, photosynthetic bacteria that actively grow in vast blooms both in fresh and seawater bodies. Moreover, cyanobacteria can grow with minimal nutrient requirements and under natural sunlight. Taking these observations together, a consortium of five British Universities was formed to test the principle of using cyanobacteria as ion exchangers, for the specific removal of Na+ and Cl− from seawater. This project consisted of the isolation and characterisation of candidate strains, with central focus on their potential to be osmotically and ionically adaptable. The selection panel resulted in the identification of two Euryhaline strains, one of freshwater (Synechocystis sp. Strain PCC 6803) and one of marine origin (Synechococcus sp. Strain PCC 7002) (Robert Gordon University, Aberdeen). Other work packages were as follows. Genetic manipulations potentially allowed for the expression of a light-driven, Cl−-selective pump in both strains, therefore, enhancing the bioaccumulation of specific ions within the cell (University of Glasgow). Characterisation of surface properties under different salinities (University of Sheffield), ensured that cell–liquid separation efficiency would be maximised post-treatment, as well as monitoring the secretion of mucopolysaccharides in the medium during cell growth. Work at Newcastle University is focused on the social acceptance of this scenario, together with an assessment of the potential risks through the generation and application of a Hazard Analysis and Critical Control Points plan. Finally, researchers in Imperial College (London) designed the process, from biomass production to water treatment and generation of a model photobioreactor. This multimodal approach has produced promising first results, and further optimisation is expected to result in mass scaling of this process

    Using patient experience data to develop a patient experience toolkit to improve hospital care: a mixed-methods study

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    Background Patients are increasingly being asked to provide feedback about their experience of health-care services. Within the NHS, a significant level of resource is now allocated to the collection of this feedback. However, it is not well understood whether or not, or how, health-care staff are able to use these data to make improvements to future care delivery. Objective To understand and enhance how hospital staff learn from and act on patient experience (PE) feedback in order to co-design, test, refine and evaluate a Patient Experience Toolkit (PET). Design A predominantly qualitative study with four interlinking work packages. Setting Three NHS trusts in the north of England, focusing on six ward-based clinical teams (two at each trust). Methods A scoping review and qualitative exploratory study were conducted between November 2015 and August 2016. The findings of this work fed into a participatory co-design process with ward staff and patient representatives, which led to the production of the PET. This was primarily based on activities undertaken in three workshops (over the winter of 2016/17). Then, the facilitated use of the PET took place across the six wards over a 12-month period (February 2017 to February 2018). This involved testing and refinement through an action research (AR) methodology. A large, mixed-methods, independent process evaluation was conducted over the same 12-month period. Findings The testing and refinement of the PET during the AR phase, with the mixed-methods evaluation running alongside it, produced noteworthy findings. The idea that current PE data can be effectively triangulated for the purpose of improvement is largely a fallacy. Rather, additional but more relational feedback had to be collected by patient representatives, an unanticipated element of the study, to provide health-care staff with data that they could work with more easily. Multidisciplinary involvement in PE initiatives is difficult to establish unless teams already work in this way. Regardless, there is merit in involving different levels of the nursing hierarchy. Consideration of patient feedback by health-care staff can be an emotive process that may be difficult initially and that needs dedicated time and sensitive management. The six ward teams engaged variably with the AR process over a 12-month period. Some teams implemented far-reaching plans, whereas other teams focused on time-minimising ‘quick wins’. The evaluation found that facilitation of the toolkit was central to its implementation. The most important factors here were the development of relationships between people and the facilitator’s ability to navigate organisational complexity. Limitations The settings in which the PET was tested were extremely diverse, so the influence of variable context limits hard conclusions about its success. Conclusions The current manner in which PE feedback is collected and used is generally not fit for the purpose of enabling health-care staff to make meaningful local improvements. The PET was co-designed with health-care staff and patient representatives but it requires skilled facilitation to achieve successful outcomes. Funding The National Institute for Health Research Health Services and Delivery Research programme

    Improving patient experience and safety at transitions of care through the Your Care Needs You (YCNY) intervention: a study protocol for a cluster randomised controlled feasibility trial

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    Background: Patients, particularly older people, often experience safety issues when transitioning from hospital to home. Although the evidence is currently equivocal as to how we can improve this transition of care, interventions that support patient involvement may be more effective. The ‘Your Care Needs You’ (YCNY) intervention supports patients to ‘know more’ and ‘do more’ whilst in hospital in order that they better understand their health condition and medications, maintain their daily activities, and can seek help at home if required. The intervention aims to reduce emergency hospital readmissions and improve safety and experience during the transition to home. Methods: As part of the Partners At Care Transitions (PACT) programme of research, a multi-centred cluster randomised controlled trial (cRCT) will be conducted to explore the feasibility of the YCNY intervention and trial methodology. Data will be used to refine the intervention and develop a protocol for a definitive cRCT. Ten acute hospital wards (the clusters) from varying medical specialties including older peoples’ medicine, trauma and orthopaedics, cardiology, intermediate care, and stroke will be randomised to deliver YCNY or usual care on a 3:2 basis. Up to 200 patients aged 75 years and over and discharged to their own homes will be recruited to the study. Patients will complete follow-up questionnaires at 5-, 30-, and 90-days post-discharge and readmission data up to 90-days post-discharge will be extracted from their medical records. Study outcomes will include measures of feasibility (e.g. screening, recruitment, and retention data) and processes required to collect routine data at a patient and ward level. In addition, interviews and observations involving up to 24 patients/carers and 28 staff will be conducted to qualitatively assess the acceptability, usefulness, and feasibility of the intervention and implementation package to patients and staff. A separate sub-study will be conducted to explore how accurately primary outcome data (30-day emergency hospital readmissions) can be gathered for the definitive cRCT. Discussion: This study will establish the feasibility of the YCNY intervention which aims to improve safety and experience during transitions of care. It will identify key methodological and implementation issues that need to be addressed prior to assessing the effectiveness of the YCNY intervention in a definitive cluster randomised controlled trial

    Measuring the impact of COVID-19 on hospital care pathways

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    Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted

    Feeding back surveillance data to prevent hospital-acquired infections.

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    We describe the Centers for Disease Control and Prevention's National Nosocomial Infections Surveillance system. Elements of the system critical for successful reduction of nosocomial infection rates include voluntary participation and confidentiality; standard definitions and protocols; identification of populations at high risk; site-specific, risk- adjusted infection rates comparable across institutions; adequate numbers of trained infection control professionals; dissemination of data to health-care providers; and a link between monitored rates and prevention efforts
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