BACKGROUND: One-third of all medication errors causing harm to hospitalized patients occur in the medication preparation and administration phase, which is predominantly a nursing activity. To monitor, evaluate and improve the quality and safety of this process, evidence-based quality indicators can be used.OBJECTIVES: The aim of study was to identify evidence-based quality indicators (structure, process and outcome) for safe in-hospital medication preparation and administration.METHODS: MEDLINE, EMBASE and CINAHL were searched for relevant studies published up to January 2015. Additionally, nine databases were searched to identify relevant grey literature. Two reviewers independently selected studies if (1) the method for quality indicator development combined a literature search with expert panel opinion, (2) the study contained quality indicators on medication safety, and (3) any of the quality indicators were applicable to hospital medication preparation and administration. A multidisciplinary team appraised the studies independently using the AIRE instrument, which contains four domains and 20 items. Quality indicators applicable to in-hospital medication preparation and administration were extracted using a structured form.RESULTS: The search identified 1683 studies, of which 64 were reviewed in detail and five met the inclusion criteria. Overall, according to the AIRE domains, all studies were clear on purpose; most of them applied stakeholder involvement and used evidence reasonably; usage of the indicator in practice was scarcely described. A total of 21 quality indicators were identified: 5 structure indicators (e.g. safety management and high alert medication), 11 process indicators (e.g. verification and protocols) and 5 outcome indicators (e.g. harm and death). These quality indicators partially cover the 7 rights.CONCLUSION: Despite the relatively small number of included studies, the identified quality indicators can serve as an excellent starting point for further development of nursing specific quality indicators for medication safety. Especially on the right patient, right route, right time and right documentation there is room future development of quality indicators.
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Background:Ecstasy (3,4-methylenedioxymethamphetamine (MDMA)) has a relatively low harm and low dependence liability but is scheduled on List I of the Dutch Opium Act (‘hard drugs’). Concerns surrounding increasing MDMA-related criminality coupled with the possibly inappropriate scheduling of MDMA initiated a debate to revise the current Dutch ecstasy policy.Methods:An interdisciplinary group of 18 experts on health, social harms and drug criminality and law enforcement reformulated the science-based Dutch MDMA policy using multi-decision multi-criterion decision analysis (MD-MCDA). The experts collectively formulated policy instruments and rated their effects on 25 outcome criteria, including health, criminality, law enforcement and financial issues, thematically grouped in six clusters.Results:The experts scored the effect of 22 policy instruments, each with between two and seven different mutually exclusive options, on 25 outcome criteria. The optimal policy model was defined by the set of 22 policy instrument options which gave the highest overall score on the 25 outcome criteria. Implementation of the optimal policy model, including regulated MDMA sales, decreases health harms, MDMA-related organised crime and environmental damage, as well as increases state revenues and quality of MDMA products and user information. This model was slightly modified to increase its political feasibility. Sensitivity analyses showed that the outcomes of the current MD-MCDA are robust and independent of variability in weight values.Conclusion:The present results provide a feasible and realistic set of policy instrument options to revise the legislation towards a rational MDMA policy that is likely to reduce both adverse (public) health risks and MDMA-related criminal burden.
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In this document, we provide the methodological background for the Safety atWork project. This document combines several project deliverables as defined inthe overall project plan: validation techniques and methods (D5.1.1), performanceindicators for safety at work (D5.1.2), personal protection equipment methods(D2.1.2), situational awareness methods (D3.1.2), and persuasive technology methods(D4.1.2).
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Chemo-enzymatic peptide synthesis is unique in enabling the fast and sustainable synthesis of cyclic peptides, complex peptides and functionalized mini-proteins. The starting materials are routinely obtained by solid-phase peptide synthesis. One of the starting materials requires an oxo-ester functionality for recognition by the enzymes active site. The SPPS-based synthesis of the oxo-ester functionality still suffers from significant byproduct formation and low overall synthesis yields. The solution to this is introduction of the oxo-ester functionality at the end of the SPPS via a so-called Passerini reaction. Such a process does not only result in a more efficient production of cyclic or long peptides, but also expand the scope towards proteins derived from biological synthesis (i.e. recombinant proteins). To highlight the relevance of this proposed methodology, we will demonstrate a site-selective modification of the pharmaceutically important drug insulin.
Granular materials (GMs) are simply a collection of individual particles, e.g., rice, coffee, iron-ore. Although straightforward in appearance, GMs are key to several processes in chemical-pharmaceutical, high-tech, agri-food and energy industry. Examples include laser sintering in additive manufacturing, tableting in pharma or just mixing of your favourite crunchy muesli mix in food industry. However, these bulk material handling processes are notorious for their inefficiency and ineffectiveness. Thereby, affecting the overall expenses and product quality. To understand and enhance the quality of a process, GMs industries utilise computer-simulations, much like how cars and aeroplanes have been designed and optimised since the 1990s. Just as how engineers utilise advanced computer-models to develop our fuel-efficient vehicle design, energy-saving granular processes are also developed utilising physics-based simulation-models, using a computer. Although physics-based models can effectively optimise large-scale processes, creating and simulating a fully representative virtual prototype of a GMs process is very iterative, computationally expensive and time intensive. On the contrary, given the available data, this is where machine learning (ML) could be of immense value. Like how ML has transformed the healthcare, energy and other top sectors, recent ML-based developments for GMs show serious promise in faster virtual prototyping and reduced computational cost. Enabling industries to rapidly design and optimise, enhancing real-time data-driven decision making. GranML aims to empower the GMs industries with ML. We will do so by (i) performing an in-depth GMs-ML literature review, (ii) developing open-access ML implementation guidelines; and (iii) an open-source proof-of-concept for an industry-relevant use case. Eventually, our follow-up mission is to build upon this vital knowledge by (i) expanding the consortium; (ii) co-developing a unified methodology for efficient computer-prototyping, unifying physics- and ML-based technologies for GMs; (iii) enhancing the existing computer-modelling infrastructure; and (iv) validating through industry focused demonstrators.
Organ-on-a-chip technology holds great promise to revolutionize pharmaceutical drug discovery and development which nowadays is a tremendously expensive and inefficient process. It will enable faster, cheaper, physiologically relevant, and more reliable (standardized) assays for biomedical science and drug testing. In particular, it is anticipated that organ-on-a-chip technology can substantially replace animal drug testing with using the by far better models of true human cells. Despite this great potential and progress in the field, the technology still lacks standardized protocols and robust chip devices, which are absolutely needed for this technology to bring the abovementioned potential to fruition. Of particular interest is heart-on-a-chip for drug and cardiotoxicity screening. There is presently no preclinical test system predicting the most important features of cardiac safety accurately and cost-effectively. The main goal of this project is to fabricate standardized, robust generic heart-on-a-chip demonstrator devices that will be validated and further optimized to generate new physiologically relevant models to study cardiotoxicity in vitro. To achieve this goal various aspects will be considered, including (i) the search for alternative chip materials to replace PDMS, (ii) inner chip surface modification and treatment (chemistry and topology), (iii) achieving 2D/3D cardiomyocyte (long term) cell culture and cellular alignment within the chip device, (iv) the possibility of integrating in-line sensors in the devices and, finally, (v) the overall chip design. The achieved standardized heart-on-a-chip technology will be adopted by pharmaceutical industry. This proposed project offers a unique opportunity for the Netherlands, and Twente in particular, which has relevant expertise, potential, and future perspective in this field as it hosts world-leading companies pioneering various core aspects of the technology that are relevant for organs-on-chips, combined with two world-leading research institutes within the University of Twente.
