Redesigning the 'choice architecture' of hospital prescription charts: a mixed methods study incorporating in situ simulation testing.

Objectives: To incorporate behavioural insights into the user-centred design of an inpatient prescription chart (Imperial Drug Chart Evaluation and Adoption Study, IDEAS chart) and to determine whether changes in the content and design of prescription charts could influence prescribing behaviour and reduce prescribing errors. Design: A mixed-methods approach was taken in the development phase of the project; in situ simulation was used to evaluate the effectiveness of the newly developed IDEAS prescription chart. Setting: A London teaching hospital. Interventions/methods: A multimodal approach comprising (1) an exploratory phase consisting of chart reviews, focus groups and user insight gathering (2) the iterative design of the IDEAS prescription chart and finally (3) testing of final chart with prescribers using in situ simulation. Results: Substantial variation was seen between existing inpatient prescription charts used across 15 different UK hospitals. Review of 40 completed prescription charts from one hospital demonstrated a number of frequent prescribing errors including illegibility, and difficulty in identifying prescribers. Insights from focus groups and direct observations were translated into the design of IDEAS chart. In situ simulation testing revealed significant improvements in prescribing on the IDEAS chart compared with the prescription chart currently in use in the study hospital. Medication orders on the IDEAS chart were significantly more likely to include correct dose entries (164/164 vs 166/174; p=0.0046) as well as prescriber's printed name (163/164 vs 0/174; p<0.0001) and contact number (137/164 vs 55/174; p<0.0001). Antiinfective indication (28/28 vs 17/29; p<0.0001) and duration (26/28 vs 15/29; p<0.0001) were more likely to be completed using the IDEAS chart. Conclusions: In a simulated context, the IDEAS prescription chart significantly reduced a number of common prescribing errors including dosing errors and illegibility. Positive behavioural change was seen without prior education or support, suggesting that some common prescription writing errors are potentially rectifiable simply through changes in the content and design of prescription charts

Recent Progress in Neutron Star Theory

This review contains chapters discussing: Energy density fluctionals of nuclear matter, Many-body theory of nucleon matter, Hadronic and quark matter, Mixtures of phases in dense matter, Neutron star observations and predictions.Comment: 33 pages +13 figs., Ann. Rev. Nucl. & Part. Science, 200

Relativistic Mean-Field Theory Equation of State of Neutron Star Matter and a Maxwellian Phase Transition to Strange Quark Matter

The equation of state of neutron star matter is examined in terms of the relativistic mean-field theory, including a scalar-isovector $\delta$-meson effective field. The constants of the theory are determined numerically so that the empirically known characteristics of symmetric nuclear matter are reproduced at the saturation density. The thermodynamic characteristics of both asymmetric nucleonic matter and $\beta$-equilibrium hadron-electron $npe$-plasmas are studied. Assuming that the transition to strange quark matter is an ordinary first-order phase transition described by Maxwell's rule, a detailed study is made of the variations in the parameters of the phase transition owing to the presence of a $\delta$-meson field. The quark phase is described using an improved version of the bag model, in which interactions between quarks are accounted for in a one-gluon exchange approximation. The characteristics of the phase transition are determined for various values of the bag parameter within the range $B\in[60,120]$ $MeV/fm^{3}$ and it is shown that including a $\delta$-meson field leads to a reduction in the phase transition pressure $P_{0}$ and in the concentrations $n_{N}$ and $n_{Q}$ at the phase transition point.Comment: 17 pages, 8 figure

A Golf Programme for People with Severe and Enduring Mental Health Problems

This article reports a pioneering golf programme for people with severe and enduring mental health problems. Following a discussion of the problems and possibilities of golf as a form of physical activity for this group, we outline the structure, organisation, and ethos of the golf programme. Through an analysis of qualitative case study data collected during the programme, we discuss the response to the programme from service users and mental health professionals. We conclude by highlighting aspects of the programme which were critical to its success and offering suggestions for further initiatives in this area

Milk: the new sports drink? A Review

There has been growing interest in the potential use of bovine milk as an exercise beverage, especially during recovery from resistance training and endurance sports. Based on the limited research, milk appears to be an effective post-resistance exercise beverage that results in favourable acute alterations in protein metabolism. Milk consumption acutely increases muscle protein synthesis, leading to an improved net muscle protein balance. Furthermore, when post-exercise milk consumption is combined with resistance training (12 weeks minimum), greater increases in muscle hypertrophy and lean mass have been observed. Although research with milk is limited, there is some evidence to suggest that milk may be an effective post-exercise beverage for endurance activities. Low-fat milk has been shown to be as effective, if not more effective, than commercially available sports drinks as a rehydration beverage. Milk represents a more nutrient dense beverage choice for individuals who partake in strength and endurance activities, compared to traditional sports drinks. Bovine low-fat fluid milk is a safe and effective post exercise beverage for most individuals, except for those who are lactose intolerant. Further research is warranted to better delineate the possible applications and efficacy of bovine milk in the field of sports nutrition

Using item response theory to explore the psychometric properties of extended matching questions examination in undergraduate medical education

BACKGROUND: As assessment has been shown to direct learning, it is critical that the examinations developed to test clinical competence in medical undergraduates are valid and reliable. The use of extended matching questions (EMQ) has been advocated to overcome some of the criticisms of using multiple-choice questions to test factual and applied knowledge. METHODS: We analysed the results from the Extended Matching Questions Examination taken by 4th year undergraduate medical students in the academic year 2001 to 2002. Rasch analysis was used to examine whether the set of questions used in the examination mapped on to a unidimensional scale, the degree of difficulty of questions within and between the various medical and surgical specialties and the pattern of responses within individual questions to assess the impact of the distractor options. RESULTS: Analysis of a subset of items and of the full examination demonstrated internal construct validity and the absence of bias on the majority of questions. Three main patterns of response selection were identified. CONCLUSION: Modern psychometric methods based upon the work of Rasch provide a useful approach to the calibration and analysis of EMQ undergraduate medical assessments. The approach allows for a formal test of the unidimensionality of the questions and thus the validity of the summed score. Given the metric calibration which follows fit to the model, it also allows for the establishment of items banks to facilitate continuity and equity in exam standards

Cross modal perception of body size in domestic dogs (Canis familiaris)

While the perception of size-related acoustic variation in animal vocalisations is well documented, little attention has been given to how this information might be integrated with corresponding visual information. Using a cross-modal design, we tested the ability of domestic dogs to match growls resynthesised to be typical of either a large or a small dog to size- matched models. Subjects looked at the size-matched model significantly more often and for a significantly longer duration than at the incorrect model, showing that they have the ability to relate information about body size from the acoustic domain to the appropriate visual category. Our study suggests that the perceptual and cognitive mechanisms at the basis of size assessment in mammals have a multisensory nature, and calls for further investigations of the multimodal processing of size information across animal species

Pedestrian, Crowd, and Evacuation Dynamics

This contribution describes efforts to model the behavior of individual pedestrians and their interactions in crowds, which generate certain kinds of self-organized patterns of motion. Moreover, this article focusses on the dynamics of crowds in panic or evacuation situations, methods to optimize building designs for egress, and factors potentially causing the breakdown of orderly motion.Comment: This is a review paper. For related work see http://www.soms.ethz.c

Validation of the SCID-hu Thy/Liv mouse model with four classes of licensed antiretrovirals.

BackgroundThe SCID-hu Thy/Liv mouse model of HIV-1 infection is a useful platform for the preclinical evaluation of antiviral efficacy in vivo. We performed this study to validate the model with representatives of all four classes of licensed antiretrovirals.Methodology/principal findingsEndpoint analyses for quantification of Thy/Liv implant viral load included ELISA for cell-associated p24, branched DNA assay for HIV-1 RNA, and detection of infected thymocytes by intracellular staining for Gag-p24. Antiviral protection from HIV-1-mediated thymocyte depletion was assessed by multicolor flow cytometric analysis of thymocyte subpopulations based on surface expression of CD3, CD4, and CD8. These mice can be productively infected with molecular clones of HIV-1 (e.g., the X4 clone NL4-3) as well as with primary R5 and R5X4 isolates. To determine whether results in this model are concordant with those found in humans, we performed direct comparisons of two drugs in the same class, each of which has known potency and dosing levels in humans. Here we show that second-generation antiretrovirals were, as expected, more potent than their first-generation predecessors: emtricitabine was more potent than lamivudine, efavirenz was more potent than nevirapine, and atazanavir was more potent than indinavir. After interspecies pharmacodynamic scaling, the dose ranges found to inhibit viral replication in the SCID-hu Thy/Liv mouse were similar to those used in humans. Moreover, HIV-1 replication in these mice was genetically stable; treatment of the mice with lamivudine did not result in the M184V substitution in reverse transcriptase, and the multidrug-resistant NY index case HIV-1 retained its drug-resistance substitutions.ConclusionGiven the fidelity of such comparisons, we conclude that this highly reproducible mouse model is likely to predict clinical antiviral efficacy in humans

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies