Modelling of errors in databases

A lot of time and energy are expended assembling national databases containing information about health care processes and outcomes. Unfortunately, given the complexity of the data gathering procedures involved, errors occur. This inevitably leads to problems when it comes to the analysis of data from such sources. Indeed, sometimes it is very much a matter of faith that summary statistics represent a true reflection of the facts. On the assumption that one knows the rates at which different forms of errors occur, mathematical modelling methods can be used to obtain estimates of the effects of such errors on the estimates that would be derived for summary statistics associated with an erroneous data base

Can the Heinrich ratio be used to predict harm from medication errors?

The purpose of this study was to establish whether, for medication errors, there exists a fixed Heinrich ratio between the number of incidents which did not result in harm, the number that caused minor harm, and the number that caused serious harm. If this were the case then it would be very useful in estimating any changes in harm following an intervention. Serious harm resulting from medication errors is relatively rare, so it can take a great deal of time and resource to detect a significant change. If the Heinrich ratio exists for medication errors, then it would be possible, and far easier, to measure the much more frequent number of incidents that did not result in harm and the extent to which they changed following an intervention; any reduction in harm could be extrapolated from this

Preliminary basic performance analysis of the Cedar multiprocessor memory system

Some preliminary basic results on the performance of the Cedar multiprocessor memory system are presented. Empirical results are presented and used to calibrate a memory system simulator which is then used to discuss the scalability of the system

Incidence and viral aetiologies of acute respiratory illnesses (ARIs) in the United States: a population-based study.

We conducted prospective, community-wide surveillance for acute respiratory illnesses (ARIs) in Rochester, NY and Marshfield, WI during a 3-month period in winter 2011. We estimated the incidence of ARIs in each community, tested for viruses, and determined the proportion of ARIs associated with healthcare visits. We used a rolling cross-sectional design to sample participants, conducted telephone interviews to assess ARI symptoms (defined as a current illness with feverishness or cough within the past 7 days), collected nasal/throat swabs to identify viruses, and extracted healthcare utilization from outpatient/inpatient records. Of 6492 individuals, 321 reported an ARI within 7 days (4·9% total, 5·7% in Rochester, 4·4% in Marshfield); swabs were collected from 208 subjects. The cumulative ARI incidence for the entire 3-month period was 52% in Rochester [95% confidence interval (CI) 42-63] and 35% in Marshfield (95% CI 28-42). A specific virus was identified in 39% of specimens: human coronavirus (13% of samples), rhinovirus (12%), RSV (7%), influenza virus (4%), human metapneumovirus (4%), and adenovirus (1%). Only 39/200 (20%) had a healthcare visit (2/9 individuals with influenza). ARI incidence was ~5% per week during winter

The Quantized O(1,2)/O(2)×Z2O(1,2)/O(2)\times Z_2 Sigma Model Has No Continuum Limit in Four Dimensions. I. Theoretical Framework

The nonlinear sigma model for which the field takes its values in the coset space $O(1,2)/O(2)\times Z_2$ is similar to quantum gravity in being perturbatively nonrenormalizable and having a noncompact curved configuration space. It is therefore a good model for testing nonperturbative methods that may be useful in quantum gravity, especially methods based on lattice field theory. In this paper we develop the theoretical framework necessary for recognizing and studying a consistent nonperturbative quantum field theory of the $O(1,2)/O(2)\times Z_2$ model. We describe the action, the geometry of the configuration space, the conserved Noether currents, and the current algebra, and we construct a version of the Ward-Slavnov identity that makes it easy to switch from a given field to a nonlinearly related one. Renormalization of the model is defined via the effective action and via current algebra. The two definitions are shown to be equivalent. In a companion paper we develop a lattice formulation of the theory that is particularly well suited to the sigma model, and we report the results of Monte Carlo simulations of this lattice model. These simulations indicate that as the lattice cutoff is removed the theory becomes that of a pair of massless free fields. Because the geometry and symmetries of these fields differ from those of the original model we conclude that a continuum limit of the $O(1,2)/O(2)\times Z_2$ model which preserves these properties does not exist.Comment: 25 pages, no figure

Interpolatory methods for H∞\mathcal{H}_\infty model reduction of multi-input/multi-output systems

We develop here a computationally effective approach for producing high-quality $\mathcal{H}_\infty$-approximations to large scale linear dynamical systems having multiple inputs and multiple outputs (MIMO). We extend an approach for $\mathcal{H}_\infty$ model reduction introduced by Flagg, Beattie, and Gugercin for the single-input/single-output (SISO) setting, which combined ideas originating in interpolatory $\mathcal{H}_2$-optimal model reduction with complex Chebyshev approximation. Retaining this framework, our approach to the MIMO problem has its principal computational cost dominated by (sparse) linear solves, and so it can remain an effective strategy in many large-scale settings. We are able to avoid computationally demanding $\mathcal{H}_\infty$ norm calculations that are normally required to monitor progress within each optimization cycle through the use of "data-driven" rational approximations that are built upon previously computed function samples. Numerical examples are included that illustrate our approach. We produce high fidelity reduced models having consistently better $\mathcal{H}_\infty$ performance than models produced via balanced truncation; these models often are as good as (and occasionally better than) models produced using optimal Hankel norm approximation as well. In all cases considered, the method described here produces reduced models at far lower cost than is possible with either balanced truncation or optimal Hankel norm approximation

Neural representation of geometry and surface properties in object and scene perception

Multiple cortical regions are crucial for perceiving the visual world, yet the processes shaping representations in these regions are unclear. To address this issue, we must elucidate how perceptual features shape representations of the environment. Here, we explore how the weighting of different visual features affects neural representations of objects and scenes, focusing on the scene-selective parahippocampal place area (PPA), but additionally including the retrosplenial complex (RSC), occipital place area (OPA), lateral occipital (LO) area, fusiform face area (FFA) and occipital face area (OFA). Across three experiments, we examined functional magnetic resonance imaging (fMRI) activity while human observers viewed scenes and objects that varied in geometry (shape/layout) and surface properties (texture/material). Interestingly, we found equal sensitivity in the PPA for these properties within a scene, revealing that spatial-selectivity alone does not drive activation within this cortical region. We also observed sensitivity to object texture in PPA, but not to the same degree as scene texture, and representations in PPA varied when objects were placed within scenes. We conclude that PPA may process surface properties in a domain-specific manner, and that the processing of scene texture and geometry is equally-weighted in PPA and may be mediated by similar underlying neuronal mechanisms

Measuring organisational readiness for patient engagement (MORE) : an international online Delphi consensus study

Date of Acceptance: 28/01/2015. © 2015 Oostendorp et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise statedWidespread implementation of patient engagement by organisations and clinical teams is not a reality yet. The aim of this study is to develop a measure of organisational readiness for patient engagement designed to monitor and facilitate a healthcare organisation’s willingness and ability to effectively implement patient engagement in healthcarePeer reviewedFinal Published versio

Probing the role of the cation–π interaction in the binding sites of GPCRs using unnatural amino acids

We describe a general application of the nonsense suppression methodology for unnatural amino acid incorporation to probe drug–receptor interactions in functional G protein-coupled receptors (GPCRs), evaluating the binding sites of both the M2 muscarinic acetylcholine receptor and the D2 dopamine receptor. Receptors were expressed in Xenopus oocytes, and activation of a G protein-coupled, inward-rectifying K^+ channel (GIRK) provided, after optimization of conditions, a quantitative readout of receptor function. A number of aromatic amino acids thought to be near the agonist-binding site were evaluated. Incorporation of a series of fluorinated tryptophan derivatives at W6.48 of the D2 receptor establishes a cation–π interaction between the agonist dopamine and W6.48, suggesting a reorientation of W6.48 on agonist binding, consistent with proposed “rotamer switch” models. Interestingly, no comparable cation–π interaction was found at the aligning residue in the M2 receptor