Medication errors in a swiss cardiovascular surgery department: a cross-sectional study based on a novel medication error report method

The purpose of this study was (1) to determine frequency and type of medication errors (MEs), (2) to assess the number of MEs prevented by registered nurses, (3) to assess the consequences of ME for patients, and (4) to compare the number of MEs reported by a newly developed medication error self-reporting tool to the number reported by the traditional incident reporting system. We conducted a cross-sectional study on ME in the Cardiovascular Surgery Department of Bern University Hospital in Switzerland. Eligible registered nurses (n = 119) involving in the medication process were included. Data on ME were collected using an investigator-developed medication error self reporting tool (MESRT) that asked about the occurrence and characteristics of ME. Registered nurses were instructed to complete a MESRT at the end of each shift even if there was no ME. All MESRTs were completed anonymously. During the one-month study period, a total of 987 MESRTs were returned. Of the 987 completed MESRTs, 288 (29%) indicated that there had been an ME. Registered nurses reported preventing 49 (5%) MEs. Overall, eight (2.8%) MEs had patient consequences. The high response rate suggests that this new method may be a very effective approach to detect, report, and describe ME in hospitals.

The influence of intention on masked priming: A study with semantic classification of words

Unconscious perception is commonly described as a phenomenon that is not under intentional control and relies on automatic processes. We challenge this view by arguing that some automatic processes may indeed be under intentional control, which is implemented in task-sets that define how the task is to be performed. In consequence, those prime attributes that are relevant to the task will be most effective. To investigate this hypothesis, we used a paradigm which has been shown to yield reliable short-lived priming in tasks based on semantic classification of words. This type of study uses fast, well practised classification responses, whereby responses to targets are much less accurate if prime and target belong to a different category than if they belong to the same category. In three experiments, we investigated whether the intention to classify the same words with respect to different semantic categories had a differential effect on priming. The results suggest that this was indeed the case: Priming varied with the task in all experiments. However, although participants reported not seeing the primes, they were able to classify the primes better than chance using the classification task they had used before with the targets. When a lexical task was used for discrimination in experiment 4, masked primes could however not be discriminated. Also, priming was as pronounced when the primes were visible as when they were invisible. The pattern of results suggests that participants had intentional control on prime processing, even if they reported not seeing the primes.

Sex Differences in Semantic Processing: Event-Related Brain Potentials Distinguish between Lower and Higher Order Semantic Analysis during Word Reading

Behavioral studies suggest that women and men differ in the strategic elaboration of verbally encoded information especially in the absence of external task demand. However, measuring such covert processing requires other than behavioral data. The present study used event-related potentials to compare sexes in lower and higher order semantic processing during the passive reading of semantically related and unrelated word pairs. Women and men showed the same early context effect in the P1-N1 transition period. This finding indicates that the initial lexical-semantic access is similar in men and women. In contrast, sexes differed in higher order semantic processing. Women showed an earlier and longer lasting context effect in the N400 accompanied by larger signal strength in temporal networks similarly recruited by men and women. The results suggest that women spontaneously conduct a deeper semantic analysis. This leads to faster processing of related words in the active neural networks as reflected in a shorter stability of the N400 map in women. Taken together, the findings demonstrate that there is a selective sex difference in the controlled semantic analysis during passive word reading that is not reflected in different functional organization but in the depth of processing.

Patterns of regional brain hypometabolism associated with knowledge of semantic features and categories in Alzheimer's disease

The study of semantic memory in patients with Alzheimer's disease (AD) has raised important questions about the representation of conceptual knowledge in the human brain. It is still unknown whether semantic memory impairments are caused by localized damage to specialized regions or by diffuse damage to distributed representations within nonspecialized brain areas. To our knowledge, there have been no direct correlations of neuroimaging of in vivo brain function in AD with performance on tasks differentially addressing visual and functional knowledge of living and nonliving concepts. We used a semantic verification task and resting 18-fluorodeoxyglucose positron emission tomography in a group of mild to moderate AD patients to investigate this issue. The four task conditions required semantic knowledge of (1) visual, (2) functional properties of living objects, and (3) visual or (4) functional properties of nonliving objects. Visual property verification of living objects was significantly correlated with left posterior fusiform gyrus metabolism (Brodmann's area [BA] 37/19). Effects of visual and functional property verification for non-living objects largely overlapped in the left anterior temporal (BA 38/20) and bilateral premotor areas (BA 6), with the visual condition extending more into left lateral precentral areas. There were no associations with functional property verification for living concepts. Our results provide strong support for anatomically separable representations of living and nonliving concepts, as well as visual feature knowledge of living objects, and against distributed accounts of semantic memory that view visual and functional features of living and nonliving objects as distributed across a common set of brain areas.

Dosimetric impact of geometric errors due to respiratory motion prediction on dynamic multileaf collimator-based four-dimensional radiation delivery

The synchronization of dynamic multileaf collimator (DMLC) response with respiratory motion is critical to ensure the accuracy of DMLC-based four dimensional (4D) radiation delivery. In practice, however, a finite time delay (response time) between the acquisition of tumor position and multileaf collimator response necessitates predictive models of respiratory tumor motion to synchronize radiation delivery. Predicting a complex process such as respiratory motion introduces geometric errors, which have been reported in several publications. However, the dosimetric effect of such errors on 4D radiation delivery has not yet been investigated. Thus, our aim in this work was to quantify the dosimetric effects of geometric error due to prediction under several different conditions. Conformal and intensity modulated radiation therapy (IMRT) plans for a lung patient were generated for anterior-posterior/posterior-anterior (AP/PA) beam arrangements at 6 and 18 MV energies to provide planned dose distributions. Respiratory motion data was obtained from 60 diaphragm-motion fluoroscopy recordings from five patients. A linear adaptive filter was employed to predict the tumor position. The geometric error of prediction was defined as the absolute difference between predicted and actual positions at each diaphragm position. Distributions of geometric error of prediction were obtained for all of the respiratory motion data. Planned dose distributions were then convolved with distributions for the geometric error of prediction to obtain convolved dose distributions. The dosimetric effect of such geometric errors was determined as a function of several variables: response time (0-0.6 s), beam energy (6/18 MV), treatment delivery (3D/4D), treatment type (conformal/IMRT), beam direction (AP/PA), and breathing training type (free breathing/audio instruction/visual feedback). Dose difference and distance-to-agreement analysis was employed to quantify results. Based on our data, the dosimetric impact of prediction (a) increased with response time, (b) was larger for 3D radiation therapy as compared with 4D radiation therapy, (c) was relatively insensitive to change in beam energy and beam direction, (d) was greater for IMRT distributions as compared with conformal distributions, (e) was smaller than the dosimetric impact of latency, and (f) was greatest for respiration motion with audio instructions, followed by visual feedback and free breathing. Geometric errors of prediction that occur during 4D radiation delivery introduce dosimetric errors that are dependent on several factors, such as response time, treatment-delivery type, and beam energy. Even for relatively small response times of 0.6 s into the future, dosimetric errors due to prediction could approach delivery errors when respiratory motion is not accounted for at all. To reduce the dosimetric impact, better predictive models and/or shorter response times are required.

Climate spectrum estimation in the presence of timescale errors

We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistence estimation. The timescale errors are modelled parametrically and included in the simulations for determining (1) the upper levels of the spectrum of the red-noise AR(1) alternative and (2) the uncertainty of the frequency of a spectral peak. Application of REDFITmc2 to ice core and stalagmite records of palaeoclimate allowed a more realistic evaluation of spectral peaks than when ignoring this source of uncertainty. The results support qualitatively the intuition that stronger effects on the spectrum estimate (decreased detectability and increased frequency uncertainty) occur for higher frequencies. The surplus information brought by algorithm REDFITmc2 is that those effects are quantified. Regarding timescale construction, not only the fixpoints, dating errors and the functional form of the age-depth model play a role. Also the joint distribution of all time points (serial correlation, stratigraphic order) determines spectrum estimation.

Enterprise Integration of Smart Objects using Semantic Service Descriptions

Integrating physical objects (smart objects) and enterprise IT systems is still a labor intensive, mainly manual task done by domain experts. On one hand, enterprise IT backend systems are based on service oriented architectures (SOA) and driven by business rule engines or business process execution engines. Smart objects on the other hand are often programmed at very low levels. In this paper we describe an approach that makes the integration of smart objects with such backends systems easier. We introduce semantic endpoint descriptions based on Linked USDL. Furthermore, we show how different communication patterns can be integrated into these endpoint descriptions. The strength of our endpoint descriptions is that they can be used to automatically create REST or SOAP endpoints for enterprise systems, even if which they are not able to talk to the smart objects directly. We evaluate our proposed solution with CoAP, UDP and 6LoWPAN, as we anticipate the industry converge towards these standards. Nonetheless, our approach also allows easy integration with backend systems, even if no standardized protocol is used.