How do clinicians reconcile conditions and medications? The cognitive context of medication reconciliation

Medication omissions and dosing failures are frequent during transitions in patient care. Medication reconciliation (MR) requires bridging discrepancies in a patient’s medical history as a setting for care changes. MR has been identified as vulnerable to failure, and a clinician’s cognition during MR remains poorly described in the literature. We sought to explore cognition in MR tasks. Specifically, we sought to explore how clinicians make sense of conditions and medications. We observed 24 anesthesia providers performing a card-sorting task to sort conditions and medications for a fictional patient. We analyzed the spatial properties of the data using statistical methods. Most of the participants (58%) arranged the medications along a straight line (p < 0.001). They sorted medications by organ systems (Friedman’s χ ²(54) = 325.7, p < 0.001). These arrangements described the clinical correspondence between each two medications (Wilcoxon W = 192.0, p < 0.001). A cluster analysis showed that the subjects matched conditions and medications related to the same organ system together (Wilcoxon W = 1917.0, p < 0.001). We conclude that the clinicians commonly arranged the information into two groups (conditions and medications) and assigned an internal order within these groups, according to organ systems. They also matched between conditions and medications according to similar criteria. These findings were also supported by verbal protocol analysis. The findings strengthen the argument that organ-based information is pivotal to a clinician’s cognition during MR. Understanding the strategies and heuristics, clinicians employ through the MR process may help to develop practices to promote patient safety.     

Heuristic approach to network database external parameters design

One of the most important issues in any database design is the optimization of its performance. The external database parameters play one of the main roles in a network database performance considerations. The analytic and the simulative approaches to establish these parameters are discussed. An heuristic approach using system simulation method to find the optimal database external parameters is developed and compared with the analytic one. The software system to implement the simulation methodology is presented. This system has been successfully implemented with the VAX-11 DBMS.     

A smart process controller framework for Industry 4.0 settings

This paper presents a smart supervisory framework for a single process controller, designed for Industry 4.0 shop floors. This digitization of a full supervisory suite for a single process controller enables self-awareness, self-diagnosis, self-prognosis, and self-healing (by definition, these "self" elements are missing from other supervisory frameworks diagnosing numerous controllers in parallel). The proposed framework is aligned with the concept of a Cyber Physical System (CPS), since its implementation generates a rich cyber physical entity of the controlled process. This CPS entity can either be considered as the process digital twin, or can provide a solid basis for generating it. Finally, the framework includes the main characteristics of Industry 4.0, such as advanced use of Artificial Intelligence (AI) and big data analysis. The framework is based on four modules: (1) Control and Awareness module—performing both continuous process control and adjustments, as well as machine learning (ML) and statistical process control (SPC) for identifying abnormalities that require further diagnosis; (2) Process -diagnosis module—performing continual (recurrent) analysis of the process state and trends; (3) Prognosis and Healing module—performing prognosis and automated intervention via parameter changes, re-configurations, and automated maintenance; (4) External Interaction Platform—an interactive module for interfacing with experts, presenting them with the process analysis information and obtaining feedback from them as part of a learning process. Using an implementation showcase to illustrate the methodological framework’s applicability, we demonstrate its real-world potential. The proposed framework could serve as a guide for implementing smart process control and maintenance systems in Industry 4.0 shop floors. It could also provide a firm basis for comparison with future suggested frameworks. Future research directions could include pursuing improvements to the proposed process control framework and validating the framework by case studies of its implementation.

     

<Emphasis Type="Italic">k</Emphasis>-Outerplanar Graphs,Planar Duality,and Low Stretch Spanning Trees

Low distortion probabilistic embedding of graphs into approximating trees is an extensively studied topic. Of particular interest is the case where the approximating trees are required to be (subgraph) spanning trees of the given graph (or multigraph), in which case, the focus is usually on the equivalent problem of finding a (single) tree with low average stretch. Among the classes of graphs that received special attention in this context are k-outerplanar graphs (for a fixed k): Chekuri, Gupta, Newman, Rabinovich, and Sinclair show that every k-outerplanar graph can be probabilistically embedded into approximating trees with constant distortion regardless of the size of the graph. The approximating trees in the technique of Chekuri et al. are not necessarily spanning trees, though.     

Perpendicular Orientation of Anisotropic Au‐Tipped CdS Nanorods at the Air/Water Interface

Anisotropic CdS nanorods tipped by Au nanoparticles on one edge (Au‐CdS‐NRs) are perpendicularly oriented at the air/water interface, whereby all the Au tips are located in the subphase, using the Langmuir–Blodgett technique. Since these nano‐objects reveal light‐induced charge separation at the semiconductor/metal interface, it is of high interest to control their organization. The orientation of these assemblies is studied in situ while compressing the Langmuir–Blodgett trough using the π‐A isotherm, Brewster angle microscopy, and horizontal touch voltammetry. All these analyses clearly confirm the induced organization of the amphiphilic Au‐CdS‐NRs by compression of the Langmuir layer. The compressed layers are successfully transferred by the Langmuir–Schaefer method onto transmission electron microscopy grids while maintaining the preferential orientation as analyzed by transmission, scanning and scanning trasmission electron microscopy, and X‐ray photoelectron spectroscopy. As far as can be determined, the Langmuir–Blodgett technique has not been used so far for perpendicularly orienting anisotropic nano‐objects. Moreover, these findings clearly demonstrate that anisotropic amphiphilic nano‐objects can be treated with some similarity to the traditional amphiphilic molecular building blocks.     

Simulation of Microwave Sintering of Ceramic Bodies with Complex Geometry

Microwave sintering, an emerging technology in which the energy is applied directly to the material, enabling rapid sintering, shows potential for the synthesis of advanced ceramic materials with superior properties. The process is complex, combining the propagation and absorption of electromagnetic waves in the ceramic material, heat transport within the geometric body, and densification. The densification changes both macroscopic shape and microstructural morphology. A dynamic balance between the rate of electromagnetic energy absorbed within the bulk of the sample and the rate of energy loss from its surface generally results in temperature gradients. These temperature gradients may be especially important during the microwave sintering of bodies with a complex geometry, because neither the diffusion distance nor the electromagnetic penetration depth scale with sample dimensions. The gradients generated in a ZnO green body of a complex geometry were studied theoretically using various microwave-sintering approaches, and it was found that (1) dual-frequency (2.45 and 30 GHz) microwave processing leads to a decrease in the duration of the temperature gradients, and (2) an increase in the heating rate from 5°C/min to 1400°C/min at 2.45 GHz decreases the total required microwave energy by a factor of 55, while at the same time the internal temperature gradients are maintained over a substantially shorter time.