SIMULATION: Transactions of The Society for Modeling and Simulation International

Jin, Haizhe; Xiao, Zhibin; Yao, Junhan; Gong, Zibo; Wang, Haiying; Zhao, Yinan

doi: 10.1177/00375497231168631pmid: N/A

Medication administration errors account for a relatively high proportion of medical errors, with more than 50% occurring at the nursing administration stage. Nursing is characterized by a large amount of work, rigid working hours, high information cognitive intensity, and frequent information updates. The high workload of nurses is a significant cause of medication administration errors. In this study, a literature analysis was used to determine the elements of the system dynamics model, and the causal loop diagram was used to draw the relationship framework among the elements. Vensim personal learning edition and interview surveys were then used for model validation and simulation. First, 302 case analyses of medication administration errors collected from the three metropolitan area hospitals were used to construct the causal loop diagram, the stock and flow map of the medication administration error system, and the dynamics model; second, the model was tested from theoretical and historical data simulation perspectives; finally, the system dynamics model proposed in this study was used to simulate a medical institution from overtime and policy perspectives. Through system dynamics modeling, the inducing mechanism of workload on medication administration errors in nursing operations was elucidated, and corresponding suggestions for prevention were provided. In addition, ideas and basis for optimizing the medication administration process, improving workload, and preventing medication administration errors considering workload were provided.

Yhdego, Haben; Kidane, Nahom; Mckenzie, Frederick; Audette, Michel

doi: 10.1177/00375497231165049pmid: N/A

Cardiac auscultation (CA), the act of listening to the heart’s sound, is a critical skill that provides valuable information for identifying serious heart diseases. Proficiency in cardiac auscultation requires repeated stethoscope practice and experience in identifying abnormal or irregular cardiac rhythms. However, nowadays, most hospital admissions are short and intensely focused, with fewer opportunities for medical trainees to learn and practice bedside examination skills. It is common practice in many institutions to incorporate standardized patients (SPs) into CA training because these actors are able to represent the patient and convey the symptoms. However, SPs are typically healthy individuals, limiting the kinds of abnormalities that students can hear. In this work, we develop a novel real-time simulation-based method for virtual pathology stethoscope (VPS) detection. The VPS system uses augmented reality (AR) to teach medical students how to perform cardiac examinations by listening to abnormal heart sounds in SPs who are otherwise healthy. A digital stethoscope with two electrodes on the chest piece collects electrocardiogram (ECG) signal data sets from SPs at the four primary auscultation sites. Next, different deep-learning methods are evaluated for classifying the location of the stethoscope by taking advantage of subtle differences in the ECG signals. This study would significantly extend the simulation capabilities of SPs by allowing medical students and trainees to perform realistic CA and hear CA in a clinical environment.

Peng, Shanbi; Luo, Xue; Yu, Bin; Huang, Li; Liu, Enbin

doi: 10.1177/00375497231168628pmid: N/A

Negative pressure wards are significant in preventing the spread of infectious pathogens which play a crucial role in fighting against COVID-19. Owing to the negative pressure, contaminated air with pathogens is not able to flow from the wards to non-contaminated zones while fresh filtered air will be transported to the ward via the ventilation system. As airflow controlled by ventilation systems affects the motion of pathogens, for example, infectious aerosol particles, the ability of a negative pressure ward to reduce the risk of infection highly relies on an effective ventilation system. In this investigation, impacts of airflow patterns under various human postures and ventilation processes aerosols diffusion are analyzed via the computational fluid dynamics (CFD) simulation. According to the results, among three airflow patterns, the highest contaminant removal efficiency is 57% at 200 s with the top supply and bottom return mode; besides, in three postures, in the case that the patient is in a standing position, the contaminant removal efficiency is the highest. Furthermore, it is found that the best airflow scheme is a slit tuyere in the ward, with a top supply and side return mode and a sitting position for the patient. This study may provide a reference for the design of airflow in negative pressure isolation wards, control of contaminants, and prevention of viral infections, so as to ensure a good working and recovery environment for medical staff and patients.

Tengesdal, Njål Kjærnes; Fotland, Gaute; Holden, Christian; Haugen, Bjørn

doi: 10.1177/00375497231175927pmid: N/A

Simple and computationally efficient drill string models running real-time describing motion in all axes in directional wells are important for the implementation of closed-loop control and assisted monitoring during drilling operations. This paper proposes a new simplified three-dimensional model based on a parametric curve and lumped-parameter modeling, where Kane’s method is used to establish the equations of motion. Validation of the steady-state motion and convergence for the lumped model in vertical and horizontal alignment was compared with a finite-element model. The configuration and restoring forces show good results compared with finite-element analysis. Hence, the model demonstrate the axial contraction as a function of the body restoring forces being oriented to the inertial frame, inherently producing nonlinear coupled axial tension forces. The qualitative response of the model is confirmed in simulation case studies, being showcased by a deviated J-well configuration. Traveling block velocity and top drive torque are included as actuated inputs to analyze off-bottom friction and contact along the wellbore. The model is proposed to act as a virtual sensor for drilling directional wells.

Yuan, Xiao-Ting; Tang, Tie-Qiao; Chen, Liang; Wang, Tao

doi: 10.1177/00375497231161146pmid: N/A

A cellular automaton (CA) model with a finer discretization of space is proposed to simulate a non-emergency evacuation process in a room with an obstacle. During the evacuation process, a triangle “evading region” phenomenon has been observed through simulation and experiment on the upstream side of the spatial obstacle. In this paper, we use a simple method to generate an obstacle floor field corresponding to the triangle. We investigate the relationship between the pedestrian trajectories and the obstacle’s position. We also study the effect of the obstacle on evacuation time and average evacuation speed. Our study provides insights into the simulation of obstacle avoidance behavior of pedestrians in simple scenarios.

Hu, Bin; Du, Yuxiao

doi: 10.1177/00375497231171138pmid: N/A

Nowadays, the introduction of digital technology improves the condition of the workplace and employees’ productivity, but the unstable behavior of employees is still typical in Internet enterprises in China. Sometimes, employees frequently show their behavior reversals between cooperation and conflict. An integrated analysis method with three steps is performed to explore its reason. First, an evolutionary game model is employed to examine the strategies of individual employee’s behavior selection between cooperation and conflict. Second, the cellular automata are developed to simulate the evolution of employee group behavior selection over time. The frequent behavior turnovers between cooperation and conflict are illustrated. Third, catastrophe theory and method are used to identify the hidden cusp catastrophe patterns under the evolution of group behavior selection. Research results reveal that individual employee selects cooperation if the penalty exceeds half the cost. Simulation results show intense and sudden changes in employee group behavior selection, in which cusp catastrophe patterns exist. The cusp catastrophe model can intuitively interpret the mechanism by which factors, such as average perceived payoff and proportion of cooperation employees, influence the behavior state of the employee group. The mechanism of catastrophe in frequent behavior turnover is explored. This methodology, which is based on the theoretical framework of social exchange theory, integrates evolutionary game theory, simulation, and catastrophe theory to identify the catastrophe mechanism in behavior turnover and make theoretical and practical contributions to behavior selection research.