Simulated Clinical Environment Research Articles

A national pilot study on simulation-based upstander training for emergency medicine clinicians.

This study assesses the effectiveness of clinical simulation-based training in boosting self-perceived confidence for using upstander communication skills to confront racism, discrimination, and microaggressions (RDM). We conducted an observational cohort study with emergency medicine professionals at the 2023 Scientific Assembly of the American Academy of Emergency Medicine in New Orleans, Louisiana. The study featured a clinical simulation-based training on upstander communications skills session followed by small- and large-group debriefs. Participants completed pre- and post-training questionnaires assessing demographics and confidence in health equity competencies. This survey was used in a previous study with emergency medicine residents. Data were analyzed using an independent Student's t-test, with a significance threshold of 0.05. Thirty-two individuals participated in the simulation-based training, and 24 completed surveys, with a 75% response rate. Most participants were non-Hispanic (24, 85.7%) and women (18, 64%), with racial demographics mostly White (8, 28.6%), Black or African American (8, 28.6%), and Asian (6, 21.4%). After the workshop, there was a notable increase in self-perceived ability and confidence in identifying RDM (from 7 ± 3.2 to 8.6 ± 1.6, p < 0.003), using upstander communication tools (from 6.1 ± 3.5 to 8.5 ± 1, p < 0.0001), and the likelihood of intervening in RDM situations (from 7.1 ± 3.3 to 8.8 ± 1.1, p < 0.0002). The clinical simulation-based training significantly improved participants' confidence and self-perceived ability to address RDM in simulated clinical environments. This training method is a promising tool for teaching health equity topics in clinical medicine.

Evaluation of the Parkinson's Remote Interactive Monitoring System in a Clinical Setting: Usability Study.

The fastest-growing neurological disorder is Parkinson disease (PD), a progressive neurodegenerative disease that affects 10 million people worldwide. PD is typically treated with levodopa, an oral pill taken to increase dopamine levels, and other dopaminergic agonists. As the disease advances, the efficacy of the drug diminishes, necessitating adjustments in treatment dosage according to the patient's symptoms and disease progression. Therefore, remote monitoring systems that can provide more detailed and accurate information on a patient's condition regularly are a valuable tool for clinicians and patients to manage their medication. The Parkinson's Remote Interactive Monitoring System (PRIMS), developed by PragmaClin Research Inc, was designed on the premise that it will be an easy-to-use digital system that can accurately capture motor and nonmotor symptoms of PD remotely. We performed a usability evaluation in a simulated clinical environment to assess the ease of use of the PRIMS and determine whether the product offers suitable functionality for users in a clinical setting. Participants were recruited from a user sign-up web-based database owned by PragmaClin Research Inc. A total of 11 participants were included in the study based on the following criteria: (1) being diagnosed with PD and (2) not being diagnosed with dementia or any other comorbidities that would make it difficult to complete the PRIMS assessment safely and independently. Patient users completed a questionnaire that is based on the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale. Interviews and field notes were analyzed for underlying themes and topics. In total, 11 people with PD participated in the study (female individuals: n=5, 45%; male individuals: n=6, 55%; age: mean 66.7, SD 7.77 years). Thematic analysis of the observer's notes revealed 6 central usability issues associated with the PRIMS. These were the following: (1) the automated voice prompts are confusing, (2) the small camera is problematic, (3) the motor test exhibits excessive sensitivity to the participant's orientation and position in relation to the cameras, (4) the system poses mobility challenges, (5) navigating the system is difficult, and (6) the motor test exhibits inconsistencies and technical issues. Thematic analysis of qualitative interview responses revealed four central themes associated with participants' perspectives and opinions on the PRIMS, which were (1) admiration of purpose, (2) excessive system sensitivity, (3) video instructions preferred, and (4) written instructions disliked. The average system usability score was calculated to be 69.2 (SD 4.92), which failed to meet the acceptable system usability score of 70. Although multiple areas of improvement were identified, most of the participants showed an affinity for the overarching objective of the PRIMS. This feedback is being used to upgrade the current PRIMS so that it aligns more with patients' needs.

Leveraging Large Language Models for Improved Patient Access and Self-Management: Assessor-Blinded Comparison Between Expert- and AI-Generated Content.

While large language models (LLMs) such as ChatGPT and Google Bard have shown significant promise in various fields, their broader impact on enhancing patient health care access and quality, particularly in specialized domains such as oral health, requires comprehensive evaluation. This study aims to assess the effectiveness of Google Bard, ChatGPT-3.5, and ChatGPT-4 in offering recommendations for common oral health issues, benchmarked against responses from human dental experts. This comparative analysis used 40 questions derived from patient surveys on prevalent oral diseases, which were executed in a simulated clinical environment. Responses, obtained from both human experts and LLMs, were subject to a blinded evaluation process by experienced dentists and lay users, focusing on readability, appropriateness, harmlessness, comprehensiveness, intent capture, and helpfulness. Additionally, the stability of artificial intelligence responses was also assessed by submitting each question 3 times under consistent conditions. Google Bard excelled in readability but lagged in appropriateness when compared to human experts (mean 8.51, SD 0.37 vs mean 9.60, SD 0.33; P=.03). ChatGPT-3.5 and ChatGPT-4, however, performed comparably with human experts in terms of appropriateness (mean 8.96, SD 0.35 and mean 9.34, SD 0.47, respectively), with ChatGPT-4 demonstrating the highest stability and reliability. Furthermore, all 3 LLMs received superior harmlessness scores comparable to human experts, with lay users finding minimal differences in helpfulness and intent capture between the artificial intelligence models and human responses. LLMs, particularly ChatGPT-4, show potential in oral health care, providing patient-centric information for enhancing patient education and clinical care. The observed performance variations underscore the need for ongoing refinement and ethical considerations in health care settings. Future research focuses on developing strategies for the safe integration of LLMs in health care settings.

Twelve tips for orienting preclinical healthcare students to simulation education

Simulation-based education (SBE) is common in healthcare education and is increasingly being incorporated in preclinical curriculum. Preclinical students typically have had little exposure to the clinical setting (i.e. hospital patient rooms, equipment) and often feel uncomfortable when first placed in the simulated clinical environment. Prebriefing, a standard of best practice in simulation, prepares learners for simulation exercises. To successfully integrate SBE in preclinical education, we recommend expanding the prebriefing to include: multiple activities that orient learners to the learning space and the structure of a simulation activity, the goals of simulation as a learning process, faculty modeling of a simulated patient encounter, and expected learner outcomes. This approach increases student familiarity with the simulation learning environment and performance expectations, which can reduce cognitive load and improve learning outcomes. We describe 12 tips for increasing the scope of the prebriefing to promote effective learner participation and development during preclinical SBE.

Are serious games seriously good at preparing students for clinical practice?: A randomized controlled trial

Purpose Serious games (SGs) have great potential for pediatric medical education. This study evaluated the efficacy of a SG in improving learner satisfaction, knowledge, and behavior. Materials and methods This was an investigator-blinded randomized controlled trial (RCT) comparing a SG against two controls: (i) adaptive tutorial (AT), and (ii) low-stimulus control (LSC). SG is a highly immersive role-playing game in a virtual hospital. AT delivers interactive web-based lessons. LSC is paper-based clinical practice guidelines. Metropolitan senior medical students at UNSW were eligible. A total of 154 enrolled and were block randomized to one intervention. Participants had access to one intervention for 8 weeks which taught pediatric acute asthma and seizure assessment and management. Satisfaction was assessed with Likert-scale responses to 5 statements and 2 free-text comments. Knowledge was assessed with 10 multiple-choice questions (MCQs). Clinical behavior was assessed during a 30-point simulated clinical management scenario (CMS). Primary analysis was performed on a modified intention-to-treat basis and compared: (1) SG vs. AT; and (2) SG vs. LSC. Results A total of 118 participants were included in the primary analysis (modified intention-to-treat model). No significant differences in MCQ results between the SG and control groups. SG group outperformed the LSC group in the CMS, with a moderate effect (score out of 30: 20.8 (3.2) vs. 18.7 (3.2), respectively, d = 0.65 (0.2–1.1), p = 0.005). No statistically significant difference between SG and AT groups in the CMS (score: 20.8 (3.2) vs. 19.8 (3.1), respectively, d = 0.31 (–0.1 to 0.8), p = 0.18). A sensitivity analysis (per-protocol model) was performed with similar outcomes. Conclusions This is the first investigator-blinded RCT assessing the efficacy of a highly immersive SG on learner attitudes, knowledge acquisition, and performance in simulated pediatric clinical scenarios. The SG demonstrated improved translation of knowledge to a simulated clinical environment, particularly compared to LSC. SGs show promise in pediatric medical education.

Implantation accuracy of novel polyimide stereotactic electroencephalographic depth electrodes-a human cadaveric study.

Stereoelectroencephalography (sEEG) is a minimally invasive procedure that uses depth electrodes stereotactically implanted into brain structures to map the origin and propagation of seizures in epileptic patients. Implantation accuracy of sEEG electrodes plays a critical role in the safety and efficacy of the procedure. This study used human cadaver heads, simulating clinical practice, to evaluate (1) neurosurgeon's ability to implant a new thin-film polyimide sEEG electrode according to the instructions for use (IFU), and (2) implantation accuracy. Four neurosurgeons (users) implanted 24 sEEG electrodes into two cadaver heads with the aid of the ROSA robotic system. Usability was evaluated using a questionnaire that assessed completion of all procedure steps per IFU and user errors. For implantation accuracy evaluation, planned electrode trajectories were compared with post-implantation trajectories after fusion of pre- and postoperative computer tomography (CT) images. Implantation accuracy was quantified using the Euclidean distance for entry point error (EPE) and target point error (TPE). All sEEG electrodes were successfully placed following the IFU without user errors, and post-implant survey of users showed favorable handling characteristics. The EPE was 1.28 ± 0.86 mm and TPE was 1.61 ± 0.89 mm. Long trajectories (>50 mm) had significantly larger EPEs and TPEs than short trajectories (<50 mm), and no differences were found between orthogonal and oblique trajectories. Accuracies were similar or superior to those reported in the literature when using similar experimental conditions, and in the same range as those reported in patients. The results demonstrate that newly developed polyimide sEEG electrodes can be implanted as accurately as similar devices in the marker without user errors when following the IFU in a simulated clinical environment. The human cadaver ex-vivo test system provided a realistic test system, owing to the size, anatomy and similarity of tissue composition to that of the live human brain.

Can Surgeons Reliably Identify Non-cirrhotic Liver Disease During Laparoscopic Bariatric Surgery?

Identification of liver disease during bariatric operations is an important task given the patients risk for occult fatty liver disease. Surgeon's accuracy of assessing for liver disease during an operation is poorly understood. The objective was to measure surgeons' performance on intra-operative visual assessment of the liver in a simulated environment. Liver images from 100 patients who underwent laparoscopic bariatric surgery and pre-operative ultrasound elastography between July 2020 and July 2021 were retrospectively evaluated. The perception of 15 surgeons regarding the degree of hepatic steatosis and fibrosis was collected in a simulated clinical environment by survey and compared to results determined by ultrasonographic exam. The surgeons' ability to correctly identify the class of steatosis and fibrosis was poor (accuracy 61% and 59%, respectively) with a very weak correlation between the surgeon's predicted class and its true class (r = 0.17 and r = 0.12, respectively). When liver disease was present, surgeons completely missed its presence in 26% and 51% of steatosis and fibrosis, respectively. Digital image processing demonstrated that surgeons subjectively classified steatosis based on the "yellowness" of the liver and fibrosis based on texture of the liver, despite neither correlating with the true degree of liver disease. Laparoscopic visual assessment of the liver surface for identification of non-cirrhotic liver disease was found to be an inaccurate method during laparoscopic bariatric surgery. While validation studies are needed, the results suggest the clinical need for alternative approaches.

COMPARISON OF THE EFFECTS OF THE IN SITU SIMULATION AND SIMULATED CLINICAL IMMERSION METHODS ON CANCER NURSING STUDENTS’ EXTRAVASATION MANAGEMENT: RANDOMIZED CONTROLLED TRIAL

In situ simulation is thought to offer a good learning environment due to the fact that it is carried out in real clinical practice. This study was performed to compare the effect of in situ simulation and simulated clinical immersion environment on cancer nursing students extravasation management. The study was carried out with a randomized controlled pretest-posttest comparative design. The participants were randomly assigned to either the simulated clinical immersion group (n=19) or the in situ simulation group (n=24). The study data were collected using Extravasation Management Knowledge Test, Objective Structured Clinical Assessment, Students’ Satisfaction and Self-Confidence Scale and the State Anxiety Inventory. The pre-posttest mean scores for the knowledge level and anxiety mean scores of the participants in the simulated clinical immersion group and the in situ group were not statistically significant (p˃.05). The satisfaction and self-confidence scale mean scores and the skill levels of the students in both settings were similar after the implementation (p˃.05). The students' knowledge, skills, anxiety, self-confidence and satisfaction were similar in both simulation-based learning environments. In situ simulation can be recommended for use in nursing education. Considering cost-effectiveness and resources, both simulation methods can be used.

Human-AI teaming: leveraging transactive memory and speaking up for enhanced team effectiveness.

In this prospective observational study, we investigate the role of transactive memory and speaking up in human-AI teams comprising 180 intensive care (ICU) physicians and nurses working with AI in a simulated clinical environment. Our findings indicate that interactions with AI agents differ significantly from human interactions, as accessing information from AI agents is positively linked to a team's ability to generate novel hypotheses and demonstrate speaking-up behavior, but only in higher-performing teams. Conversely, accessing information from human team members is negatively associated with these aspects, regardless of team performance. This study is a valuable contribution to the expanding field of research on human-AI teams and team science in general, as it emphasizes the necessity of incorporating AI agents as knowledge sources in a team's transactive memory system, as well as highlighting their role as catalysts for speaking up. Practical implications include suggestions for the design of future AI systems and human-AI team training in healthcare and beyond.

Interprofessional Healthcare Themes derived through Critical Discourse Analysis

One of the four primary learning competencies of Interprofessional Education (IPE) is Interprofessional (IP) Communication. Rosalind Franklin University of Medicine and Science (RFUMS) partnered with the University of New England (UNE) to offer an IP Team Immersion (IPTI) telehealth simulation (tSIM). IPTI aims to provide opportunities for IP teams of students to increase understanding of each other's roles, responsibilities, demonstrate teamwork principles and skills, and apply integrated communication skills for team-based, patient-centered practice in a simulated setting. We hypothesized that IPTI provides an opportunity for students to learn communication skills in an interprofessional team setting and that CDA can be used to identify incidences of verbal and non-verbal communication.In this experience, groups of students formed IP teams and worked together to plan their approach to a standardized patient (SP) case. Nine student teams across two universities and ten health professions participated in the virtual sessions and simulations. At the end of the tSIM activities, IP student teams were given 45 minutes to debrief and discuss their performance.CDA can be used to understand how communication among a team of IP healthcare students contributes to student learning in a simulated clinical environment. This study used CDA to analyze communication during the debrief sessions and the main themes identified were Verbal Communication, Non-Verbal Communication, Working Relationships, and Telehealth.Our results indicated that IPTI provided an opportunity for students working in a team to learn communication skills used within an IP team.

Characterizing lesion morphology of a novel diamond-tip temperature-controlled irrigated radiofrequency ablation catheter.

The DiamondTemp ablation (DTA) system is a novel temperature-controlled irrigated radiofrequency (RF) ablation system that accurately measures tip-tissue temperatures for real-time power modulation. Lesion morphologies from longer RF durations with the DTA system have not been previously described. We sought to evaluate lesion characteristics of the DTA system when varying the application durations. A bench model using porcine myocardium was used to deliver discrete lesions in a simulated clinical environment. The DTA system was power-limited at 50 W with temperature set-points of 50 °C and 60 °C (denoted Group_50 and Group_60). Application durations were randomized with a range of 5-120 s. In total, 280 applications were performed. Steam pops were observed in five applications: two applications at 90 s and three applications at 120 s. Lesion size (depth and maximum width) increased significantly with longer applications, until 60 s for both Group_50 and Group_60 (depth: 4.5 ± 1.2 mm and 5.6 ± 1.3 mm; maximum width: 9.3 ± 2.7mm and 11.2 ± 1.7mm, respectively). As lesions transition from resistive to conductive heating (longer than 10 s), the maximum width progressed in a sub-surface propagation. Using a "Time after Temperature 60 °C" (TaT60) analysis, depths of 2-3 mm occur in 0-5 s and depths plateau at 4.6 ± 0.8 mm between 20 and 30 s. The DTA system rapidly creates wide lesions with lesion depth increasing over time with application durations up to 60 s. Using a TaT60 approach is a promising ablation guidance that would benefit from further investigation.

Appraisal and Evaluation of the Learning Environment Instruments of the Student Nurse: A Systematic Review Using COSMIN Methodology

Nursing education consists of theory and practice, and student nurses' perception of the learning environment, both educational and clinical, is one of the elements that determines the success or failure of their university study path. This study aimed to identify the currently available tools for measuring the clinical and educational learning environments of student nurses and to evaluate their measurement properties in order to provide solid evidence for researchers, educators, and clinical tutors to use in the selection of tools. We conducted a systematic review to evaluate the psychometric properties of self-reported learning environment tools in accordance with the Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) Guidelines of 2018. The research was conducted on the following databases: PubMed, CINAHL, APA PsycInfo, and ERIC. In the literature, 14 instruments were found that evaluate both the traditional and simulated clinical learning environments and the educational learning environments of student nurses. These tools can be ideally divided into first-generation tools developed from different learning theories and second-generation tools developed by mixing, reviewing, and integrating different already-validated tools. Not all the relevant psychometric properties of the instruments were evaluated, and the methodological approaches used were often doubtful or inadequate, thus threatening the instruments' external validity. Further research is needed to complete the validation processes undertaken for both new and already developed instruments, using higher-quality methods and evaluating all psychometric properties.

Evaluating the Impact on Clinical Task Efficiency of a Natural Language Processing Algorithm for Searching Medical Documents: Prospective Crossover Study.

Information retrieval (IR) from the free text within electronic health records (EHRs) is time consuming and complex. We hypothesize that natural language processing (NLP)-enhanced search functionality for EHRs can make clinical workflows more efficient and reduce cognitive load for clinicians. This study aimed to evaluate the efficacy of 3 levels of search functionality (no search, string search, and NLP-enhanced search) in supporting IR for clinical users from the free text of EHR documents in a simulated clinical environment. A clinical environment was simulated by uploading 3 sets of patient notes into an EHR research software application and presenting these alongside 3 corresponding IR tasks. Tasks contained a mixture of multiple-choice and free-text questions. A prospective crossover study design was used, for which 3 groups of evaluators were recruited, which comprised doctors (n=19) and medical students (n=16). Evaluators performed the 3 tasks using each of the search functionalities in an order in accordance with their randomly assigned group. The speed and accuracy of task completion were measured and analyzed, and user perceptions of NLP-enhanced search were reviewed in a feedback survey. NLP-enhanced search facilitated more accurate task completion than both string search (5.14%; P=.02) and no search (5.13%; P=.08). NLP-enhanced search and string search facilitated similar task speeds, both showing an increase in speed compared to the no search function, by 11.5% (P=.008) and 16.0% (P=.007) respectively. Overall, 93% of evaluators agreed that NLP-enhanced search would make clinical workflows more efficient than string search, with qualitative feedback reporting that NLP-enhanced search reduced cognitive load. To the best of our knowledge, this study is the largest evaluation to date of different search functionalities for supporting target clinical users in realistic clinical workflows, with a 3-way prospective crossover study design. NLP-enhanced search improved both accuracy and speed of clinical EHR IR tasks compared to browsing clinical notes without search. NLP-enhanced search improved accuracy and reduced the number of searches required for clinical EHR IR tasks compared to direct search term matching.

Evaluation of the Clinical Utility of the Bone Metastases Ensemble Trees for Survival Decision Support Platform (BMETS-DSP): A Case-Based Pilot Assessment.

The Bone Metastases Ensemble Trees for Survival Decision Support Platform (BMETS-DSP) provides patient-specific survival predictions and evidence-based recommendations to guide multidisciplinary management for symptomatic bone metastases. We assessed the clinical utility of the BMETS-DSP through a pilot prepost design in a simulated clinical environment. Ten Radiation Oncology physicians reviewed 55 patient cases at two time points: without and then with the use of BMETS-DSP. Assessment included 12-month survival estimate, confidence in and likelihood of sharing estimates with patients, and recommendations for open surgery, systemic therapy, hospice referral, and radiotherapy (RT) regimen. Paired statistics compared pre- versus post-DSP outcomes. Reported statistical significance is P < .05. Pre- versus post-DSP, overestimation of true minus estimated survival time was significantly reduced (mean difference -2.1 [standard deviation 4.1] v -1 month [standard deviation 3.5]). Prediction accuracy was significantly improved at cut points of < 3 (72 v 79%), ≤ 6 (64 v 71%), and ≥ 12 months (70 v 81%). Median ratings of confidence in and likelihood of sharing prognosis significantly increased. Significantly greater concordance was seen in matching use of 1-fraction RT with the true survival < 3 months (70 v 76%) and < 10-fraction RT with the true survival < 12 months (55 v 62%) and appropriate use of open surgery (47% v 53%), without significant changes in selection of hospice referral or systemic therapy. This pilot study demonstrates that BMETS-DSP significantly improved physician survival estimation accuracy, prognostic confidence, likelihood of sharing prognosis, and use of prognosis-appropriate RT regimens in the care of symptomatic bone metastases, supporting future multi-institutional validation of the platform.

The impact of small-group virtual patient simulator training on perceptions of individual learning process and curricular integration: a multicentre cohort study of nursing and medical students

BackgroundThe COVID-19 pandemic has precipitated rapid changes in medical education to protect students and patients from the risk of infection. Virtual Patient Simulators (VPS) provide a simulated clinical environment in which students can interview and examine a patient, order tests and exams, prioritize interventions, and observe response to therapy, all with minimal risk to themselves and their patients. Like high-fidelity simulators (HFS), VPS are a tool to improve curricular integration. Unlike HFS, VPS require limited infrastructure investment and can be used in low-resource settings. Few studies have examined the impact of VPS training on clinical education. This international, multicenter cohort study was designed to assess the impact of small-group VPS training on individual learning process and curricular integration from the perspective of nursing and medical students.MethodsWe conducted a multi-centre, international cohort study of nursing and medical students. Baseline perceptions of individual learning process and curricular integration were assessed using a 27-item pre-session questionnaire. Students subsequently participated in small-group VPS training sessions lead by a clinical tutor and then completed a 32-item post-session questionnaire, including 25 paired items. Pre- and post-session responses were compared to determine the impact of the small-group VPS experience.ResultsParticipants included 617 nursing and medical students from 11 institutions in 8 countries. At baseline, nursing students reported greater curricular integration and more clinical and simulation experience than did medical students. After exposure to small-group VPS training, participants reported significant improvements in 5/6 items relating to individual learning process and 7/7 items relating to curricular integration. The impact of the VPS experience was similar amongst nursing and medical students.ConclusionsIn this multi-centre study, perceptions of individual learning process and curricular integration improved after exposure to small-group VPS training. Nursing and medical students showed similar impact. Small-group VPS training is an accessible, low-risk educational strategy that can improve student perceptions of individual learning process and curricular integration.

All clinical stressors are not created equal: Differential task stress in a simulated clinical environment.

A variety of stressors are encountered while working in the emergency department and are often recreated in simulation-based medical education. We seek to examine the physiologic and stress state response of participants in a simulated clinical environment to commonly encountered stressors. Emergency medicine (EM) residents participated in a randomized, controlled trial of six simulated patient encounters with one of three stressors, medical difficulty, interpersonal challenge, and technology/equipment failure, randomized into each scenario. Participants wore smart shirts to measure heart rate variability (HRV) at rest and just after the introduced stressor and completed the Short Stress State Questionnaire (SSSQ) before and after each scenario. Twenty-seven EM residents participated in the study. Interpersonal challenge resulted in increased distress as measured by SSSQ compared to the other two stressors (one way ANOVA, F[2,144]=9.95, p<0.001). There was no difference in worry or task engagement across stressors. HRV decreased significantly from rest for all stressors (p=0.0003, p=0.0112, p=0.0027 for medical difficulty, interpersonal challenge, and equipment failure, respectively), but there was no statistically significant difference between mean change in HRV across stressors (one way ANOVA, F[2,120]=0.17, p=0.8452). Interpersonal challenge stressor was significantly associated with an increase in distress in EM residents during the simulated encounters as compared to the other stressors. While heart rate variability decreased from rest for each stressor as expected following stressor introduction, differing stressors did not produce a differential change.

Imaging AI in Practice: A Demonstration of Future Workflow Using Integration Standards

Artificial intelligence (AI) tools are rapidly being developed for radiology and other clinical areas. These tools have the potential to dramatically change clinical practice; however, for these tools to be usable and function as intended, they must be integrated into existing radiology systems. In a collaborative effort between the Radiological Society of North America, radiologists, and imaging-focused vendors, the Imaging AI in Practice (IAIP) demonstrations were developed to show how AI tools can generate, consume, and present results throughout the radiology workflow in a simulated clinical environment. The IAIP demonstrations highlight the critical importance of semantic and interoperability standards, as well as orchestration profiles for successful clinical integration of radiology AI tools. Keywords: Computer Applications-General (Informatics), Technology Assessment © RSNA, 2021.

Holistic Patient Assessment in Simulated Clinical Experiences

Nursing care extends beyond physical ailments; it includes holistic components such as the psychosocial, cultural, spiritual, and developmental aspects of care. These learning needs are generally met in the traditional clinical environment. However, research findings suggest that opportunities for holistic patient care in simulated clinical environments may be lacking, rendering these environments insufficient to meet nursing students’ learning needs. This paper outlines numerous holistic patient care concepts, simulated patient and family responses, props, and moulage that are low-cost and easily implemented in the simulated environment.

Are Traditional and Simulated Clinical Environments Meeting Nursing Students’ Learning Needs?

BackgroundThe Clinical Learning Environment Comparison Survey compares nursing students’ perceptions of how well their learning needs are met in the clinical and simulation environments, providing insight into how to enhance learning opportunities in both environments. MethodsThis multisite study took place at nine nursing schools with accredited simulation programs. The CLECS was completed by undergraduate nursing students who had cared for at least one simulated patient and one live patient. ResultsOne hundred fifty-nine students completed the survey. Subscale means were higher in the traditional clinical environment for three of the six subscales (communication [p <.001], nursing process [p =.026], holism [p <.001]. The subscale mean for teaching-learning dyad [p = .060] was higher in the simulated clinical environment. The total CLECS mean scores (p = .154) were higher for the traditional clinical environment than the simulated environment. ConclusionsThe importance of the type of clinical learning environment and associated experiences created for undergraduate nursing student learning cannot be overestimated. Periodic evaluation of both environments from the students’ perspective will assist educators with making vital educational decisions.

High-fidelity simulation and virtual reality: an evaluation of medical students’ experiences

BackgroundSimulation technology is widely used in medical education, providing an environment in which students can develop and practise a multitude of skills that are relevant to clinical practice, without the...