985 resultados para Patient simulation
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In the last years, simulation training has become widespread in different areas of medicine due to social expectations, political accountability and professional regulation. Different types of simulators allow to improve knowledge, skills, communication and team behavior. Simulation sessions have been proven to shorten the learning curve and allow education in a safe environment. Patients on dialysis are an expanding group. They often suffer from several comorbidities and need complex surgical procedures with regard to their dialysis access. Therefore, education in evidence-based algorithms is as important as teaching of practical skills. In this chapter, we are presenting an overview of available dialysis access training modalities. We are convinced that simulation will become more important in the near future and has a substantial impact on strategies to improve aspects of patient safety. © 2015 S. Karger AG, Basel.
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Introduction Since the quality of patient portrayal of standardized patients (SPs) during an Objective Structured Clinical Exam (OSCE) has a major impact on the reliability and validity of the exam, quality control should be initiated. Literature about quality control of SP’s performance focuses on feedback [1, 2] or completion of checklists [3, 4]. Since we did not find a published instrument meeting our needs for the assessment of patient portrayal, we developed such an instrument after being inspired by others [5] and used it in our high-stakes exam. Methods SP trainers from all five Swiss medical faculties collected and prioritized quality criteria for patient portrayal. Items were revised with the partners twice, based on experiences during OSCEs. The final instrument contains 14 criteria for acting (i.e. adequate verbal and non-verbal expression) and standardization (i.e. verbatim delivery of the first sentence). All partners used the instrument during a high-stakes OSCE. Both, SPs and trainers were introduced to the instrument. The tool was used in training (more than 100 observations) and during the exam (more than 250 observations). FAIR_OSCE The list of items to assess the quality of the simulation by SPs was primarily developed and used to provide formative feedback to the SPs in order to help them to improve their performance. It was therefore named “Feedbackstruckture for the Assessment of Interactive Role play in Objective Structured Clinical Exams (FAIR_OSCE). It was also used to assess the quality of patient portrayal during the exam. The results were calculated for each of the five faculties individually. Formative evaluation was given to the five faculties with individual feedback without revealing results of other faculties other than overall results. Results High quality of patient portrayal during the exam was documented. More than 90% of SP performances were rated to be completely correct or sufficient. An increase in quality of performance between training and exam was noted. In example the rate of completely correct reaction in medical tests increased from 88% to 95%. 95% completely correct reactions together with 4% sufficient reactions add up to 99% of the reactions meeting the requirements of the exam. SP educators using the instrument reported an augmentation of SPs performance induced by the use of the instrument. Disadvantages mentioned were high concentration needed to explicitly observe all criteria and cumbersome handling of the paper-based forms. Conclusion We were able to document a very high quality of SP performance in our exam. The data also indicate that our training is effective. We believe that the high concentration needed using the instrument is well invested, considering the observed augmentation of performance. The development of an iPad based application for the form is planned to address the cumbersome handling of the paper.
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Introduction In our program, simulated patients (SPs) give feedback to medical students in the course of communication skills training. To ensure effective training, quality control of the SPs’ feedback should be implemented. At other institutions, medical students evaluate the SPs’ feedback for quality control (Bouter et al., 2012). Thinking about implementing quality control for SPs’ feedback in our program, we wondered whether the evaluation by students would result in the same scores as evaluation by experts. Methods Consultations simulated by 4th-year medical students with SPs were video taped including the SP’s feedback to the students (n=85). At the end of the training sessions students rated the SPs’ performance using a rating instrument called Bernese Assessment for Role-play and Feedback (BARF) containing 11 items concerning feedback quality. Additionally the videos were evaluated by 3 trained experts using the BARF. Results The experts showed a high interrater agreement when rating identical feedbacks (ICCunjust=0.953). Comparing the rating of students and experts, high agreement was found with regard to the following items: 1. The SP invited the student to reflect on the consultation first, Amin (= minimal agreement) 97% 2. The SP asked the student what he/she liked about the consultation, Amin = 88%. 3. The SP started with positive feedback, Amin = 91%. 4. The SP was comparing the student with other students, Amin = 92%. In contrast the following items showed differences between the rating of experts and students: 1. The SP used precise situations for feedback, Amax (=maximal agreement) 55%, Students rated 67 of SPs’ feedbacks to be perfect with regard to this item (highest rating on a 5 point Likert scale), while only 29 feedbacks were rated this way by the experts. 2. The SP gave precise suggestions for improvement, Amax 75%, 62 of SPs’ feedbacks obtained the highest rating from students, while only 44 of SPs’ feedbacks achieved the highest rating in the view of the experts. 3. The SP speaks about his/her role in the third person, Amax 60%. Students rated 77 feedbacks with the highest score, while experts judged only 43 feedbacks this way. Conclusion Although evaluation by the students was in agreement with that of experts concerning some items, students rated the SPs’ feedback more often with the optimal score than experts did. Moreover it seems difficult for students to notice when SPs talk about the role in the first instead of the third person. Since precision and talking about the role in the third person are important quality criteria of feedback, this result should be taken into account when thinking about students’ evaluation of SPs’ feedback for quality control. Bouter, S., E. van Weel-Baumgarten, and S. Bolhuis. 2012. Construction and Validation of the Nijmegen Evaluation of the Simulated Patient (NESP): Assessing Simulated Patients’ Ability to Role-Play and Provide Feedback to Students. Academic Medicine: Journal of the Association of American Medical Colleges
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Rapidly growing technical developments and working time constraints call for changes in trainee formation. In reality, trainees spend fewer hours in the hospital and face more difficulties in acquiring the required qualifications in order to work independently as a specialist. Simulation-based training is a potential solution. It offers the possibility to learn basic technical skills, repeatedly perform key steps in procedures and simulate challenging scenarios in team training. Patients are not at risk and learning curves can be shortened. Advanced learners are able to train rare complications. Senior faculty member's presence is key to assess and debrief effective simulation training. In the field of vascular access surgery, simulation models are available for open as well as endovascular procedures. In this narrative review, we describe the theory of simulation, present simulation models in vascular (access) surgery, discuss the possible benefits for patient safety and the difficulties of implementing simulation in training.
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OBJECTIVES The aim of this Short Communication was to present a workflow for the superimposition of intraoral scan (IOS), cone-beam computed tomography (CBCT), and extraoral face scan (EOS) creating a 3D virtual dental patient. MATERIAL AND METHODS As a proof-of-principle, full arch IOS, preoperative CBCT, and mimic EOS were taken and superimposed to a unique 3D data pool. The connecting link between the different files was to detect existing teeth as constant landmarks in all three data sets. RESULTS This novel application technique successfully demonstrated the feasibility of building a craniofacial virtual model by image fusion of IOS, CBCT, and EOS under 3D static conditions. CONCLUSIONS The presented application is the first approach that realized the fusion of intraoral and facial surfaces combined with skeletal anatomy imaging. This novel 3D superimposition technique allowed the simulation of treatment planning, the exploration of the patients' expectations, and the implementation as an effective communication tool. The next step will be the development of a real-time 4D virtual patient in motion.
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Workshop Overview The use of special effects (moulage) is a way to augment the authenticity of a scenario in simulation. This workshop will introduce different techniques of moulage (oil based cream colors, watercolors, transfer tattoos and 3D Prosthetics). The participants will have the opportunity to explore these techniques by applying various moulages. They will compare the techniques and discuss their advantages and disadvantages. Moreover, strategies for standardization and quality assurance will be discussed. Workshop Rationale Moulage supports the sensory perception in an scenario (1). It can provide evaluation clues (2) and help learners (and SPs) to engage in the simulation. However, it is of crucial importance that the simulated physical pathologies are represented accurate and reliable. Accuracy is achieved by using the appropriate technique, which requires knowledge and practice . With information about different moulage techniques, we hope to increases the knowledge of moulage during the workshop. By applying moulages in various techniques we will practice together. As standardization is critical for simulation scenarios in assessment (3, 4) strategies for standardization of moulage will be introduced and discussed. Workshop Objectives During the workshop participants will: - gain knowledge about different techniques of moulages - practice moulages in various techniques - discuss the advantages and disadvantages of moulage techniques - describe strategies for standardization and quality assurance of moulage Planned Format 5 min Introduction 15 min Overview – Background & Theory (presentation) 15 min Application of moulage for ankle sprain in 4 different techniques (oil based cream color, water color, temporary tatoo, 3D prosthetic) in small groups 5 min Comparing the results by interactive viewing of prepared moulages 15 min Application of moulages for burn in different techniques in small groups 5 min Comparing results the results by interactive viewing of prepared moulages 5 min Sharing experiences with different techniques in small groups 20 min Discussion of the techniques including standardization and quality assurance strategies (plenary discussion) 5 min Summary / Take home points
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The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^
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An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^
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The Phase I clinical trial is considered the "first in human" study in medical research to examine the toxicity of a new agent. It determines the maximum tolerable dose (MTD) of a new agent, i.e., the highest dose in which toxicity is still acceptable. Several phase I clinical trial designs have been proposed in the past 30 years. The well known standard method, so called the 3+3 design, is widely accepted by clinicians since it is the easiest to implement and it does not need a statistical calculation. Continual reassessment method (CRM), a design uses Bayesian method, has been rising in popularity in the last two decades. Several variants of the CRM design have also been suggested in numerous statistical literatures. Rolling six is a new method introduced in pediatric oncology in 2008, which claims to shorten the trial duration as compared to the 3+3 design. The goal of the present research was to simulate clinical trials and compare these phase I clinical trial designs. Patient population was created by discrete event simulation (DES) method. The characteristics of the patients were generated by several distributions with the parameters derived from a historical phase I clinical trial data review. Patients were then selected and enrolled in clinical trials, each of which uses the 3+3 design, the rolling six, or the CRM design. Five scenarios of dose-toxicity relationship were used to compare the performance of the phase I clinical trial designs. One thousand trials were simulated per phase I clinical trial design per dose-toxicity scenario. The results showed the rolling six design was not superior to the 3+3 design in terms of trial duration. The time to trial completion was comparable between the rolling six and the 3+3 design. However, they both shorten the duration as compared to the two CRM designs. Both CRMs were superior to the 3+3 design and the rolling six in accuracy of MTD estimation. The 3+3 design and rolling six tended to assign more patients to undesired lower dose levels. The toxicities were slightly greater in the CRMs.^
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Subtraction of Ictal SPECT Co-registered to MRI (SISCOM) is an imaging technique used to localize the epileptogenic focus in patients with intractable partial epilepsy. The aim of this study was to determine the accuracy of registration algorithms involved in SISCOM analysis using FocusDET, a new user-friendly application. To this end, Monte Carlo simulation was employed to generate realistic SPECT studies. Simulated sinograms were reconstructed by using the Filtered BackProjection (FBP) algorithm and an Ordered Subsets Expectation Maximization (OSEM) reconstruction method that included compensation for all degradations. Registration errors in SPECT-SPECT and SPECT-MRI registration were evaluated by comparing the theoretical and actual transforms. Patient studies with well-localized epilepsy were also included in the registration assessment. Global registration errors including SPECT-SPECT and SPECT-MRI registration errors were less than 1.2 mm on average, exceeding the voxel size (3.32 mm) of SPECT studies in no case. Although images reconstructed using OSEM led to lower registration errors than images reconstructed with FBP, differences after using OSEM or FBP in reconstruction were less than 0.2 mm on average. This indicates that correction for degradations does not play a major role in the SISCOM process, thereby facilitating the application of the methodology in centers where OSEM is not implemented with correction of all degradations. These findings together with those obtained by clinicians from patients via MRI, interictal and ictal SPECT and video-EEG, show that FocusDET is a robust application for performing SISCOM analysis in clinical practice.
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The mechanical response of the cornea subjected to a non-contact air-jet tonometry diagnostic test represents an interplay between its geometry, the corneal material behavior and the loading. The objective is to study this interplay to better understand and interpret the results obtained with a non-contact tonometry test. A patient-specific finite element model of a healthy eye, accounting for the load free configuration, was used. The corneal tissue was modeled as an anisotropic hyperelastic material with two preferential directions. Three different sets of parameters within the human experimental range obtained from inflation tests were considered. The influence of the IOP was studied by considering four pressure levels (10–28 mmHg) whereas the influence of corneal thickness was studied by inducing a uniform variation (300–600 microns). A Computer Fluid Dynamics (CFD) air-jet simulation determined pressure loading exerted on the anterior corneal surface. The maximum apex displacement showed a linear variation with IOP for all materials examined. On the contrary, the maximum apex displacement followed a cubic relation with corneal thickness. In addition, a significant sensitivity of the apical displacement to the corneal stiffness was also obtained. Explanation to this behavior was found in the fact that the cornea experiences bending when subjected to an air-puff loading, causing the anterior surface to work in compression whereas the posterior surface works in tension. Hence, collagen fibers located at the anterior surface do not contribute to load bearing. Non-contact tonometry devices give useful information that could be misleading since the corneal deformation is the result of the interaction between the mechanical properties, IOP, and geometry. Therefore, a non-contact tonometry test is not sufficient to evaluate their individual contribution and a complete in-vivo characterization would require more than one test to independently determine the membrane and bending corneal behavior.
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Aim To develop an appropriate dosing strategy for continuous intravenous infusions (CII) of enoxaparin by minimizing the percentage of steady-state anti-Xa concentration (C-ss) outside the therapeutic range of 0.5-1.2 IU ml(-1). Methods A nonlinear mixed effects model was developed with NONMEM (R) for 48 adult patients who received CII of enoxaparin with infusion durations that ranged from 8 to 894 h at rates between 100 and 1600 IU h(-1). Three hundred and sixty-three anti-Xa concentration measurements were available from patients who received CII. These were combined with 309 anti-Xa concentrations from 35 patients who received subcutaneous enoxaparin. The effects of age, body size, height, sex, creatinine clearance (CrCL) and patient location [intensive care unit (ICU) or general medical unit] on pharmacokinetic (PK) parameters were evaluated. Monte Carlo simulations were used to (i) evaluate covariate effects on C-ss and (ii) compare the impact of different infusion rates on predicted C-ss. The best dose was selected based on the highest probability that the C-ss achieved would lie within the therapeutic range. Results A two-compartment linear model with additive and proportional residual error for general medical unit patients and only a proportional error for patients in ICU provided the best description of the data. Both CrCL and weight were found to affect significantly clearance and volume of distribution of the central compartment, respectively. Simulations suggested that the best doses for patients in the ICU setting were 50 IU kg(-1) per 12 h (4.2 IU kg(-1) h(-1)) if CrCL < 30 ml min(-1); 60 IU kg(-1) per 12 h (5.0 IU kg(-1) h(-1)) if CrCL was 30-50 ml min(-1); and 70 IU kg(-1) per 12 h (5.8 IU kg(-1) h(-1)) if CrCL > 50 ml min(-1). The best doses for patients in the general medical unit were 60 IU kg(-1) per 12 h (5.0 IU kg(-1) h(-1)) if CrCL < 30 ml min(-1); 70 IU kg(-1) per 12 h (5.8 IU kg(-1) h(-1)) if CrCL was 30-50 ml min(-1); and 100 IU kg(-1) per 12 h (8.3 IU kg(-1) h(-1)) if CrCL > 50 ml min(-1). These best doses were selected based on providing the lowest equal probability of either being above or below the therapeutic range and the highest probability that the C-ss achieved would lie within the therapeutic range. Conclusion The dose of enoxaparin should be individualized to the patients' renal function and weight. There is some evidence to support slightly lower doses of CII enoxaparin in patients in the ICU setting.
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Travail d’intégration présenté en vue de l’obtention du grade de physiothérapeute en Maîtrise en physiothérapie
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Travail d’intégration présenté en vue de l’obtention du grade de physiothérapeute en Maîtrise en physiothérapie
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Many have called for medical students to learn how to manage complexity in healthcare. This study examines the nuances of students' challenges in coping with a complex simulation learning activity, using concepts from complexity theory, and suggests strategies to help them better understand and manage complexity.Wearing video glasses, participants took part in a simulation ward-based exercise that incorporated characteristics of complexity. Video footage was used to elicit interviews, which were transcribed. Using complexity theory as a theoretical lens, an iterative approach was taken to identify the challenges that participants faced and possible coping strategies using both interview transcripts and video footage.Students' challenges in coping with clinical complexity included being: a) unprepared for 'diving in', b) caught in an escalating system, c) captured by the patient, and d) unable to assert boundaries of acceptable practice.Many characteristics of complexity can be recreated in a ward-based simulation learning activity, affording learners an embodied and immersive experience of these complexity challenges. Possible strategies for managing complexity themes include: a) taking time to size up the system, b) attuning to what emerges, c) reducing complexity, d) boundary practices, and e) working with uncertainty. This study signals pedagogical opportunities for recognizing and dealing with complexity.