Short Presentations 2 – Technology and Techniques – 18.03.2017, 10.00 to 11.15 – Lecture hall A 003
Chair: Monika Brodmann
|10:00 – 10:15
|How realistic are low cost, low fidelity bronchoscopy simulators?
|10:15 – 10:30
|Motion tracking for mass-casualty-incident simulations using cell phones
University of Applied Sciences Hamburg, Germany; email@example.com
Background: The simulation of mass-casualty-incidents (MCI) requires a huge amount of standardized patients (SP), medical and paramedical staff, resources and time. Nonetheless it is important to train the necessary protocols as often as possible to be prepared in case of a real situation. Since these simulations cannot be realized on a short-term regular base it is important to gather as much information as possible.
The project introduced here allows the role centered automatic tracking of participant movements in a simulated MCI scenario without gathering information about their identities. This tracking allows automatic detection of the time needed to rescue the SPs, the transport time to the treatment area and the time until the SPs are on their way to the hospital. The collected data can be used for debriefing while the role is separated from the involved participants. In that way a neutral review of the simulation is possible. Additional dissections of the simulation are also possible.
Project description: In this project a cell phone app is developed which allows live tracking of participants of an MCI simulation. The data is sent to a server, so that the current movement can be displayed and analyzed. The submitted information allows no inference to the real person or the submitting cell phone. The first message, which is sent only once gives background information of the function of the participant within the simulation e.g. emergency doctor, fireman or patient (red) and an optional tag which allows conclusion about the case depicted by the standardized patient. The following messages sent every second contain latitude, longitude and altitude information together with a time stamp.
Additionally a Windows program is developed which analyzes the submitted data. Current movements are displayed, so that the whole simulation is under surveillance. At the same time the Software allows the analysis of the submitted data. The submitted paths can be shown and the simulation can be replayed and discussed step by step. The area of operations is detected automatically and the movement coverage of that region is shown, so that hotspots of interest of the involved people can be identified.
Outcome or expected outcome: First test runs of the software show that it is possible to track the participants of an MCI simulation and display their movements live on a PC. The Area of operations could be detected, subdivided into smaller regions and the probability of passing through the smaller regions could be calculated. The result is a coverage map of the region marking the spots of interest for the medical and paramedical staff. By selecting only the movement history of special roles it is possible to show the interaction of these roles during the time of the simulation.
The whole simulation could be replayed so that all movements could be used for a debriefing. SPs within the simulation could be marked which allows the software to measure and display the time needed to find and transport the SPs.
Since the first test run was used to test the software and to implement missing features based on realistic movements, not all roles were measured in the course of the simulation. Hence the measured movements did not cover the whole scenario and they could not be used for a debriefing. As a next step the display of motion and event data shall be used for a debriefing in order to evaluate the advantages and possible optimizations of the method for the training.
Challenges: The detection of movement works well as long as the participants are outside of buildings and the GPS signal is not disturbed by e.g. concrete. Also the cell phone needs a good connection to the next network receiver so that the gathered data can be transmitted. The latter can be handled by implementing a data buffer that collects movement data if a connection to the network is impossible. This will save the data but of course prohibits a live tracking.
Within buildings the tracking is a challenge, since the network connection and the GPS signal is blocked by obstacles. A possible solution would be indoor GPS  which is not available in all buildings.
But further research has to be done to find a simple solution without an elaborate preparation of the simulation area.
Discussion: This project aims to develop a cell phone app that tracks movements of roles within a simulated MCI as well as a software visualizing the measured data to improve the analysis of events and the debriefing. First measurements show that it is possible to collect and analyze movement information as long as participants stay outside of buildings. Further development and research has to be done to improve the collection of data even inside of buildings and to proof that the collected data improves the debriefing.
 Indoor Positioning via Three Different RF Technologies, Vorst et al., 4th European Workshop on RFID Systems and Technologies (RFID SysTech), 2008
|10:30 – 10:45
|Continuous Education for Communication Trainers: Using the method Flipped Classroom to improve Communicational Skills and enhance teambuilding
|Sibylle Matt Robert
Bern University of Applied Sciences, Switzerland; firstname.lastname@example.org
Background: The Bern University of Applied Sciences, Health Division, collaborates with professional actors who act as Communication trainers (CTs). Compared to settings with standardized patients CTs have extended competencies. Apart from functioning as partners in the role plays and giving a short subjective feedback they are also moderating the demanding feedback discussion and link findings out of the role play with communication theory. In our setting there is no other faculty member present.
Collaborating with a team of CTs mainly consisting of external staff members means that they not only have to be trained in various communication skills. There has also to be time for measures to support teambuilding processes. In the past the design of the yearly workshop day contained inputs of lecturers as well as methods to transfer knowledge into everyday practice. This year we introduced an electronic educational platform and applied the method Flipped Classroom. In this concept the acquirement of knowledge is mainly situated during an online learning phase preceding the workshop. It’s based on the fact that persons in a learning process are highly motivated when they are often given individual feedback (Rheinberg 2012).
|10:45 – 11:00
|Development of a Wearable Electronic Sensor Array and Measuring Unit for Spine and Posture Analysis for Use with Standardized Patients in Medical Simulation and Education
|11:00 – 11:15
|C4 : Centre Coordonné de Compétences Clinique : an interinstitutionnal partnership for the teaching of the clinical competences
| Nadine Oberhauser; Nadine.OBERHAUSER@hesav.ch
Haute Ecole de Santé Vaud, Switzerland;
The C4 is the result of an interinstitutionnal partnership established between HESAV, the FBM-UNIL, the hEdS La Source and the CHUV all based in Lausanne (Canton de Vaud). The project started a few years ago and the opening of the C4 is planed in 2020. Its aim is to promote the quality of health care, and develop the coordination and collaboration between health professionnals. Dedicated to simulation, the C4 will host about 700 to 1000 people per day, and allow an interprofessionnal approach and training of various care situations. The aim of the presentation is to enhance the interest and the complexity of the process and its aims.
 Haute Ecole de Santé Vaud,
 Faculté de Biologie et de Médecine de l’Université de Lausanne
 Haute Ecole de Santé La Source
 Centre hospitalier Universitaire, Centre des Formations