The proliferation of ventilator graphic displays on today’s current generation of ventilators has necessitated that respiratory care educators emphasize understanding and interpretation of ventilator waveform graphics. The presentation of a dynamic subject matter such as capnography, electrocardiography, or ventilator waveform graphics has traditionally been accomplished using static images that attempt to illustrate discreet and often subtle changes of a dynamic and reactive process.
Static pictorial representations of waveforms tend to work well to reinforce processes for those who have experience working with clinical situations, particularly for those who have the clinical experience to serve as the context against which the static waveforms may be framed. Unfortunately most respiratory care students, and healthcare students in general, lack the clinical context necessary to project an understanding of the static images onto the dynamic waveforms displayed on the current generation of ventilators. Medical simulations offer a promising method of training because they are able to display dynamic and reactive waveforms and provide a context framework to students who lack clinical experience and therefore the clinical context that is so important in interpretation of dynamic waveforms.
|Figure 1: Screen-Based ICU Ventilator Simulation|
Medical simulations have been broadly defined as a device or set of conditions that aims to imitate real patients, anatomic regions, or clinical tasks and/or to mirror the real life situations in which medical services are rendered.1 Simulations are not identical to real life events; rather, the simulation places the learner in life-like situations that provides immediate feedback about questions, decisions and actions. Work in educational and cognitive psychology suggests that simulation technology, when integrated into the curriculum, has the potential to enhance student achievement, particularly for those students for whom lecture, passive information gathering and linear thinking may not provide full engagement.2,3 Medical simulations vary in their fidelity. High fidelity medical simulations are able to recreate a patient and the intensive care unit environment in nearly every detail. These types of simulations are valuable for fostering communication, team building and interpersonal skills, and they provide powerful learning experiences that give learners an opportunity to examine their roles within a team.4 Due to their complexity, high fidelity manikin simulation laboratories are very costly to purchase, run and maintain.
Of necessity, simulation sessions are usually held during fixed laboratory schedules; thus students are usually not able to work through simulated cases after normal laboratory hours. The fidelity required for a particular application depends upon the specific goal thus the added gains of replicating reality with this level of precision may yield limited value.5,6 A simulation of lower fidelity may avoid the expense, operator intensiveness and time inflexibility of the manikin-based high fidelity simulations while emulating a real world event and providing immediate patient feedback. In this sense a simulation represents simplified reality and is free of the need to include every possible detail.7
|Figure 2: Mobile Device Simulated Patient Waveforms|
Students who are fortunate enough to have access to high-fidelity learning simulations often want the opportunity for a “do over” soon after encountering a scenario for the first time. This ability to try again, know formally as Rapid Cycle Deliberate Practice (RCDP), was associated with improved resuscitation skills in pediatric medical residents.8 When implemented in a high fidelity manikin laboratory, RCDP is time consuming and not always possible. But a computerized, learner-controlled simulation can easily allow for such deliberate practice. It can also allow for learning by selecting second and third answer choices just to see varying outcomes.
Simulations in Respiratory Care
A variety of lung simulators are available that connect to commercial mechanical ventilators and permit a student the opportunity to interact with a variety of common and uncommon physiologic states. These lung simulators vary in price and many of the more sophisticated models are capable of realistically duplicating commonly encountered normal and abnormal respiratory physiology. Similar to high fidelity medical manikins, most lung simulators and their necessary associated ventilators are available only during scheduled laboratory sessions due to concerns about cost and potential damage. Although valuable for large programs and laboratory sessions, the expense of the most sophisticated lung simulators and their inaccessibility to students outside of scheduled, staffed laboratory sessions have combined to limit their universal acceptance by all respiratory care training programs.
Screen-based healthcare simulations use a computer to represent selected visual and audio components of the environment and provide dynamic clinical data in real time from physiologic and pharmacologic models.9,10 Unlike high fidelity simulations that may require an ICU or hospital room, manikin and ventilator to recreate a hospital environment, screen-based simulations are software based and require only a computer to operate. This simplicity is reflected in their lower cost, and since the software can be loaded onto a personal computer, students may access the simulations at a variety of locations and times. A variety of screen-based medical simulations have been created including those for anesthesia, cardiopulmonary resuscitation, and respiratory care (Figure 1). While not physically connected to an actual ventilator as is a lung simulator, screen-based ventilation simulators are able to depict virtual controls and patient monitoring panels, are reasonably priced and have the advantage of portability, giving students the ability to use the ventilator as a learning opportunity and practice activity at times other than scheduled laboratory sessions. Adding to their flexibility, many screen-based simulations permit the instructor and students to create custom patient scenarios that highlight specific conditions and allow user groups to share the created patient files.
|Figure 3: Mobile Device Simulation Scenario|
Mobile Device Simulations
Capitalizing on the explosive proliferation of cell phones and tablets, a new generation of healthcare simulations engineered for mobile device platforms is emerging (Figure 2). These new simulations have the potential to revolutionize respiratory care education by providing students with the ability to learn and practice the discipline of mechanical ventilation almost anywhere. The portability of these devices permits the student to experience a wide range of normal and abnormal respiratory physiology and to experiment with a variety of ventilation settings on demand and even at the bedside.
Mobile device simulations have the ability to deliver a critical amount of core material to students prior to a scheduled lecture or other class activity and harvest student responses and treatment choices (Figures 3 and 4), thus providing the instructor with a pre-class snap shot of individual and class knowledge. The instructor is then able to tailor their subsequent class or laboratory session activity based upon student comprehension on the pre-class mobile simulation. This process whereby student pre-class comprehension is used to structure a subsequent presentation by the instructor is a proven educational strategy known as Just in Time Teaching (JiTT). Developed for physics education11,12 traditional JiTT requires students to read and complete carefully constructed exercises, covering material that has not yet been presented, and submit them electronically. Instructors subsequently review students’ pre-class responses and configure the upcoming classroom session.
|Figure 4: Mobile Device Treatment Questions|
Although the JiTT strategy is documented to increase student learning and is preferred by students compared with traditional lecture,13 the technique requires a substantial investment of both student and faculty time and effort. Noncompliance of students with pre-class assignments and increased faculty workload inherent in the technique have combined to limit the universal acceptance of this teaching and learning approach.14
The increasing computing power, ability to communicate, and portability of the current generation of tablets and smart phones makes them ideal candidates to deliver dynamic and reactive simulated patient waveforms as part of a JiTT strategy. Pre-class simulation scenarios incorporating dynamic, reactive ventilator waveforms are delivered to a student’s mobile device while completion notification and individual student responses to questions and treatment decisions are transmitted to the instructor.
The potential for learning and for providing instructor feedback with these teaching tools is tremendous and is limited only by our ability as educators to integrate this technology into the curriculum. In addition, the portability of these devices makes it possible for practitioners to take them to the bedside and predict a patient’s response to a change in ventilation settings. Mobile learning simulations can be valuable not only for learning and practicing new skills, but can be a very cost-effective way to provide refreshers for experienced staff on infrequent procedures and annual certifications.
Robert Keegan is an associate professor and Anesthesia Section Head in the College of Veterinary Medicine, Washington State University, Pullman, Wash. In 2014, Keegan founded WholeLogic LLC, a Health Care Simulation Software Company based upon IP generated during over 25 years of research and teaching experience. Keegan can be reached by email at email@example.com
Jonathan Waugh is faculty director of the Center for Teaching & Learning at the University of Alabama at Birmingham and a professor in the Respiratory Therapy Program of the Clinical and Diagnostic Sciences Department in the School of Health Professions, Birmingham, Ala.
1. Scalese RJ, et al. Effective use of simulations for the teaching and acquisition of veterinary professional and clinical skills. J Vet Med Educ 2005;32(4):461-467.
2. Pardue K, et al. Substantive innovation in nursing education: Shifting the emphasis from content coverage to student learning. Nursing Education Perspectives 2005;26:55-57.
3. Harder BN. Use of simulation in teaching and learning in health sciences: A systematic review. Journal of Nursing Education 2010;49(1):23-28.
4. Ker J, et al. Early introduction to interprofessional learning: a simulated ward environment. Med Educ 2003;37:248-55.
5. Smith BE, et al. Simulators. In Lake CL, Hines RL, Clitt CD editors. Clinical Monitoring. Practical applications for anesthesia and critical care. Philadelphia, WB Saunders; 2001:26-44.
6. Maran NJ, et al. Low to high fidelity simulation – a continuum of medical education? Medical Education 2003;37(suppl. 1):22-28.
7. Jones K. Simulations: A Handbook for Teachers. New York: Kogan Page-Nichols Publishing Company, 1980.
8. Hunt EA, et al. Pediatric resident resuscitation skills improve after “Rapid Cycle Deliberate Practice” training. Resuscitation. 2014. http://dx.doi.org/10.1016/j.resuscitation.2014.02.025.
9. Schwid HA, et al. Anesthesiologists’ management of simulated critical incidents. Anesthesiology 1992;76(4):495-501.
10. Gaba DB. Improving anesthesiologists’ performance by simulating reality. Anesthesiology 1992;76(4)491-494.
11. Novak GM, et al. Just-In-Time teaching. http://webphysics.iupui.edu/jitt/jitt.html, last modified 2006 (accessed April, 2014).
12. Novak GM, et al. Just-in-time teaching: Blending active learning with web technology. 1999. Upper Saddle River, NJ: Prentice Hall.
13. Marrs KA, et al. Just-in-time teaching in biology: creating an active learner classroom using the internet. CBE Life Sci.Educ. 2004;3, 49.
14. Moravec M, et al. Learn before Lecture: A strategy that improves learning outcomes in a large introductory biology class. CBE Life Sci Educ, 2010;9,473-481.