June 25, 2020By Dr. Kim Baily

INACSL 2020 Day 1 Session Recap: RRT Algorithm Development Through Simulation & Context Based Learning

The INACSL 2020 Virtual Conference is in full swing this week as nursing simulation educators from around the world come together online to network and engage with the latest in best practices. HealthySimulation.com staff writer Dr. Kim Baily PhD, MSN, RN, CNE, previous Simulation Coordinator for Los Angeles Harbor College and Director of Nursing for El Camino College, responded to two presentations from day 1 of the International Nursing Association for Clinical Simulation and Learning event!

The INACSL Conference is a leading forum for simulation aficionados, researchers, and vendors providing the ideal environment to gain and disseminate current, state-of-the-art knowledge in the areas of skills/simulation operations and applications in an evidenced-based venue. Healthcare professionals will have the opportunity to network with colleagues and exhibitors, discuss best practices as relates to competencies, safety and quality performance indicators, and advance the science of simulation.


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The Development of Pediatric Rapid Response Algorithms Through Simulation: A Formula for Success by D. Bracken, and M. Burch, B. Hall  from the Intermountain Healthcare (IMH) Simulation Consortium in Utah which serves 24 rural and urban locations.

Care of the deteriorating pediatric patient varied at each facility and interventions were not standardized. Availability of pediatricians and pediatric hospitalists varied per facility, especially those in rural areas. Rapid Response nurses were often adult-focused and had little experience caring for pediatric patients. These deficits led to inconsistent, inappropriate, or delays in pediatric patient care. Using a shared mental model, evidence-based rapid response algorithms and problem-specific interventions were developed. Kotter’s “8 Steps To Transforming Your Organization” were used as a basis for the development:

Step One, Create Urgency: Intermountain Healthcare already knew they had an existing problem. The variety of institutions within the system, the lack of standardization throughout the system, the lack of consistency of team membership, the use of staff with experience in adult rapid response but not pediatric response and known serious events all contributed to the identification of an existing problem. Goals included creating algorithms that could be initiated by either a physician or a nurse and to empower nurses to act when physicians were not available. They began by reviewing the literature and although found data to support the use of Rapid Response Teams (RRTs), they could not find data to support using a shared mental model to develop algorithms.

Step Two, Form a Powerful Coalition: The coalition consisted in a diverse group of staff with experience in simulation, education, internal medicine, emergency medicine, pediatric and PICU nursing and resuscitation. The team worked well together and supported each other.


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Step Three, Create a Vision for Change: The multidisciplinary team developed a shared mental model. This is key for a plan to be successful because when team members have a shared understanding of the task that is to be performed, team performance improves. Since IMH already had an existing policy for adult rapid response, they decided to use this as a basis but to adapt it for pediatric use. They were concerned that any pediatric booklet that was developed should look sufficiently different so that it would not be confused with an adult version. A white board was used to develop ideas which were then transferred to more formal diagrams. Input was sought from all team members during this process.

Step Four, Communicate the Vision: IMH shared their vision with relevant departments and institutions throughout the entire process by using simulation, education and show and tell. Early versions were shared on the floors and with existing RRTs. Then theses versions were taken on the road throughout Utah to 13 out of 22 facilities. The final algorithms were tested at the large children’s hospital simulation lab with representatives of all stakeholders. Algorithms were tested again and again in the simulation lab and were then updated to ensure that they contained evidence-based practice and best standardized care. Simulation provided an invaluable tool for refining the algorithms. In situ simulation provided information on logistics and potential environmental and process issues.

Step Five, Remove Obstacles: The presenters noted that this was probably the most difficult step as the whole organization underwent a restructuring which created difficulties for determining who was responsible for the project and where funding was coming from. However, all 22 facilities medical executive committees finally approved the algorithms. At this point the algorithms were added to electronic health records and charting.

Step Six, Create Short-Term Wins:It is important to demonstrate the advantages of the new process by creating some short-term wins. Shorter term targets are also useful tools for motivation and direction. Using these wins to justify investment and effort can help to re-motivate staff to continue backing the change.

Step Seven, Build on the Change: Creation of order sets for pediatric RRTs. Empowerment of nurses to initiate RRT.

Step Eight, Institutionalizing New Approaches. This step was crucial to empower staff and create a “no fault” culture for initiating a pediatric rapid response. Sharing data with staff was also part of this step.

Much of the remainder of this presentation related to the details of the various algorithms which have been integrated and are in use corporation wide. Simulation was invaluable in the development and testing of the pediatric rapid response algorithms and order sets. Through simulation, latent threats were identified early and corrected prior to implementation, decreasing the risk for human error and improving patient safety. Simulation provided effective team training opportunities in the implementation of a new evidence-based process. The success of this project has the potential to save pediatric patient lives across the IMH system. Healthcare simulation played a significant role in the successful development of the algorithms and order sets.

Context Based Learning: Flipping the Classroom to the Simulation Lab by Wagner, R. and Catalano, L. from the University of Cincinnati.

The preparation-to-practice gap, exhibited by lack of practice readiness, is widening; only 23% of new graduate nurses demonstrate entry-level competence and are unable to use academic knowledge in the practice settings. Context-based learning may bridge that gap by improving critical thinking skills and by increasing the reality of abstract didactic concepts. Learning is an active process that occurs when learners are actively involved in a process of meaning and knowledge construction as opposed to passively receiving the information. Wagner and Catalano suggest that information presented in a traditional classroom often miss context and learners cannot relate isolated bits of information to the clinical setting. Learners do not innately understand how to connect individual “dots” of information and relate them to patients. The authors believe this contributes to the practice gap of new graduates.

They designed a simulation using a Backward Design Method/Technique which starts with the end in mind i.e. starts by identifying the learning objectives and then creates learning activities to enable students to reach the learning outcomes. The chosen subject for the study related to knowledge of the interventions, diagnoses and medications needed to care for patients with Acute Coronary Syndrome (ACS). Using the INACSL Simulation Scenario Design Standard, the authors designed a simulation scenario in which the faculty will assume the role of a clinical nurse and care for the patient with ACS.

Activities were planned based on what the students already knew and what new knowledge related to ACS which would be covered in the simulation. Learners were required to complete prebriefing reading assignments related to the care the patient with ACS including relevant pharmacology. The authors noted that fidelity and authenticity are not the same and that high tech does not necessarily equate to high fidelity. An authentic learning environment provides a context that reflects the knowledge and skills that will be used in an actual patient care situation.

Twenty-one second-degree students in a medical-surgical course module completed an ACS simulation where the patient experienced chest pain and myocardial infarction while the instructor cared for him. The simulation used a Sim Man which was progressed from admission through treatment and discharge, including complications and post-intervention care. All the students observed the simulation at the same time. Students were able to interact with the instructor, who periodically paused the simulation to interact and question the rationale for various clinical interventions.

Students were highly engaged throughout the simulation, and informal feedback was 100% positive on this learning strategy. Exam results on the content showed 17% improvement as compared to the previous semester with the same content but were with a more traditional classroom learning strategy. Bringing didactic content to simulation is a learning strategy that engages students more effectively than traditional classes activities. The authors suggest that smaller groups might be more effective and that standardized patients could be used instead of manikin-based simulation.

There’s still time to register to watch these recorded sessions so…

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