TeamSTEPPS^®Simulator

The first time learners use Bodyswaps, this onboarding sequence familiarises them with the features of the app, takes them through an avatar selection and embodiment activity, and prepares them for the experience to come.

In the onboarding, learners will:

• Find out how this training is different from the rest
• Select their avatar
• Discover their virtual journal
• Learn how to navigate and use the tools and settings

After the onboarding activity, the learner meets their virtual coach, Nurse Sam, in the central nursing station at Summerview Hospital. She talks about how much she loves collaborating with different professions in her role, but it comes with all sorts of challenges. 

The learner is then invited to answer a few quick multiple-choice questions about how they feel doing collaborative tasks – like sharing patient information, raising concerns, and taking the lead in emergencies. This encourages self-reflection and activates working memory to prepare them for the simulations to come. 

After the questions, Sam explains that TeamSTEPPS^® can help healthcare teams to collaborate more effectively, and handle the challenges she mentioned. It can reduce the risk of medical errors, improve the standard of care, and make the team feel better connected. That’s why she runs this simulation at Summerview Hospital: so nurses have a safe space to practice using key TeamSTEPPS^® tools.

But learners don’t need to worry if they aren’t familiar with the tools. This simulation will help them discover how the tools can help them.  

Sam also says she’ll be reviewing their performance throughout the simulation. She’ll provide feedback along the way and in the debrief at the end.  

Now, the learner’s first shift is about to start. But before they go, Sam shows them her messaging system, which she’ll use this throughout the module to send the learner helpful guidance and feedback. 

This topic begins with the learner watching a conversation between Kevin, Joanna, and triage nurse Tala in Summerview’s reception. This helps set the scene for the learner and prepares them for the upcoming activity. 

Kevin is seated nearby while Joanna tells Tala why they’re here: Kevin is struggling with a racing heart, head rushes, and feeling out of breath. As Joanna finishes explaining, Kevin starts feeling dizzy – and faints.

Moving on, the learner finds themselves at Kevin’s bedside, where they take on the role of his admitting nurse. Nurse Sam messages them with details about Kevin’s diagnosis, current vitals, and next steps. 

Now, the learner’s goal is to provide Charge Nurse Zachary with a clear and concise update about Kevin’s condition using the TeamSTEPPS^® tool SBAR. 

The learner does this by speaking in their own words. Behind the scenes, AI technology analyzes their response to determine whether they’re following the SBAR method appropriately.

After one of a possible three different replies from Zachary, the learner can retry their response or move on. Once they proceed, Nurse Sam gives feedback about their performance, and awards them an ‘SBAR badge’ if they successfully used the technique.

It’s the learner’s next shift, and the topic begins with them watching Dr Huan wrap up a conversation with Kevin. Dr Huan explains that the learner is going to coordinate his discharge as the supporting nurse.

Dr Huan then outlines Kevin’s treatment and discharge plan to the learner, such as his medication needs and when to return for a follow up appointment. 

To move the activity forwards, the learner must then select one of three options: 

1. Got it, thank you Huan.
2. Could you repeat all that for me please? 
3. Can I confirm those details with you Huan?

A moves the learner straight onto Nurse Sam’s feedback at the end of the topic. B repeats Huan’s explanation, before returning to the three options. 

C prompts the learner to speak in their own voice, and their goal is to use the TeamSTEPPS^® tool Check-Back in their response.  

As they speak, AI technology analyses if they’re checking back all the key details that Huan shared. The learner elicits different replies from Huan, such as him correcting any details they get wrong, or confirming if what they said is correct. They can choose to redo their answer if they want to practice again. 

Before moving onto the next topic, the learner receives another concluding message from Nurse Sam about their performance, and a ‘Check-Back badge’ if they successfully checked back all the key details.

The next patient the learner meets is Emmanuel, a Spanish-speaking man with a bad cough. The learner watches as Dr Grace examines him, with Emmanuel’s son-in-law Derek providing basic interpretation. When Dr Grace leaves to order medication, the learner sees Emmanuel coughing up blood.

Nurse Sam sends the learner a message, wondering if Dr Grace got a full picture of Emmanuel’s condition, and asks them what they want to do. The learner respond with one of the following options: 

1. I shouldn’t get involved – Dr Grace knows best.
2. I should ask Dr Grace if we got enough information.
3. I should raise a concern with Dr Grace.

A moves the learner straight onto Nurse Sam’s feedback at the end of the topic. B prompts Dr Grace to say that she thinks they have a pretty full picture, and the learner then returns to the three options. 

The ideal response is option C. This prompts them to speak to Dr Grace in their own words, giving them the opportunity to use the TeamSTEPPS® tool CUS to raise a concern about Emmanuel’s bleeding and the language barrier. Behind the scenes, AI technology checks if they correctly applied the CUS method.

Dr Grace responds differently depending on whether or not the learner used CUS. The learner can then try again, if they wish. Once they move on, Nurse Sam provides feedback about their performance, and awards them with a ‘CUS badge’ if they succeeded.

In this activity, the learner faces two scenarios: one where they receive team support and one where they give it. 

In the first scenario, Nurse Sam lets the learner know it’s time for lunch, but they still have outstanding tasks. They need to seek support from Charge Nurse Tala to redistribute their workload. In the second scenario, the learner must decide whether or not to proactively offer team support when they have some spare time, and decide how to respond when Nurse Peter asks for assistance with his patient, Melaina.

When speaking to Tala and Peter, the learner’s goal is to choose affirming or proactive responses, which follow the principles of the TeamSTEPPS^® tool Task Assistance. Each response they choose has a score based on whether it would uplift or diminish team morale. 

Peter and Tala respond differently depending on the learner’s choices. Affirming, proactive responses elicit positive reactions. But diminishing or self-focused ones annoy or upset them, reducing the team’s sense of camaraderie.

The learner can also choose options that avoid asking for or offering help altogether. Charge Nurse Tala identifies that the learner needs support, even if they choose not to seek her help, meaning they still have a chance to interact with her. However, declining to assist Nurse Peter takes them straight to the end of the activity, skipping their opportunity to practice talking to him. 

When the learner reaches the end of the activity, the final score from all their responses is tallied. This determines the feedback they now receive from Nurse Sam, and whether or not she awards them a ‘Task Assistance’ badge. They must choose all the best responses to achieve this badge. 

This topic opens with the learner witnessing patient Zhuri falling unconscious. Nurse Sam guides the learner through some pop-up interactions to raise the alarm, check her pulse, and discover that she’s gone into cardiac arrest. 

The response team of Tala, Zachary, and Peter arrive, and Nurse Sam prompts a ‘time out’ to prepare the learner for the upcoming activity. She tells them it’s time to lead the resuscitation effort as the situational leader, and then provides some details about the three primary roles that need fulfilling: chest compressions, airway management, and defibrillation pads. 

The learner is now prompted to speak aloud to talk to Tala, Zachary, and Peter. Their goal is to follow the principles of the TeamSTEPPS^® tool Call-Out and assign the three primary roles to the team. 

As the learner speaks, AI analyzes if they’re successfully achieving this goal. Once they finish giving their response to the team, Tala, Zachary, and Peter will respond accordingly – either confirming their assigned role, or sounding uncertain about what to do. 

If the learner is unsuccessful at assigning the roles, Nurse Sam offers feedback and a hint about the role of a situational leader, then invites them to try again if they wish. If the learner succeeds in using Call-Out for all the roles, Sam will congratulate them and award them with a ‘Call-Out badge’.

The learner’s time at Summerview Hospital comes to a close, and they rejoin Nurse Sam back in the central nursing station to debrief. She firstly offers some concluding thoughts about how challenging the last few shifts must have felt, and congratulates them for making it through. 

Next, she provides the learner with an overall TeamSTEPPS^® ranking, based on how many of the tools they successfully used: 

• Expert: All 5 
• Competent: 4 or 3 
• Advanced Beginner: 2 or 1
• Novice: 0 

A pop-up panel then displays the TeamSTEPPS^® badges, indicating which ones they achieved, and the learner can select which they’d like to receive feedback about. For each one, Sam talks through the learner’s outcome, providing thoughts on where they did well and where they could improve.

For example, if they successfully used the TeamSTEPPS^® tool SBAR during Topic 1, she’ll congratulate them and reiterate the power of using the tool. But if they didn’t, she’ll offer advice about how using SBAR could’ve made their patient update more clear and concise. 

This feedback will then be accessible beyond the simulation in a personalized learner report, helping you as the tutor or facilitator to see which TeamSTEPPS^® tools the learner used well and which they’d benefit from practicing further. 

As the debrief draws to an end, Sam congratulates them once again and reminds them they can come back to the simulation to practice anytime.