Introduction

Clinical teaching (CT) involves learning how to relate with patients, family members and other professionals, think about diagnoses, take a history from a patient, analyze situations in daily practice and discuss treatment plans, focused on providing students with the opportunity to learn clinical skills and professional competences¹. Nowadays, many factors hinder activities related to quality CT: advances in knowledge and new technologies², cost structure and the different approaches to managing health systems and subsystems, overcrowding in universities, overlapping of medical practice and teaching activities of healthcare workers, and patient safety measures. All these factors limit the opportunities of medical students to “learn in practice”, in terms of time and quality. At first, simulation seems to mitigate some of these effects. Its benefits rely on a solid basis of repetitive experience, reflection, student-centered learning and patient safety. Simulation can be considered as a teaching activity for a particular skill in parallel to CT, or as a substitution of part of the time devoted to it¹.

However, the current COVID-19 pandemic poses additional challenges to CT by affecting the normal development of onsite activities. In particular, medical schools are facing serious difficulties in implementing clinical teaching, which requires a real working environment: the hospital, the practice, the healthcare center or their own simulation centers.

We need solutions to mitigate these effects and to answer questions including how to continue learning and acquiring competencies in terms of knowledge, skills and attitudes with virtual lessons. Virtual simulation, remote simulation or telesimulation (TS) is defined as the reality represented through a screen and is widely accepted by these new generations of digital natives³. This broad definition covers a variety of systems using different technologies to meet different needs. Virtual patient education provides an active way of learning that seems to be beneficial for the development of clinical reasoning (CR) skills. These complex systems are made up of highly developed technologies, but there is still a lack of exploratory evidence on the usefulness or impact of the different variants and the possible combinations of them. The aim of this study is to present a TS strategy and analyze the instructional design perspective of undergraduate students of surgery.

Material and methods

The INSPIRE Simulación Femeba teaching team developed a pilot program of TS in collaboration with the faculty of the Chair of Surgery “D” of the School of Medical Sciences of UNLP, adapting the method to a clinical teaching activity. Twenty-six students participated in a usual training session of the specialty immersed in a virtual scenario in which they could interact with a manikin simulator, experience and analyze critical situations and make decisions for the development of a therapeutic plan.

The students were divided into two groups of 13 participants each and logged into an online communication platform (Google Meet^®, Google LLC^®) from their homes. A simulation technician, hereinafter “the avatar”, spoke in first person from the simulation center (INSPIRE Simulación Femeba) using a mobile phone, while a simulation instructor along with the faculty members of the chair observed the scenario and provided the information required by those students who participated as healthcare workers. The avatar represented the eyes, hands and ears of the students within the scenarios and the voice of the patient when required. The faculty members completed the performance checklist within the scenarios using the simulation center management software LearningSpace Enterprise^® (LS) (CAE Healthcare Inc), and also provided direct feedback during the analysis phase.

Briefly, a combination of manikin simulator (Apollo^®, CAE Healthcare Inc), software, mobile phone and video conferencing platform allowed for immersion in advanced clinical simulation scenarios aimed at training CR and non-technical skills (NTS) (Fig. 1). This required spending more time on pre-briefing and briefing about the simulation environment and practice context than in normal (onsite) situations, to understand the interactions of all the actors, the technology used, ensure fiction and confidentiality contracts, and communicate the learning objectives.

Figure 1 Instructional design: example view of students in observer mode with patient monitoring of first-person (A) and view of students immersed in the scenario (B). 

A case of acute cholangitis was presented to the students and divided into three scenarios: low complexity, transfer and high complexity. The design and dynamics of the activity determined the progression of the case from a low complexity to a high complexity scenario. The learning targets were established in “key points” under the categories of CR and NTS. Of the 13 students in each group, 6 students participated actively, 2 for each scenario, who shared the avatar, while the others participated as observers of the situation through the peripheral vision offered by the LS.

That is, each pair of participants was assigned an avatar intended to promote shared decision-making and a “think backwards”⁴ approach, for a shared understanding of reasoning. The PEARLS framework was used for debriefing⁵ using a plus-delta technique, in which technical performance gaps such as CR were addressed through self-assessment, peer evaluation and directive feedback provided by the educators. Those gaps related with human factors were approached by the instructor using the inquiry-advocacy technique⁶. Each clinical simulation experience -briefing, simulation and debriefing- lasted one hour. Finally, a satisfaction survey was carried out.

Data analysis was carried out using a quantitative-qualitative approach, focusing on the participants’ experiences during the activity and trying to provide a comprehensive description of their experience. The satisfaction survey, the transcriptions made during debriefing, an open-ended question from the satisfaction survey (What suggestions would you make to the educators to improve it in the future?) and a final questionnaire with an open-ended question corresponding to the conclusions of the activity (What do you think you have learned from this activity and how do you think this experience has helped to make it happen?) were considered. The transcriptions were analyzed based on categories that correspond to the previously established “key points” aimed at analyzing the activity in terms of the learning opportunities and attributes of the method as perceived by the students (Table 1). Encoding was performed using an Excel^® spreadsheet (Microsoft Corporation). Although the participants were divided into two groups, they will be considered as a single group for the objective of this study

Table 1 

Results

Of the 23 students, 15 responded the satisfaction survey. The activity exceeded the expectations of 64% the respondents and met the expectations of 34%. The workload was very demanding in 18%, moderately demanding in 46% and not very demanding in 36% of the respondents. The time available was sufficient for 73% and insufficient for 27%. All the students considered that the content of the activity was relevant and 91% responded that they learned a lot (in contrast, 9% responded that they did not learn a lot). All of them would recommend the activity to other peers.

The analysis of the qualitative data suggests at least two dimensions: one related with the “learning opportunity” and the other one with the teaching technique. Two categories are outstanding within the first dimension: clinical reasoning and non-technical skills. The category “telesimulation” stands out in the second dimension.

Discussion

Telesimulation is a technique that has grown in popularity since the pandemic and, although the evidence on the usefulness of the different design variants is lacking, it is feasible and constitutes a reasonable alternative to onsite simulation⁷. As the results obtained by McCoy et al.⁸ indicate, students stated that the TS allowed them to better embed knowledge about patient care and that the experience gave them added value above and beyond the knowledge provided by just reading the content.

Among the learning targets we should highlight CR, understood as the combination of clinical information and medical knowledge to generate a diagnosis and a therapeutic plan, which is complex, dynamic and uncertain. The theory that knowledge is linked to certain factors such as activity, social rules, context and culture, means that healthcare workers can think about different aspects of the same case to solve problems⁹. It implies understanding that problems are inherently human and, therefore, diverse, unorganized, tacit and fraught with uncertainty, where reasoning shifts from being merely clinical to “practical”. By thinking that clinical problems are human we are accepting the existence of certain interactions that emerge during medical practice and that mostly correspond to NTS, as expressed in our experience during the peer review and included as learning targets of the activity. One problem of the lack of awareness of these skills is that one tends to overestimate one’s performance during self-assessment¹⁰, although it would seem that this is not the case when we place ourselves in the external role of observer.

A relevant statement states that simulation or TS is the excuse to debrief¹¹. This type of assessment shapes skills and knowledge through feedback, and helps develop the professional identity through the social interaction that occurs in conversations¹². Good surgeons should be good learners and treat debriefing as an opportunity to learn and improve¹³.

In conclusion, TS, as a learning opportunity, promotes the development of practical reasoning, which considers clinical problems as human and therefore complex problems characterized by disorder, uncertainty and interactions. It considers the context and social construction of knowledge. Although TS can achieve high fidelity as a technique, it cannot neglect the technical and technological aspects that would alter its course.

Among the criticisms of analyzing students’ perspectives on a given teaching strategy is that they only generate qualitative data. We wonder if “human” problems can or should be quantified. “Not everything that can be counted counts and not everything that counts can be counted¹⁴” but everything can be told.