[ChatGPT for use in technology-enhanced learning in anesthesiology and emergency medicine and potential clinical application of AI language models : Between hype and reality around artificial intelligence in medical use]. / ChatGPT im Einsatz für "technology-enhanced learning" in Anästhesiologie und Notfallmedizin und potenzielle klinische Anwendung von KI­Sprachmodellen : Zwischen Hype und Wirklichkeit um künstliche Intelligenz im medizinischen Einsatz.

BACKGROUND: The utilization of AI language models in education and academia is currently a subject of research, and applications in clinical settings are also being tested. Studies conducted by various research groups have demonstrated that language models can answer questions related to medical board examinations, and there are potential applications of these models in medical education as well. RESEARCH QUESTION: This study aims to investigate the extent to which current version language models prove effective for addressing medical inquiries, their potential utility in medical education, and the challenges that still exist in the functioning of AI language models. METHOD: The program ChatGPT, based on GPT 3.5, had to answer 1025 questions from the second part (M2) of the medical board examination. The study examined whether any errors and what types of errors occurred. Additionally, the language model was asked to generate essays on the learning objectives outlined in the standard curriculum for specialist training in anesthesiology and the supplementary qualification in emergency medicine. These essays were analyzed afterwards and checked for errors and anomalies. RESULTS: The findings indicated that ChatGPT was able to correctly answer the questions with an accuracy rate exceeding 69%, even when the questions included references to visual aids. This represented an improvement in the accuracy of answering board examination questions compared to a study conducted in March; however, when it came to generating essays a high error rate was observed. DISCUSSION: Considering the current pace of ongoing improvements in AI language models, widespread clinical implementation, especially in emergency departments as well as emergency and intensive care medicine with the assistance of medical trainees, is a plausible scenario. These models can provide insights to support medical professionals in their work, without relying solely on the language model. Although the use of these models in education holds promise, it currently requires a significant amount of supervision. Due to hallucinations caused by inadequate training environments for the language model, the generated texts might deviate from the current state of scientific knowledge. Direct deployment in patient care settings without permanent physician supervision does not yet appear to be achievable at present.

Bedside teaching without bedside - an introduction to clinical reasoning in COVID-19 times.

Introduction: The Corona virus pandemic rendered most live education this spring term impossible. Many classes were converted into e-learning formats. Teaching at the bedside (BST) seemed unfeasible under the circumstances. BST and clinical reasoning as its major outcome is introduced at the beginning of semester 5, henceforth all BST refers to this first presentation. Project outline: To ensure proficiency of current 5th semester students in future BST sessions, the introduction could not be cancelled albeit teaching with patients was. Knowing that the practical learning objectives of bedside teaching cannot be mirrored in online formats, a compensating module to teach the concept of BST and clinical reasoning had to be designed. Summary of work: To facilitate an understanding of the concept of bedside teaching with a focus on clinical reasoning we developed paper cases and a survey in Microsoft Forms following the history and examination path used in live BST with the addendum of clinical reasoning tables. For the first paper case, a personal feedback was provided for the clinical reasoning tables. A sample solution was provided later for self-feedback on the whole case. The first case was completed by 87, the second by 40 of 336 students. Response to individual feedback was positive. Students still missed hands-on training in history taking and examination with patients. Discussion: Paper cases cannot fully substitute BST. However, given the prime directive during the pandemic to protect our patients, this module engaged around one third of the cohort. The review of uploaded clinical reasoning tables gave proof to the sufficient students' grasp of clinical reasoning. Conclusion: Albeit not an exhaustive substitute for BST, this online module seems a feasible way to convey clinical reasoning strategies to students.

Social distancing in advanced emergency medicine courses - can it work?

Introduction: The corona virus pandemic rendered most live education this spring term impossible. Many classes were converted into e-learning formats. But not all learning content and outcomes can readily be transferred into digital space. Project outline: Emergency medicine teaching relies on hands-on simulation training. Therefore, we had to devise a catalogue of measures, that would enable us to offer simulation training for Advanced Life Support. Summary of work: Strict hygienic rules including disinfection of hands, wearing personal protective gear at all times and disinfection of equipment were implemented. Group size and number of staff was reduced, introducing fixed student teams accompanied by the same teacher. Only large rooms with good ventilation were used. Under these conditions, we were allowed to carry out core Advanced Life Support simulations. Other content had to be transferred to online platforms. Discussion: Heeding general hygiene advise and using personal protective gear, a central cluster of simulations was carried out. Students and staff adhered to rules without complaint. No infections within faculty or student body were reported. Conclusion: It seems feasible to conduct core simulations under strict hygienic protocol.

Can we adequately teach ethics and ethical decision making via distant learning? A pandemic pilot.

The Corona virus pandemic rendered most live education this spring term impossible. Other formats and new ideas were needed to offer students the opportunity to learn unchanged learning content and outcomes. To replace our module on ethics and ethical decision making in emergency medicine with simulation patients we developed an e-learning module consisting of a case, trigger questions and literature for self-study. This was followed by a Microsoft Teams seminar in which the students discussed their questions in subgroups on the basis of their reading and developed a team product they then presented to the other team. Students valued this module as enabling a safe space for their beliefs and views. A vast majority deemed the topics as relevant, two thirds would retake the seminar. Despite a productive online discourse, this format should not be used as sole module under normal conditions since it lacks the (simulation) patient interaction but it can prove to be a valuable addendum to live teaching.