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Introduction: The experience of a second victim phenomenon after an event plays a significant role in health care providers’ well-being. Untreated; it may lead to severe harm to victims and their families; other patients; hospitals; and society due to impairment or even loss of highly specialised employees. In order to manage the phenomenon, lifelong learning is inevitable but depends on learning motivation to attend training. This motivation may be impaired by overconfidence effects (e.g., over-placement and overestimation) that may suggest no demand for education. The aim of this study was to examine the interdependency of learning motivation and overconfidence concerning second victim effects. Methods: We assessed 176 physicians about overconfidence and learning motivation combined with a knowledge test. The nationwide online study took place in early 2022 and addressed about 3000 German physicians of internal medicine. Statistics included analytical and qualitative methods. Results: Of 176 participants, 83 completed the assessment. Analysis showed the presence of two overconfidence effects and in-group biases (clinical tribalism). None of the effects correlated directly with learning motivation, but cluster analysis revealed three different learning types: highly motivated, competent, and confident “experts”, motivated and overconfident “recruitables”, and unmotivated and overconfident “unawares”. Qualitative analysis revealed four main themes: “environmental factors”, “emotionality”, “violence and death”, and “missing qualifications” contributing to the phenomenon. Discussion: We confirmed the presence of overconfidence in second victim management competencies in about 3% of all persons addressed. Further, we could detect the same three learning motivation patterns compared to preceding studies on learning motivation in other medical competencies like life support and infection control. These findings considering overconfidence effects may be helpful for safety managers, medical teachers, curriculum developers and supervisors to create preventive educational curricula on second victim recognition and management.

Background and aimThere are no investigations on hand hygiene during cardiopulmonary resuscitation (CPR), even though these patients are at high risk for healthcare-associated infections. We aimed to evaluate the number of indicated hand hygiene per CPR case in general and the fraction that could be accomplished without delay for other life-saving techniques through standardized observations.Materials and methodsIn 2022, we conducted Advanced Cardiovascular Life Support (ACLS) courses over 4 days, practicing 33 ACLS case vignettes with standard measurements of chest compression fractions and hand hygiene indications. A total of nine healthcare workers (six nurses and three physicians) participated.ResultsA total of 33 training scenarios resulted in 613 indications for hand disinfection. Of these, 150 (24%) occurred before patient contact and 310 (51%) before aseptic activities. In 282 out of 310 (91%) indications, which have the highest impact on patient safety, the medication administrator was responsible; in 28 out of 310 (9%) indications, the airway manager was responsible. Depending on the scenario and assuming 15 s to be sufficient for alcoholic disinfection, 56–100% (mean 84.1%, SD ± 13.1%) of all indications could have been accomplished without delaying patient resuscitation. Percentages were lower for 30-s of exposure time.ConclusionTo the best of our knowledge, this is the first study investigating the feasibility of hand hygiene in a manikin CPR study. Even if the feasibility is overestimated due to the study setup, the fundamental conclusion is that a relevant part of the WHO indications for hand disinfection can be implemented without compromising quality in acute care, thus increasing the overall quality of patient care.

Disconcerting reports from different EU countries during the first wave of the COVID-19 pandemic demonstrated the demand for supporting decision instruments and recommendations in case tertiary triage is needed. COVID-19 patients mainly present sequentially, not parallelly, and therefore ex-post triage scenarios were expected to be more likely than ex-ante ones. Decision-makers in these scenarios may be highly susceptible to second victim and moral injury effects, so that reliable and ethically justifiable algorithms would have been needed in case of overwhelming critical cases.To gather basic information about a potential tertiary triage instrument, we designed a three-dimensional instrument developed by an expert group using the Delphi technique. The instrument focused on three parameters: 1) estimated chance of survival, 2) estimated prognosis of regaining autonomy after treatment, and 3) estimated length of stay in the ICU. To validate and test the instrument, we conducted an anonymous online survey in 5 German hospitals addressing physicians that would have been in charge of decision-making in the case of a mass infection incident. Of about 80 physicians addressed, 47 responded. They were presented with 16 fictional ICU case vignettes (including 3 doublets) which they had to score using the three parameters of the instrument.We detected a good construct validity (Cronbach’s Alpha 0.735) and intra-reliability (p < 0.001, Cohens Kappa 0.497 to 0.574), but a low inter-reliability (p < 0.001, Cohen’s Kappa 0.252 to 0.327) for the three parameters. The best inter-reliability was detected for the estimated length of stay in the ICU. Further analysis revealed concerns in assessing the prognosis of the potentially remaining autonomy, especially in patients with only physical impairment.In accordance with German recommendations, we concluded that single-rater triage (which might happen in stressful and highly resource-limited situations) should be avoided to ensure patient and health care provider safety. Future work should concentrate on reliable and valid group decision instruments and algorithms and question whether the chance of survival as a single triage parameter should be complemented with other parameters, such as the estimated length of stay in the ICU.

Background: Paediatric emergencies are challenging for healthcare workers, first aiders, and parents waiting for emergency medical services to arrive. With the expected rise of virtual assistants, people will likely seek help from such digital AI tools, especially in regions lacking emergency medical services. Large Language Models like ChatGPT proved effective in providing health-related information and are competent in medical exams but are questioned regarding patient safety. Currently, there is no information on ChatGPT’s performance in supporting parents in paediatric emergencies requiring help from emergency medical services. This study aimed to test 20 paediatric and two basic life support case vignettes for ChatGPT and GPT-4 performance and safety in children. Methods: We provided the cases three times each to two models, ChatGPT and GPT-4, and assessed the diagnostic accuracy, emergency call advice, and the validity of advice given to parents. Results: Both models recognized the emergency in the cases, except for septic shock and pulmonary embolism, and identified the correct diagnosis in 94%. However, ChatGPT/GPT-4reliably advised to call emergency services only in 12 of 22 cases (54%), gave correct first aid instructions in 9 cases (45%) and incorrectly advised advanced life support techniques to parents in 3 of 22 cases (13.6%). Conclusion: Considering these results of the recent ChatGPT versions, the validity, reliability and thus safety of ChatGPT/GPT-4 as an emergency support tool is questionable. However, whether humans would perform better in the same situation is uncertain. Moreover, other studies have shown that human emergency call operators are also inaccurate, partly with worse performance than ChatGPT/GPT-4in our study. However, one of the main limitations of the study is that we used prototypical cases, and the management may differ from urban to rural areas and between different countries, indicating the need for further evaluation of the context sensitivity and adaptability of the model. Nevertheless, ChatGPT and the new versions under development may be promising tools for assisting lay first responders, operators, and professionals in diagnosing a paediatric emergency. Trial registration: not applicable