[Education for resuscitation]. / Lehre in der Reanimation: Leitlinien des European Resuscitation Council 2021.

These European Resuscitation Council education guidelines are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. This section provides guidance to citizens and healthcare professionals with regard to teaching and learning the knowledge, skills and attitudes of resuscitation with the ultimate aim of improving patient survival after cardiac arrest.

European Resuscitation Council Guidelines 2021: Education for resuscitation.

These European Resuscitation Council education guidelines, are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. This section provides guidance to citizens and healthcare professionals with regard to teaching and learning the knowledge, skills and attitudes of resuscitation with the ultimate aim of improving patient survival after cardiac arrest.

Education, Implementation, and Teams: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations.

For this 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations, the Education, Implementation, and Teams Task Force applied the population, intervention, comparator, outcome, study design, time frame format and performed 15 systematic reviews, applying the Grading of Recommendations, Assessment, Development, and Evaluation guidance. Furthermore, 4 scoping reviews and 7 evidence updates assessed any new evidence to determine if a change in any existing treatment recommendation was required. The topics covered included training for the treatment of opioid overdose; basic life support, including automated external defibrillator training; measuring implementation and performance in communities, and cardiac arrest centers; advanced life support training, including team and leadership training and rapid response teams; measuring cardiopulmonary resuscitation performance, feedback devices, and debriefing; and the use of social media to improve cardiopulmonary resuscitation application.

Improving Fluid Management in Critical Care - Towards the ICU of the Future.

BACKGROUND: The calculation of daily fluid balances is essential in perioperative and postoperative fluid management in order to prevent severe hypervolemia or hypovolemia in critically ill patients. In this context, modern health information technology has the potential to reduce the workload for health care professionals by not only automating data collection but also providing appropriate decision support. OBJECTIVES: Within this work, current problems and barriers regarding fluid balancing in cardiac intensive care patients are outlined and improvement activities are specified. METHODS: Literature research and qualitative interviews with health care professionals were conducted to assess the state-of-the-art technological setting within an intensive care unit. RESULTS: An example case shows that interconnecting not only devices but also wards can facilitate daily clinical tasks. CONCLUSION: Smart devices and decision support systems can improve fluid management. Several technologies, which today are sometimes still considered to be futuristic, are in fact not that far away or already available. However, they need proper implementation with respect to intensivists', nurses' and patients' needs.

Development of a Clinical Decision Support System in Intensive Care.

BACKGROUND: Intensive care is confronted with an increasing complexity and large amounts of data provided by new technological tools. One way of assisting health care professionals is providing effective clinical decision support (CDS) systems. OBJECTIVES: The aim is to develop a tailored model for the sustainable development of a clinical decision support system in intensive care. METHODS: The model consists of two parts. The first part includes the interaction of the following partners: science industry and HCP. The second part comprises a three-phase process consisting of (1) the identification of clinical needs, (2) modeling and prototyping, and (3) implementation. RESULTS: By July 2015, a government funded CDS development project started in Graz, Austria. After assigning a multi-professional and interdisciplinary team, a clinical need statement was formulated within the first six months. A prototype was developed by end of 2016 and verified using a clinical dataset. CONCLUSION: The developed model proofed to be feasible regarding the first two phases. Additional progress needs to made to assess the performance of the model in the implementation phase.