BackgroundAcute care providers intervening on fragile patients face many knowledge and information related challenges. Explanation based on causal chains of events has limitations when applied to complex physiological systems, and model-driven educational software may overwhelm the learner with information. We introduce a new concept and educational technology to facilitate understanding, reasoning, and communication in the clinical environment. The aim is to grasp complex physiology in a more intuitive way.Explanatory models (EM)An EM is a representation of relevant physiologic processes that provides insight into the relationships between therapeutic interventions and monitored variables, and their dependency on incidents and pathologies. We systematically analyze types of information incorporated into models and displayed in simulations and consider their explanatory relevance.Transposition of the great arteries (TGA)A conceptual model (diagram) of the normal neonatal cardiorespiratory system is adapted to reflect TGA and implemented in animated, interactive software.Illustration of educational useThe use of this model is illustrated via the explanation to pediatric residents of the relationships between blood pressures, blood flow rates, ventilation, oxygen saturation, and oxygen distribution in a neonate with TGA. Learners explore clinical scenarios and effects of therapeutic interventions.DiscussionExplanatory models hold promise as mental models for clinical practice and could possibly play a role in clinical decision making in neonatal intensive care and beyond.Companion softwareThe software is freely available via the web addendum: https://www.dropbox.com/sh/ciufq5rqxgs9bkt/AAC7oKsvkEr73eYUJkx0pZ1Ya?dl=0

Maintaining an optimal acid base is important for the patient. The theory underlying acid–base balance can be challenging for clinicians and educators. These considerations justify creating simulations that include realistic changes to the partial pressure of carbon dioxide, pH, and bicarbonate ion concentration in a range of conditions. Our explanatory simulation application requires a model that derives these variables from total carbon dioxide content and runs in real time. The presented model is derived from the Stewart model, which is based on physical and chemical principles, and takes into account the effects of weak acids and strong ions on the acid–base balance. An inventive code procedure allows for efficient computation. The simulation results match target data for a broad range of clinically and educationally relevant disturbances of the acid–base balance. The model code meets the real-time goals of the application and can be applied in other educational simulations. Python model source code is made available.