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One of the major challenges in pediatric intensive care is the detection of life-threatening health conditions under acute time constraints and performance pressure. This includes the assessment of pediatric organ dysfunction (OD) that demands extraordinary clinical expertise and the clinician's ability to derive a decision based on multiple information and data sources. Clinical decision support systems (CDSS) offer a solution to support medical staff in stressful routine work. Simultaneously, detection of OD by using computerized decision support approaches has been scarcely investigated, especially not in pediatrics.Objectives: The aim of the study is to enhance an existing, interoperable, and rule-based CDSS prototype for tracing the progression of sepsis in critically ill children by augmenting it with the capability to detect SIRS/sepsis-associated hematologic OD, and to determine its diagnostic accuracy.Methods: We reproduced an interoperable CDSS approach previously introduced by our working group: (1) a knowledge model was designed by following the commonKADS methodology, (2) routine care data was semantically standardized and harmonized using openEHR as clinical information standard, (3) rules were formulated and implemented in a business rule management system. Data from a prospective diagnostic study, including 168 patients, was used to estimate the diagnostic accuracy of the rule-based CDSS using the clinicians' diagnoses as reference.Results: We successfully enhanced an existing interoperable CDSS concept with the new task of detecting SIRS/sepsis-associated hematologic OD. We modeled openEHR templates, integrated and standardized routine data, developed a rule-based, interoperable model, and demonstrated its accuracy. The CDSS detected hematologic OD with a sensitivity of 0.821 (95% CI: 0.708-0.904) and a specificity of 0.970 (95% CI: 0.942-0.987).Conclusion: We could confirm our approach for designing an interoperable CDSS as reproducible and transferable to other critical diseases. Our findings are of direct practical relevance, as they present one of the first interoperable CDSS modules that detect pediatric SIRS/sepsis-associated hematologic OD.

Many physically demanding tasks require the help of a second person to avoid the otherwise harmful effects of musculoskeletal disorders when performing the task alone. The workforce in many domains, such as nursing care, is rapidly declining. Furthermore, complex repositioning tasks during patient care make it all the more difficult to find a simple solution. Therefore, robotic assistance could be a perfect fit to support this scenario. For this purpose, we conducted a study where 12 caregivers were given the task of repositioning a patient simulator (80 kg) within a nursing bed with the help of a robotic assistant. We measured the physical relief potential using muscle activity and force data while examining this human-robot collaboration problem with two different control approaches, namely a virtual reality-based and a rule-based robot control method. The results show that both methods effectively supported the chosen task with varied strengths and weaknesses. The main advantage of VR-based control is the ability to adapt to the situation and execute quickly (6.61 s), but this also results in higher acting robot forces (35.70 N). With the rule-based control variant, a lower speed of support can be noted on average (10.84 s), but better robot interaction forces (14.95 N) can be discovered in return.

This paper presents the concept and current workin progress of an android robot-patient for communication training of relatives of critically ill non-verbal patients with motor impairment. Additionally, this paper presents the initial results of a field study regarding the social interactions of a patient in need of out-of-hospital intensive care. Furthermore, the implementation of the ongoing development, different levels of abstractions of the android robot-patient and the subsequent training scenario are described. Subsequently, an initial simulation of an interaction mode is implemented, presented and compared to the actual patient’s behavior.

Digitization in the healthcare sector is an ongoing process in which it is necessary for success to turn those affected into participants. Many considerations are limited to addressing only physicians and nurses in the digitization of healthcare, neglecting the fact that the role of the computer scientist for the necessary digital infrastructures of care plays an equally important role. A common understanding and a common language is essential so that the designated roles can shape the digital transformation together in a meaningful way. The development of competencies in the field of medical informatics is a key prerequisite here. HiGHmeducation as part of the project HiGHmed of the Medical Informatics Initiative (MII) focuses on the nationwide development of eLearning courses to make the required medical informatics competencies for the digital transformation in healthcare accessible for various target groups. In this article, one of these courses is presented and evaluation results of 3 years of implementation are presented. The course of the Department of Medical Informatics Göttingen addresses the topic of clinical decision support systems.

Abstract: Digitalization offers many new opportunities to make learning and teaching more attractive, flexible, interesting and also more effective. However, the transition from traditional classroom teaching to digital teaching is also challenging. This chapter deals with concepts and techniques of digital teaching in academic and continuing education. It is intended as a practical guide to successfully delivering online courses. Its main part focuses on presenting a five-phase didactical framework starting from welcoming of the learners to summative assessment and course completion. The didactically motivated framework is linked with suitable tools of learning management systems (LMSs) to support the activities of the phases. Two real life course examples from medical informatics education illustrate how online courses can be set up based on the presented framework using the open-source LMSs Moodle and ILIAS. The chapter also addresses necessary skills for educators and learners for successful digital learning and discusses the specifics of digital teaching in continuing education.