The impact of sensor-enhanced regional health information systems

The expected economic impact of new health enabling technologies is often used as motivation for their development. Another motivation is the predicted positive impact on health care in general. The objective of this paper is to give a simple example for an economic calculation based on statistical data. A positive effect on health care in general can only be gained if the new technologies are sustainably integrated in health care processes

Early Career Support for Biomedical Exchange Students with an International Mentor-to-Mentor Concept - The Biomedical Education Program (BMEP)

In medicine, many international exchange opportunities exist, yet often only towards the end of the course of study. Opportunities for students to gain high-level international research experience early during the studies are rare. A good student-mentor relationship during a research stay abroad is a key factor for scientific success. The aims of this paper are to report on an international exchange and education program that has funded more than 700 students and has been carefully developed and advanced over more than 40 years, its mentor-to-mentor concept and potential success factors for building and maintain such programs. A summary of the history, the concept and the experiences of students is provided, along with a discussion of evaluation results and success factors. The Biomedical Education Program (BMEP) team has - within the last seven years of leadership by the authors - selected and funded 83 German students from different biomedical studies who went abroad for research projects. Preliminary evaluation results show a high degree of satisfaction with the program and its mentor-to-mentor concept, which we deem to be the key to success. Further factors include continued funding, determination, self-organization and assertiveness, an excellent alumni network and a meticulous selection process for both, students and hosts. Further, more detailed evaluation of survey results has to follow. Our results may support the build-up of similar exchange programs

Komplexitätssteigerung medizinischer Entscheidungssituationen - Herausforderungen der Digitalisierung erkennen und gestalten

The opportunities and limits of digitalisation for medical decision-making situations have been discussed heavily so far regarding to the potentials of single technologies and digital tools. Following sociological perspectives, which understand medical decision-making as socially embedded and hybrid, we show central structural challenges of digitalisation in clinical decision-making situations and develop recommendations for action for practice. If the structural challenges of digitalisation can be overcome positively, sustainable opportunities for improving medical decision-making situations through digitalisation will open up. With this integrative perspective, it is possible to avoid narrowing down to individual technologies and idealising decision-making situations, to anticipate unintended consequences and to open up perspectives for medium- and long-term quality improvements. © 2022 Georg Thieme Verlag. All rights reserved.Die Chancen und Grenzen der Digitalisierung für medizinische Entscheidungssituationen werden bislang stark in Bezug auf die Potenziale einzelner Technologien und digitaler Tools diskutiert. Im Anschluss an soziologische Perspektiven, die medizinisches Entscheiden als sozial eingebettet und hybrid verstehen, zeigen wir zentrale strukturelle Herausforderungen der Digitalisierung in klinischen Entscheidungssituationen auf und entwickeln Handlungsempfehlungen für die Praxis. Gelingt es, strukturelle Herausforderung der Digitalisierung positiv zu bewältigen, eröffnen sich nachhaltige Möglichkeiten zur Verbesserung medizinischer Entscheidungssituationen durch Digitalisierung. Mit dieser integrativen Perspektive gelingt es, Engführungen auf einzelne Technologien und Idealisierungen von Entscheidungssituationen zu vermeiden, nichtintendierte Folgen zu antizipieren und Perspektiven für mittel- und langfristige Qualitätssteigerungen zu eröffnen

Using openEHR Archetypes for Automated Extraction of Numerical Information from Clinical Narratives

Up to 80% of medical information is documented by unstructured data such as clinical reports written in natural language. Such data is called unstructured because the information it contains cannot be retrieved automatically as straightforward as from structured data. However, we assume that the use of this flexible kind of documentation will remain a substantial part of a patient’s medical record, so that clinical information systems have to deal appropriately with this type of information description. On the other hand, there are efforts to achieve semantic interoperability between clinical application systems through information modelling concepts like HL7 FHIR or openEHR. Considering this, we propose an approach to transform unstructured documented information into openEHR archetypes. Furthermore, we aim to support the field of clinical text mining by recognizing and publishing the connections between openEHR archetypes and heterogeneous phrasings. We have evaluated our method by extracting the values to three openEHR archetypes from unstructured documents in English and German language

Facilitating Inter-Domain Synergies in Ambient Assisted Living Environments

Current Ambient Assisted Living (AAL) environments lack integration of sensors and actuators of other sub-domains. Creating technical and organizational integration is addressed by the BASIS project (Build Automation by a Scalable and Intelligent System), which aims to build a cross-domain home bus system. The main objective of this paper is to present an overview of design, architecture and state of realization of BASIS by describing the requirements development process, underlying hardware design and software architecture. We built a distributed system of one independent building manager with several redundantly meshed segment controllers, each controlling a bus segment with any number of bus nodes. The software system layer is divided into logical partitions representing each sub-domain. Structured data storage is possible with a special FHIR based home centered data warehouse. The system has been implemented in six apartments running under daily living conditions. BASIS integrates a broad range of sub-domains, which poses challenges to all project partners in terms of a common terminology, and project management methods, but enables development of inter-domain synergies like using the same sensor and actuator hardware for a broad range of services and use cases

INBED: A Highly Specialized System for Bed-Exit-Detection and Fall Prevention on a Geriatric Ward

OBJECTIVE:In geriatric institutions, the risk of falling of patients is very high and frequently leads to fractures of the femoral neck, which can result in serious consequences and medical costs. With regard to the current numbers of elderly people, the need for smart solutions for the prevention of falls in clinical environments as well as in everyday life has been evolving. METHODS:Hence, in this paper, we present the Inexpensive Node for bed-exit Detection (INBED), a comprehensive, favourable signaling system for bed-exit detection and fall prevention, to support the clinical efforts in terms of fall reduction. The tough requirements for such a system in clinical environments were gathered in close cooperation with geriatricians. RESULTS:The conceptional efforts led to a multi-component system with a core wearable device, attached to the patients, to detect several types of movements such as rising, restlessness and-in the worst case-falling. Occurring events are forwarded to the nursing staff immediately by using a modular, self-organizing and dependable wireless infrastructure. Both, the hardware and software of the entire INBED system as well as the particular design process are discussed in detail. Moreover, a trail test of the system is presented. CONCLUSIONS:The INBED system can help to relieve the nursing staff significantly while the personal freedom of movement and the privacy of patients is increased compared to similar systems

Improving mental well-being in psychocardiology—a feasibility trial for a non-blended web application as a brief metacognitive-based intervention in cardiovascular disease patients

Background: Many patients with cardiovascular disease also show a high comorbidity of mental disorders, especially such as anxiety and depression. This is, in turn, associated with a decrease in the quality of life. Psychocardiological treatment options are currently limited. Hence, there is a need for novel and accessible psychological help. Recently, we demonstrated that a brief face-to-face metacognitive therapy (MCT) based intervention is promising in treating anxiety and depression. Here, we aim to translate the face-to-face approach into digital application and explore the feasibility of this approach. Methods: We translated a validated brief psychocardiological intervention into a novel non-blended web app. The data of 18 patients suffering from various cardiac conditions but without diagnosed mental illness were analyzed after using the web app over a two-week period in a feasibility trial. The aim was whether a non-blended web app based MCT approach is feasible in the group of cardiovascular patients with cardiovascular disease. Results: Overall, patients were able to use the web app and rated it as satisfactory and beneficial. In addition, there was first indication that using the app improved the cardiac patients’ subjectively perceived health and reduced their anxiety. Therefore, the approach seems feasible for a future randomized controlled trial. Conclusion: Applying a metacognitive-based brief intervention via a non-blended web app seems to show good acceptance and feasibility in a small target group of patients with CVD. Future studies should further develop, improve and validate digital psychotherapy approaches, especially in patient groups with a lack of access to standard psychotherapeutic care

Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups

<p>Abstract</p> <p>Background</p> <p>Hospital in-patient falls constitute a prominent problem in terms of costs and consequences. Geriatric institutions are most often affected, and common screening tools cannot predict in-patient falls consistently. Our objectives are to derive comprehensible fall risk classification models from a large data set of geriatric in-patients' assessment data and to evaluate their predictive performance (aim#1), and to identify high-risk subgroups from the data (aim#2).</p> <p>Methods</p> <p>A data set of n = 5,176 single in-patient episodes covering 1.5 years of admissions to a geriatric hospital were extracted from the hospital's data base and matched with fall incident reports (n = 493). A classification tree model was induced using the C4.5 algorithm as well as a logistic regression model, and their predictive performance was evaluated. Furthermore, high-risk subgroups were identified from extracted classification rules with a support of more than 100 instances.</p> <p>Results</p> <p>The classification tree model showed an overall classification accuracy of 66%, with a sensitivity of 55.4%, a specificity of 67.1%, positive and negative predictive values of 15% resp. 93.5%. Five high-risk groups were identified, defined by high age, low Barthel index, cognitive impairment, multi-medication and co-morbidity.</p> <p>Conclusions</p> <p>Our results show that a little more than half of the fallers may be identified correctly by our model, but the positive predictive value is too low to be applicable. Non-fallers, on the other hand, may be sorted out with the model quite well. The high-risk subgroups and the risk factors identified (age, low ADL score, cognitive impairment, institutionalization, polypharmacy and co-morbidity) reflect domain knowledge and may be used to screen certain subgroups of patients with a high risk of falling. Classification models derived from a large data set using data mining methods can compete with current dedicated fall risk screening tools, yet lack diagnostic precision. High-risk subgroups may be identified automatically from existing geriatric assessment data, especially when combined with domain knowledge in a hybrid classification model. Further work is necessary to validate our approach in a controlled prospective setting.</p

Ansätze zur interaktiv-antizipierenden Exploration dreidimensionaler medizinischer Bildobjekte

Softcover, 108 S.: 13,00 €InhaltAbbildungen Tabellen1 Einleitung und Motivation2 Grundlagen der Verarbeitung, Visualisierung und Exploration dreidimensionaler medizinischer Bilddaten2.1 Techniken der Verarbeitung und Visualisierung von Volumendatensätzen2.1.1 Rendering Parameter2.1.2 Segmentierung2.1.3 Rendering Algorithmen2.1.3.1 Maximum Intensity Projection (MIP)2.1.3.2 Shaded Surface Display2.1.3.3 Volume Rendering2.1.4 Möglichkeiten der dreidimensionalen Darstellung von Bilddaten2.1.4.1 Stereoskopie2.1.4.2 Dynamische Darstellungen2.2 Konzepte zur Exploration medizinischer Volumendatensätze2.2.1 Die herkömmliche Exploration von Volumendatensätzen2.2.2 Interaktive Exploration mit Unterstützung einer Grafik-Workstation2.2.3 virtusMED – eine interaktive Mensch-Maschine-Schnittstelle2.3 Die Bedeutung der inhaltlichen Antizipation bei der Exploration medizinischer Bilddaten3 Wissensrepräsentation in der Medizin3.1 Der Begriff des Wissens3.2 Medizinisches Wissen3.2.1 Explizites medizinisches Wissen3.2.2 Implizites medizinisches Wissen – Tacit Knowledge3.3 Grundlagen der Wissensrepräsentation in der Medizin3.3.1 Modellierung der Wissensbasis - Ontologien3.3.1.1 Kausale Ontologien3.3.1.2 Taxonomische Ontologien3.3.2 Formale Darstellungsformen von Semantik und Wissensstrukturen3.3.2.1 Semantische Netzwerke (nach Sowa)3.3.2.1.1 Definitional Networks3.3.2.1.2 Assertional Networks – konzeptuelle Graphen3.3.2.1.3 Weitere Formen semantischer Netzwerke3.3.2.2 RDF/XML – Das Semantic Web von Berners-Lee3.3.2.3 Knowledge Interchange Format (KIF)3.3.2.4 Web Ontology Language (OWL)3.3.2.5 GALEN Representation and Integration Language (GRAIL)3.3.2.6 Formalized English (FE) und Frame-Conceptual-Graphs (FCG)3.3.3 Inferenzmodelle3.4 Ausgewählte Ansätze zur ontologiebasierten anatomischen Wissensrepräsentation in der Medizin3.4.1 Das GALEN/ GALEN-IN-USE Projekt3.4.2 Der Digital Anatomist von Rosse et al.3.4.3 Das symbolisch-räumliche Modell von Schubert3.5 Der Einsatz wissensbasierter Systeme in der Medizin für die Interpretation und Exploration medizinischer Bilddaten3.5.1 Bildanalyse- und Bildsuchsysteme3.5.2 Agentensysteme4 Konzeption eines wissensbasierten Software-Systems zur antizipierenden Exploration dreidimensionaler medizinischer Bilddaten4.1 Die Entwicklung eines Konzeptes für eine wissensbasierte interaktive Explorations- und Lernoberfläche für die Interpretation dreidimensionaler medizinischer Bilddaten4.1.1 Überblick über das Systemkonzept4.1.2 Beschreibung der Systemkomponenten4.1.2.1 Die ontologische Wissensbasis4.1.2.2 Die Bild- und Explorationsdatenbank4.1.2.3 Der Explorationsrecorder und –player4.1.2.4 Das Explorations- und Lernmodul4.1.2.4.1 Kognitionspsychologische und lerntheoretische Grundlagen4.1.2.4.2 Konzeption des Explorations- und Lernmoduls4.1.2.5 Die Visualisierung des Explorationspfades4.2 Anwendungsbeispiel: Exploration von Calcaneusfrakturen4.2.1 Medizinische Grundlagen der Calcaneusfraktur4.2.1.1 Die Anatomie des Calcaneus4.2.1.2 Der Frakturmechanismus4.2.1.3 Die Frakturformen und entstehende Fragmente4.2.1.4 Die Frakturklassifikation4.2.1.4.1 Die Klassifikation nach Sanders4.2.1.4.2 Die Klassifikation nach Zwipp4.2.2 Die Relevanz dreidimensionaler Darstellungen in der Diagnostik von Calcaneusfrakturen4.2.3 Beispiel einer antizipierenden Exploration einer Calcaneusfraktur durch einen Experten4.2.4 Vorschlag eines prototypischen Explorationspfades4.2.5 Die Umsetzung des entwickelten Systemkonzeptes in eine Softwarelösung: Calcaneus Fracture Diagnostics4.2.5.1 Darstellung der verwendeten Technologien4.2.5.2 Darstellung der Anwendungsfälle als UML Use Cases4.2.5.3 Beschreibung der Anwendung Calcaneus Fracture Diagnostics4.2.5.3.1 Die Klasse MainFrame4.2.5.3.2 Die Klasse KnowledgeBase4.2.5.3.3 Die Klasse InferenceMachine4.2.5.3.4 Die Klasse VisualizationModule4.2.6 Ergebnisse5 Diskussion und Ausblick6 LiteraturverzeichnisAnhangA Die ontologische Wissensbasis der Calcaneusfraktur-DomäneB Darstellung der Calcaneusfraktur-Ontologie in der Ontology Web Language (OWL)Softcover, 17x24Bei der Arbeit mit modernen bildgebenden Verfahren wie der Computertomographie (CT) und der Magnetresonanztomographie (MRT) fallen täglich gigantische Mengen von medizinischen Bilddaten an. Diese Technologien bieten den Vorteil, dass die exakte sowie detaillierte Visualisierung fundiertere und damit bessere diagnostische sowie therapeutische Entscheidungen ermöglichen kann. Eine der Hauptaufgaben der Medizinischen Informatik ist die Verarbeitung der anfallenden Rohdaten und deren Aufbereitung in anschauliches Bildmaterial, das vom Mediziner interpretierbar ist. Das vorliegende Buch befasst sich mit den Möglichkeiten der Verarbeitung und Visualisierung von medizinischen Bildobjekten. Neue Ansätze für eine adäquatere und effektivere Nutzung der Daten werden vorgestellt und das Potential der verschiedenen Kombinationsalternativen von Bilddaten und medizinischem Wissen geprüft. Dazu werden zunächst die Grundlagen der Verarbeitung und Exploration medizinischer Bilddaten referiert. Herkömmliche und moderne Ansätze werden diskutiert und auf die Frage hin untersucht, ob sie eine Exploration im eigentlichen Wortsinn - nämlich die »Ausforschung« - gestatten. Ebenso werden das Wesen des medizinischen Wissens und die Grundlagen seiner Repräsentation dargestellt. Dabei wird insbesondere auf die speziellen Probleme eingegangen, welche eine derart komplexe und hochdynamische Wissensdomäne aufwirft. Schließlich wird ein neuer Ansatz vorgestellt, welcher die Exploration medizinischer Bilddaten unter Berücksichtigung von spezifischem Domänenwissen ermöglichen soll. Das entwickelte Systemkonzept wird in Form einer Anwendung aus der Unfallchirurgie exemplarisch umgesetzt. Die Diskussion der Ergebnisse und der Ausblick auf zukünftige Entwicklung runden diese Veröffentlichung ab