Refine
Year of publication
Document Type
- Article (56) (remove)
Is part of the Bibliography
- yes (56)
Keywords
- COVID-19 (2)
- Evaluation (2)
- eHealth (2)
- health information technology (2)
- Bass model (1)
- Clinical handover (1)
- Common ground (1)
- Communication (1)
- Computerized patient records (1)
- Continuity of care (1)
Institute
- Fakultät WiSo (55)
Wirtschaftsinformatik und Medizinische Informatik gehören zu den sogenannten Bindestrich-Informatik-Fächern, die sich mit der Anwendung der Methoden und Erkenntnisse der Informatik, aber auch mit der Weiterentwicklung solcher Methoden und Erkenntnisse für gewisse Anwendungsgebiete befassen. Auf einer Podiumsdiskussion der Jahrestagung 2018 der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS) wurde für Wirtschaftsinformatik, Medizinische Informatik und Informatik analysiert wie sie zueinander stehen. Die Analyse erfolgte anhand von fünf Fragen:
1. Welche grundlegenden Ziele bestimmen die jeweilige wissenschaftliche Arbeit?
2. Wie ist der Praxisbezug ausgeprägt?
3. Inwieweit sind Besonderheiten von Medizin bzw. Ökonomie prägend für die jeweilige wissenschaftliche Arbeit?
4. Welche Rolle spielen Theoriefundierung und Evidenz?
5. Was können Wirtschaftsinformatik und Informatik von Medizinischer Informatik und Medizin lernen – und umgekehrt?
Die Analyse zeigt, dass die drei Disziplinen von einem systematischen wechselseitigen Austausch profitieren können. Das „Lernende Gesundheitssystem“ bietet Ansätze für einen entsprechenden Rahmen.
Das Thema Digitalisierung ist in aller Munde – gerade auch im Bereich Krankenhaus. Allerdings noch nicht zuverlässig und im großen Stile valuiert sind die Fragen: Wie digitalisiert ist die Gesamtheit der deutschen Krankenhäuser tatsächlich? Wie entwickelt sich der Digitalisierungsgrad über die Zeit und im Vergleich zu anderen Nationen? Welchen Maßstab sollte man anlegen? Die Autoren stellen im folgenden Artikel ihren Ansatz für eine bundesweite Erfassung der Krankenhausdigitalisierung vor. Im Ergebnis weisen die betrachteten Krankenhäuser deutliche Optimierungspotenziale auf. Diese reichen von der mobilen Verfügbarkeit elektronischer Patientendaten und IT-Funktionen bis hinzu Fragen der Integration und Interoperabilität der im Einsatz befindlichen Systeme.
Objectives: eHealth and innovation are often regarded as synonyms - not least because eHealth technologies and applications are new to their users. This position paper challenges this view and aims at exploring the nature of eHealth innovation against the background of common definitions of innovation and facts from the biomedical and health informatics literature. A good understanding of what constitutes innovative eHealth developments allows the degree of innovation to be measured and interpreted.
Methods: To this end, relevant biomedical and health informatics literature was searched mainly in Medline and ACM digital library. This paper presents seven facts about implementing and applying new eHealth developments hereby drawing on the experience published in the literature.
Results: The facts are: 1. eHealth innovation is relative. 2. Advanced clinical practice is the yardstick. 3. Only used and usable eHealth technology can give birth to eHealth innovatio. 4. One new single eHealth function does not make a complex eHealth innovation. 5. eHealth innovation is more evolution than revolution. 6. eHealth innovation is often triggered behind the scenes; and 7. There is no eHealth innovation without sociocultural change.
Conclusions: The main conclusion of the seven facts is that eHealth innovations have many ingredients: newness, availability, advanced clinical practice with proven outcomes, use and usability, the supporting environment, other context factors and the stakeholder perspectives. Measuring eHealth innovation is thus a complex matter. To this end we propose the development of a composite score that expresses comprehensively the nature of eHealth innovation and that breaks down its complexity into the three dimensions: i) eHealth adoption, ii) partnership with advanced clinical practice, and iii) use and usability of eHealth. In order to better understand the momentum and mechanisms behind eHealth innovation the fourth dimension, iv) eHealth supporting services and means, needs to be studied. Conceptualising appropriate measurement instruments also requires eHealth innovation to be distinguished from eHealth sophistication, performance and quality, although innovation is intertwined with these concepts. The demanding effort for defining eHealth innovation and measuring it properly seem worthwhile and promise advances in creating better systems. This paper thus intends to stimulate the necessary discussion.
Der zunehmende Einsatz von Informations- und Kommunikationstechnologie im Gesundheitswesen verlangt auch von Angehörigen der Pflegeberufe Kompetenzen zur Nutzung der entsprechenden Systeme und Verfahren. Vor diesem Hintergrund haben sich die AG „Informationsverarbeitung in der Pflege“ der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), die Österreichische Gesellschaft für Pflegeinformatik (ÖGPI) und die Schweizerische Interessensgruppe Pflegeinformatik (IGPI) innerhalb des Schweizer Berufsverband der Pflegefachfrauen und Pflegefachmänner (SBK) entschlossen, gemeinsame Empfehlungen für benötigte Kernkompetenzfelder in Pflegeinformatik zu erarbeiten. Auf Basis einer iterativen multimethodischen Vorgehensweise unter Einbeziehung von einer großen Anzahl von Fachexperten aus Deutschland, Österreich und der Schweiz (D-A-CH) wurden 24 notwendige Felder von Kernkompetenzen definiert und deren Relevanz für fünf typische Berufsfelder in der Pflege bewertet. Damit liegt erstmalig eine wissenschaftlich fundierte Empfehlung für zu vermittelnde Kernkompetenzfelder in der Pflegeinformatik für verschiedene pflegerische Berufsfelder vor. Sie richtet sich an alle Personen mit Verantwortung für die Planung von Studium, Lehre, Aus- und Weiterbildung in der Pflege.
Background and purpose:
Clinical information logistics is a construct that aims to describe and explain various phenomena of information provision to drive clinical processes. It can be measured by the workflow composite score, an aggregated indicator of the degree of IT support in clinical processes. This study primarily aimed to investigate the yet unknown empirical patterns constituting this construct. The second goal was to derive a data-driven weighting scheme for the constituents of the workflow composite score and to contrast this scheme with a literature based, top-down procedure. This approach should finally test the validity and robustness of the workflow composite score.
Methods:
Based on secondary data from 183 German hospitals, a tiered factor analytic approach (confirmatory and subsequent exploratory factor analysis) was pursued. A weighting scheme, which was based on factor loadings obtained in the analyses, was put into practice.
Results:
We were able to identify five statistically significant factors of clinical information logistics that accounted for 63% of the overall variance. These factors were “flow of data and information”, “mobility”, “clinical decision support and patient safety”, “electronic patient record” and “integration and distribution”. The system of weights derived from the factor loadings resulted in values for the workflow composite score that differed only slightly from the score values that had been previously published based on a top-down approach.
Conclusion:
Our findings give insight into the internal composition of clinical information logistics both in terms of factors and weights. They also allowed us to propose a coherent model of clinical information logistics from a technical perspective that joins empirical findings with theoretical knowledge. Despite the new scheme of weights applied to the calculation of the workflow composite score, the score behaved robustly, which is yet another hint of its validity and therefore its usefulness.
Information Technology (IT) continues to evolve and develop with electronic devices and systems becoming integral to healthcare in every country. This has led to an urgent need for all professions working in healthcare to be knowledgeable and skilled in informatics. The Technology Informatics Guiding Education Reform (TIGER) Initiative was established in 2006 in the United States to develop key areas of informatics in nursing. One of these was to integrate informatics competencies into nursing curricula and life-long learning. In 2009, TIGER developed an informatics competency framework which outlines numerous IT competencies required for professional practice and this work helped increase the emphasis of informatics in nursing education standards in the United States. In 2012, TIGER expanded to the international community to help synthesise informatics competencies for nurses and pool educational resources in health IT. This transition led to a new interprofessional, interdisciplinary approach, as health informatics education needs to expand to other clinical fields and beyond.
In tandem, a European Union (EU) - United States (US) Collaboration on eHealth began a strand of work which focuses on developing the IT skills of the health workforce to ensure technology can be adopted and applied in healthcare. One initiative within this is the EU*US eHealth Work Project, which started in 2016 and is mapping the current structure and gaps in health IT skills and training needs globally. It aims to increase educational opportunities by developing a model for open and scalable access to eHealth training programmes. With this renewed initiative to incorporate informatics into the education and training of nurses and other health professionals globally, it is time for educators, researchers, practitioners and policy makers to join in and ROAR with TIGER.
The TIGER Initiative
(2016)
Background:
Large health organizations often struggle to build complex health information technology (HIT) solutions and are faced with ever-growing pressure to continuously innovate their information systems. Limited research has been conducted that explores the relationship between organizations’ innovative capabilities and HIT quality in the sense of achieving high-quality support for patient care processes.
Objective:
The aim of this study is to explain how core constructs of organizational innovation capabilities are linked to HIT quality based on a conceptual sociotechnical model on innovation and quality of HIT, called the IQHIT model, to help determine how better information provision in health organizations can be achieved.
Methods:
We designed a survey to assess various domains of HIT quality, innovation capabilities of health organizations, and context variables and administered it to hospital chief information officers across Austria, Germany, and Switzerland. Data from 232 hospitals were used to empirically fit the model using partial least squares structural equation modeling to reveal associations and mediating and moderating effects.
Results:
The resulting empirical IQHIT model reveals several associations between the analyzed constructs, which can be summarized in 2 main insights. First, it illustrates the linkage between the constructs measuring HIT quality by showing that the professionalism of information management explains the degree of HIT workflow support (R²=0.56), which in turn explains the perceived HIT quality (R²=0.53). Second, the model shows that HIT quality was positively influenced by innovation capabilities related to the top management team, the information technology department, and the organization at large. The assessment of the model’s statistical quality criteria indicated valid model specifications, including sufficient convergent and discriminant validity for measuring the latent constructs that underlie the measures of HIT quality and innovation capabilities.
Conclusions:
The proposed sociotechnical IQHIT model points to the key role of professional information management for HIT workflow support in patient care and perceived HIT quality from the viewpoint of hospital chief information officers. Furthermore, it highlights that organizational innovation capabilities, particularly with respect to the top management team, facilitate HIT quality and suggests that health organizations establish this link by applying professional information management practices. The model may serve to stimulate further scientific work in the field of HIT adoption and diffusion and to provide practical guidance to managers, policy makers, and educators on how to achieve better patient care using HIT.
Background: While health informatics recommendations on competencies and education serve as highly desirable corridors for designing curricula and courses, they cannot show how the content should be situated in a specific and local context. Therefore, global and local perspectives need to be reconciled in a common framework.
Objectives: The primary aim of this study is therefore to empirically define and validate a framework of globally accepted core competency areas in health informatics and to enrich this framework with exemplar information derived from local educational settings.
Methods: To this end, (i) a survey was deployed and yielded insights from 43 nursing experts from 21 countries worldwide to measure the relevance of the core competency areas, (ii) a workshop at the International Nursing Informatics Conference (NI2016) held in June 2016 to provide information about the validation and clustering of these areas and (iii) exemplar case studies were compiled to match these findings with the practice. The survey was designed based on a comprehensive compilation of competencies from the international literature in medical and health informatics.
Results: The resulting recommendation framework consists of 24 core competency areas in health informatics defined for five major nursing roles. These areas were clustered in the domains “data, information, knowledge”, “information exchange and information sharing”, “ethical and legal issues”, “systems life cycle management”, “management” and “biostatistics and medical technology”, all of which showed high reliability values. The core competency areas were ranked by relevance and validated by a different group of experts. Exemplar case studies from Brazil, Germany, New Zealand, Taiwan/China, United Kingdom (Scotland) and the United States of America expanded on the competencies described in the core competency areas.
Conclusions: This international recommendation framework for competencies in health informatics directed at nurses provides a grid of knowledge for teachers and learner alike that is instantiated with knowledge about informatics competencies, professional roles, priorities and practical, local experience. It also provides a methodology for developing frameworks for other professions/disciplines. Finally, this framework lays the foundation of cross-country learning in health informatics education for nurses and other health professionals.