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While Nursing Informatics competencies seem essential for the daily work of nurses, they are not formally integrated into nursing education in Austria, Germany and Switzerland, nor are there any national educational recommendations. The aim of this paper is to show how such recommendations can be developed, what competency areas are most relevant in the three countries and how the recommendations can be implemented in practice. To this end, a triple iterative procedure was proposed and applied starting with national health informatics recommendations for other professionals, matching and enriching these findings with topics from the international literature and finally validating them in an expert survey with 87 experts and in focus group sessions. Out of the 24 compiled competency areas, the relevance ratings of the following four recommended areas achieved values above 90%: nursing documentation (including terminologies), principles of nursing informatics, data protection and security, and quality assurance and quality management. As there were no significant differences between the three countries, these findings laid the foundation of the DACH Recommendations of Nursing Informatics as joint German (D), Austrian (A), and Swiss (CH) recommendations in Nursing Informatics. The methodology proposed has been utilized internationally, which demonstrates the added value of this study also outside the confines of Austria, Germany, Switzerland.
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.
Background:
While aiming for the same goal of building a national eHealth Infrastructure, Germany and the United States pursued different strategic approaches – particularly regarding the role of promoting the adoption and usage of hospital Electronic Health Records (EHR).
Objective:
To measure and model the diffusion dynamics of EHRs in German hospital care and to contrast the results with the developments in the US.
Materials and methods:
All acute care hospitals that were members of the German statutory health system were surveyed during the period 2007–2017 for EHR adoption. Bass models were computed based on the German data and the corresponding data of the American Hospital Association (AHA) from non-federal hospitals in order to model and explain the diffusion of innovation.
Results:
While the diffusion dynamics observed in the US resembled the typical s-shaped curve with high imitation effects (q = 0.583) but with a relatively low innovation effect (p = 0.025), EHR diffusion in Germany stagnated with adoption rates of approx. 50% (imitation effect q = -0.544) despite a higher innovation effect (p = 0.303).
Discussion:
These findings correlate with different governmental strategies in the US and Germany of financially supporting EHR adoption. Imitation only seems to work if there are financial incentives, e.g. those of the HITECH Act in the US. They are lacking in Germany, where the government left health IT adoption strategies solely to the free market and the consensus among all of the stakeholders.
Conclusion:
Bass diffusion models proved to be useful for distinguishing the diffusion dynamics in German and US non-federal hospitals. When applying the Bass model, the imitation parameter needs a broader interpretation beyond the network effects, including driving forces such as incentives and regulations, as was demonstrated by this study.
Die Gesundheitstelematik unterstützt die Versorgungskontinuität und fördert damit die Patientensicherheit. In Anlehnung an den eArztbrief wurde an der FH Osnabrück der elektronische Pflegebericht entwickelt. Mit dem ePflegebe-richt leistet die Pflege einen ersten wichtigen Beitrag zur Gestaltung eigener gesundheitstelematischer Anwendungen.
Introduction: Establishing continuity of care in handovers at changes of shift is a challenging endeavor that is jeopardized by time pressure and errors typically occurring during synchronous communication. Only if the outgoing and incoming persons manage to collaboratively build a common ground for the next steps of care is it possible to ensure a proper continuation. Electronic systems, in particular electronic patient record systems, are powerful providers of information but their actual use might threaten achieving a common understanding of the patient if they force clinicians to work asynchronously. In order to gain a deeper understanding of communication failures and how to overcome them, we performed a systematic review of the literature, aiming to answer the following four research questions: (1a) What are typical errors and (1b) their consequences in handovers? (2) How can they be overcome by conventional strategies and instruments? (3) electronic systems? (4) Are there any instruments to support collaborative grounding?
Methods: We searched the databases MEDLINE, CINAHL, and COCHRANE for articles on handovers in general and in combination with the terms electronic record systems and grounding that covered the time period of January 2000 to May 2012.
Results: The search led to 519 articles of which 60 were then finally included into the review. We found a sharp increase in the number of relevant studies starting with 2008. As could be documented by 20 studies that addressed communication errors, omission of detailed patient information including anticipatory guidance during handovers was the greatest problem. This deficiency could be partly overcome by structuring and systematizing the information, e.g. according to Situation, Background, Assessment and Recommendation schema (SBAR), and by employing electronic tools integrated in electronic records systems as 23 studies on conventional and 22 articles on electronic systems showed. Despite the increase in quantity and quality of the information achieved, it also became clear that there was still the unsolved problem of anticipatory guidance and presenting “the full story” of the patient. Only a small number of studies actually addressed how to establish common ground with the help of electronic tools.
Discussion: The increase in studies manifests the rise of great interest in the handover scenario. Electronic patient record systems proved to be excellent information feeders to handover tools, but their role in collaborative grounding is unclear. Concepts of how to move to joint information processing and IT-enabled social interaction have to be implemented and tested.
Background: Clinical handovers at changes of shifts are typical scenarios of time restricted and information intensive communication, which are highly cognitively demanding. The currently available applications supporting handovers typically present complex information in a textual checklist-like manner. This presentation style has been criticised for not meeting the specific user requirements.
Objectives: We, therefore, aimed at developing a concept for visualising the overview of a clinical case that serves as an alternative way to checklist-like presentations in clinical handovers. We also aimed at implementing this concept in a handoverEHR in order to support the pre-handover phase, the actual handover, and the post-handover phase as well as at evaluating its usability and attractiveness.
Results: We developed and implemented a concept that draws on Tolman's pioneering work on cognitive maps that we designed in accordance with Gestalt principles. These maps provide a pictorial overview of a clinical case. The application to build, manipulate, and store the cognitive maps was integrated into an openEHR based handover record that extends conventional records with handover specific information. Usability (n = 28) and attractiveness (n = 26) testing with experienced clinicians resulted in good ratings for suitability for the task as well as for attractiveness and pragmatism.
Conclusion: We propose cognitive maps to represent and visualise the clinical case in situations where there is limited time to present complex information.
The demand for evidence-based health informatics and benchmarking of 'good' information systems in health care gives an opportunity to continue reporting on recent papers in the German journal GMS Medical Informatics, Biometry and Epidemiology (MIBE) here. The publications in focus deal with a comparison of benchmarking initiatives in German-speaking countries, use of communication standards in telemonitoring scenarios, the estimation of national cancer incidence rates and modifications of parametric tests. Furthermore papers in this issue of MIM are introduced which originally have been presented at the Annual Conference of the German Society of Medical Informatics, Biometry and Epidemiology. They deal as well with evidence and evaluation of 'good' information systems but also with data harmonization, surveillance in obstetrics, adaptive designs and parametrical testing in statistical analysis, patient registries and signal processing.
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.