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Hintergrund
Demografisch bedingt wird sich die Anzahl pflegebedürftiger Menschen weiter erhöhen. Tragende Säule der pflegerischen Versorgung sind ihre Angehörigen, die den Großteil der Pflegeaufgaben übernehmen. Dies hat jedoch oftmals Auswirkungen auf ihre eigene Gesundheit und ihr Wohlbefinden.
Methodisches Vorgehen
Mit dem Fragebogen zur Angehörigenresilienz und -belastung (FARBE) liegt ein Instrument vor, um sowohl die Resilienz als auch Belastung pflegender Angehöriger zu ermitteln. Der Fragebogen wurde im Rahmen der Pflegestudie des VdK-Sozialverbands genutzt und von 12.475 Angehörigen komplett ausgefüllt. Durch eine multiple lineare Regression wurden Einflüsse und ihre Wirkstärke auf die Resilienz und Belastung analysiert.
Ergebnisse
Angehörige von Menschen mit Demenz, Depression oder hohem Pflegegrad weisen eine stärkere Belastung auf. Demenz und Depression mindern zudem die Resilienz. Positiv wirkt sich die soziale Unterstützung aus. Ebenso bedingt ein höheres Alter eine stärkere Resilienz.
Schlussfolgerungen
Im Ergebnis dieser Arbeit gelang eine Identifikation von relevanten Einflussfaktoren. Dies ermöglicht, Unterstützungs- und Entlastungsangebote auf ihre Anwendung und Wirksamkeit zu überprüfen. Besondere Bedeutung haben Unterstützungsangebote für Angehörige von Menschen mit Demenz, Depression und/oder höheren Pflegegraden. Stressreduzierende Maßnahmen und das Bilden sozialer Netzwerke für Angehörige können weitere Maßnahmen zur Stärkung der Resilienz und Abschwächung von Belastung sein.
The PosiThera project focuses on the management of chronic wounds, which is multi-professional and multi-disciplinary. For this context, a software prototype was developed in the project, which is intended to support medical and nursing staff with the assistance of artificial intelligence. In accordance with the user-centred design, national workshops were held at the beginning of the project with the involvement of domain experts in wound care in order to identify requirements and use cases of IT systems in wound care, with a focus on AI. In this study, the focus was on involving nursing and nursing science staff in testing the software prototype to gain insights into its functionality and usability. The overarching goal of the iterative testing and adaptation process is to further develop the prototype in a way that is close to care.
Diabetic foot ulcer (DFU) is a chronic wound and a common diabetic complication as 2% – 6% of diabetic patients witness the onset thereof. The DFU can lead to severe health threats such as infection and lower leg amputations, Coordination of interdisciplinary wound care requires well-written but time-consuming wound documentation. Artificial intelligence (AI) systems lend themselves to be tested to extract information from wound images, e.g. maceration, to fill the wound documentation. A convolutional neural network was therefore trained on 326 augmented DFU images to distinguish macerated from unmacerated wounds. The system was validated on 108 unaugmented images. The classification system achieved a recall of 0.69 and a precision of 0.67. The overall accuracy was 0.69. The results show that AI systems can classify DFU images for macerations and that those systems could support clinicians with data entry. However, the validation statistics should be further improved for use in real clinical settings. In summary, this paper can contribute to the development of methods to automatic wound documentation.
Venous leg ulcers and diabetic foot ulcers are the most common chronic wounds. Their prevalence has been increasing significantly over the last years, consuming scarce care resources. This study aimed to explore the performance of detection and classification algorithms for these types of wounds in images. To this end, algorithms of the YoloV5 family of pre-trained models were applied to 885 images containing at least one of the two wound types. The YoloV5m6 model provided the highest precision (0.942) and a high recall value (0.837). Its mAP_0.5:0.95 was 0.642. While the latter value is comparable to the ones reported in the literature, precision and recall were considerably higher. In conclusion, our results on good wound detection and classification may reveal a path towards (semi-) automated entry of wound information in patient records. To strengthen the trust of clinicians, we are currently incorporating a dashboard where clinicians can check the validity of the predictions against their expertise.
Background:
Chronic health conditions are on the rise and are putting high economic pressure on health systems, as they require well-coordinated prevention and treatment. Among chronic conditions, chronic wounds such as cardiovascular leg ulcers have a high prevalence. Their treatment is highly interdisciplinary and regularly spans multiple care settings and organizations; this places particularly high demands on interoperable information exchange that can be achieved using international semantic standards, such as Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT).
Objective:
This study aims to investigate the expressiveness of SNOMED CT in the domain of wound care, and thereby its clinical usefulness and the potential need for extensions.
Methods:
A clinically consented and profession-independent wound care item set, the German National Consensus for the Documentation of Leg Wounds (NKDUC), was mapped onto the precoordinated concepts of the international reference terminology SNOMED CT. Before the mapping took place, the NKDUC was transformed into an information model that served to systematically identify relevant items. The mapping process was carried out in accordance with the ISO/TR 12300 formalism. As a result, the reliability, equivalence, and coverage rate were determined for all NKDUC items and sections.
Results:
The developed information model revealed 268 items to be mapped. Conducted by 3 health care professionals, the mapping resulted in moderate reliability (κ=0.512). Regarding the two best equivalence categories (symmetrical equivalence of meaning), the coverage rate of SNOMED CT was 67.2% (180/268) overall and 64.3% (108/168) specifically for wounds. The sections general medical condition (55/66, 83%), wound assessment (18/24, 75%), and wound status (37/57, 65%), showed higher coverage rates compared with the sections therapy (45/73, 62%), wound diagnostics (8/14, 57%), and patient demographics (17/34, 50%).
Conclusions:
The results yielded acceptable reliability values for the mapping procedure. The overall coverage rate shows that two-thirds of the items could be mapped symmetrically, which is a substantial portion of the source item set. Some wound care sections, such as general medical conditions and wound assessment, were covered better than other sections (wound status, diagnostics, and therapy). These deficiencies can be mitigated either by postcoordination or by the inclusion of new concepts in SNOMED CT. This study contributes to pushing interoperability in the domain of wound care, thereby responding to the high demand for information exchange in this field. Overall, this study adds another puzzle piece to the general knowledge about SNOMED CT in terms of its clinical usefulness and its need for further extensions.
Restricted Versus Unrestricted Search Space : Experience from Mining a Large Japanese Database
(2015)
The aim of this study was to investigate whether standard Big Data mining methods lead to clinically useful results. An association analysis was performed using the apriori algorithm to discover associations among co-morbidities of diabetes patients. Selected data were further analyzed by using k-means clustering with age, long-term blood sugar and cholesterol values. The association analysis led to a multitude of trivial rules. Cluster analysis detected clusters of well and badly managed diabetes patients both belonging to different age groups. The study suggests the usage of cluster analysis on a restricted space to come to meaningful results.
Innovations are typically characterised by their relative newness for the user. In order for new eHealth applications to be accepted as innovations more criteria were proposed including “use” and “usability”. The handoverEHR is a new approach that allows the user to translate the essentials of a clinical case into a graphical representation, the so-called cognitive map of the patient. This study aimed at testing the software usability. A convenience sample of 23 experienced nurses from different healthcare organisations across the country rated the usability of the handoverEHR after performing typical handover tasks. All usability scales of the IsoMetricsL questionnaire showed positive values (4 “I agree”) with the exception of “error tolerance” (3 “neutral statement”). A significant improvement was found in self-descriptiveness as compared to an initial usability testing prior to this study. Different subgroups of users tended to rate the usability of the system differently. This study demonstrated the benefits of formative evaluations in terms of improving the usability of an entirely new approach. It thus helps to transform a novel piece of software towards becoming a real innovation. Our findings also hint at the importance of user characteristics that could affect the usability ratings.
Patient handovers are cognitively demanding, crucial for information continuity and patient safety, but error prone. This study investigated the effect of an electronic handover tool, i.e. the handoverEHR, on the memory and care planning performance of nurse students (n=32) in a randomised, controlled cross-over design with the factors handover task and handover role. On a descriptive level, handover recipients could improve their memory performance with electronic support, handover givers their performance of writing care plans. Statistically meaningful differences occurred, however, only when the participants were givers. Without handover experience and with low fluency to word problems, givers performed badly in the most demanding of the handover tasks. Final recommendations, however, can only be made after replicating this study in a clinical setting with mixed groups.
Health IT systems are employed to support continuity of care via information continuity, while management continuity is often neglected. This study aims at investigating issues of management continuity when developing a collaborative decision support system for chronic wounds. Thirty-three experts from a variety of professions and disciplines discussed problems and possible solutions in four workshops. The following topics emerged from the discussion: existing networks involving payers, responsibilities as well as good discharge management. These topics clearly address management continuity and are also relevant for the scenario of inter-professional wound care across different settings.
Angehörige der Gesundheitsberufe sehen sich vermehrt mit komplexen und neuen Aufgaben sowie einem veränderten Arbeitsumfeld konfrontiert. Gleichzeitig ist das Gesundheitswesen durch ein hohes Maß an Arbeitsteilung gekennzeichnet, die das nahtlose Zusammenwirken unterschiedlichster Gesundheitsberufe voraussetzt. Daher kommt der Entwicklung interdisziplinärer Kompetenzen eine hohe Bedeutung zu.
An der Hochschule Osnabrück werden im Rahmen des BMBF-geförderten Forschungsverbundprojekts „Kompetenzentwicklung von Gesundheitsfachpersonal im Kontext des Lebenslangen Lernens“ (KeGL) berufsbegleitende wissenschaftliche Zertifikatsangebote in den Bereichen Patientensicherheitsmanagement und Gesundheitsinformatik entwickelt und in interdisziplinär zusammengesetzten Gruppen erprobt. Im Mittelpunkt dieser Handreichung stehen die Ergebnisse und Erfahrungen aus der ersten Förderphase, in welcher neben einer Analyse von Kompetenzbedarfen, die Erarbeitung eines Lehr-Lern-Konzepts und die Erprobung zweier Pilotmodule erfolgt sind.