Refine
Year of publication
Document Type
- Conference Proceeding (17)
- Article (10)
- Book (3)
- Working Paper (2)
- Part of a Book (1)
Is part of the Bibliography
- yes (33)
Keywords
- Bass model (1)
- CEO (1)
- CEO-CIO relationship (1)
- Diffusion of innovation (1)
- Electronic health records (1)
- Entlassungsmanagement (1)
- Evaluation (1)
- Health Informatics (1)
- Health policy (1)
- IT decision making (1)
- IT knowledge (1)
- Interprofessionalism (1)
- Kinematische Kette (1)
- Lean Management (1)
- Patient Journey Board (1)
- Photometrie (1)
- Prozessoptimierung (1)
- Sakroiliakalgelenk (1)
- Schmerzmessung (1)
- Sprunggelenksverletzung (1)
- Summer School (1)
- Verweildauersteuerung (1)
- Whiteboard (1)
- chronic leg ulcer (1)
- chronic wound (1)
- clinical information logistics (1)
- clinical workflows (1)
- composite score (1)
- health information exchange (1)
- health information technology (1)
- model building (1)
- semantic interoperability (1)
- terminology mapping (1)
- wound care (1)
Institute
- Fakultät WiSo (32)
The aim of this European interprofessional Health Informatics (HI) Summer School was (i) to make advanced healthcare students familiar with what HI can offer in terms of knowledge development for patient care and (ii) to give them an idea about the underlying technical and legal mechanisms. According to the students’ evaluation, interprofessional education was very well received, problem-based learning focussing on cases was rated positively and the learning goals were met. However, it was criticised that the online material provided was rather detailed and comprehensive and could have been a bit overcharging for beginners. These drawbacks were obviously compensated by the positive experience of working in international and interprofessional groups and a generally welcoming environment.
In September 2022, the interprofessional European Summer School on the topic “Information in Healthcare – From Data to Knowledge” was held at the University of Porto. This Summer School included the topics Interoperability, Data Protection and Security and Data Analytics and consisted of an online preparation phase and an attendance phase in Porto. The didactic concept involved problem-based learning using a case study. A variety of course materials were developed and used to achieve the learning objectives. There are plans to continue the Summer School concept at participating institutions in the future, starting with a Spring School 2023 in Osnabrück.
Interoperability, Data Protection and Security and Data Analytics are of high relevance for the future of eHealth and interprofessional care. Three online courses were therefore designed and delivered for these topics, all of which followed the same structure. A variety of materials were developed and different tools for knowledge transfer, communication and collaboration were used.
Hintergrund
Sprunggelenksverletzungen (SGV) sind die häufigsten Verletzungen des muskuloskeletalen Systems. Neben Schmerz, Schwellung und Funktionseinschränkung werden Zusammenhänge zwischen einem Sprunggelenkstrauma und Veränderungen am Becken bzw. Sakroiliakalgelenk (SIG) diskutiert. In der vorliegenden Studie wird geprüft, ob Wechselwirkungen von SGV und Veränderungen am Becken bzw. SIG bestehen.
Material und Methoden
In dieser Querschnittsstudie ohne Verblindung wurden 18 Probanden mit SGV und 22 gesunde Probanden am Becken und SIG untersucht. Der Zustand nach der SGV wurde anhand des FAAM-G-Fragebogens ermittelt. Die Evaluation der Beckenposition erfolgte mit Photometrie. Dabei wurden die Referenzpunkte SIAS und SIPS zueinander verglichen. Am SIG erfolgten Schmerzprovokationstests, um Veränderungen am SIG zu ermitteln. Die in beiden Gruppen erhobenen Daten wurden statistisch ausgewertet und verglichen.
Ergebnisse
Der funktionelle Zustand der Sprunggelenke unterschied sich zwischen der Kontrollgruppe und der Experimentalgruppe signifikant. Die Unterschiede bei den photometrischen Ergebnissen waren für die Beckensymmetrie nicht signifikant (SIAS p = 0,426; SIPS p = 0,779). Hinsichtlich der Schmerzhaftigkeit des SIG zeigte sich ebenfalls kein signifikanter Unterschied (p = 0,477).
Schlussfolgerung
Es konnten keine Positionsveränderungen des Beckens infolge eines Sprunggelenktraumas beobachtet werden. Auch zeigten sich keine Assoziationen zwischen SGV und Becken- bzw. SIG-Position.
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.
Building on Rogers’ Diffusion of Innovation Theory, Bass models describe the diffusion processes distinguishing between innovation (p) and imitation (q). This study aimed at modelling the uptake of RIS, PACS and EHR systems in Germany and Finland. The Bass models revealed a quick and almost identical uptake process across all three systems for Finland. In contrast, the Bass models mirrored a slower uptake in Germany. Consequently, the Finnish “imitation” coefficients were larger than the German ones. While in Germany almost free market forces were driving the adoption through imitation but without tail wind from policy, the adoption process in Finland was centrally governed. This suggests that the diffusion process in Finland reflected a well-managed roll-out of the systems rather than imitation behaviour. Thus, in order for Bass model coefficients to be understood properly, additional contextual information is required.
The diabetic foot ulcer, which 2% – 6% of diabetes patients experience, is a severe health threat. It is closely linked to the risk of lower extremity amputation (LEA). When a DFU is present, the chief imperative is to initiate tertiary preventive actions to avoid amputation. In this light, clinical decision support systems (CDSS) can guide clinicians to identify DFU patients early. In this study, the PEDIS classification and a Bayesian logistic regression model are utilised to develop and evaluate a decision method for patient stratification. Therefore, we conducted a Bayesian cutpoint analysis. The CDSS revealed an optimal cutpoint for the amputation risk of 0.28. Sensitivity and specificity were 0.83 and 0.66. These results show that although the specificity is low, the decision method includes most actual patients at risk, which is a desirable feature in monitoring patients at risk for major amputation. This study shows that the PEDIS classification promises to provide a valid basis for a DFU risk stratification in CDSS.
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.
This study describes the eHealth4all@eu course development pipeline that builds upon the TIGER educational recommendations and allows a systematic development grounded on scientific and field requirements of competencies, a case/problem-based pedagogical approach and finally results in the syllabus and the course content. The pipeline is exemplified by the course Learning Healthcare in Action: Clinical Data Analytics.