Refine
Document Type
- Conference Proceeding (13) (remove)
Language
- English (13) (remove)
Has Fulltext
- yes (13)
Is part of the Bibliography
- yes (13)
Keywords
- CEO (1)
- CEO-CIO relationship (1)
- Health Informatics (1)
- IT decision making (1)
- IT knowledge (1)
- Interprofessionalism (1)
- Summer School (1)
Institute
- Fakultät WiSo (13)
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.
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.
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.
Radiology has a reputation for having a high affinity to innovation – particularly with regard to information technologies. Designed for supporting the peculiarities of radiological diagnostic workflows, Radiology Information Systems (RIS) and Picture Archiving and Communication Systems (PACS) developed into widely used information systems in hospitals and form the basis for advancing the field towards automated image diagnostics. RIS and PACS can thus serve as meaningful indicators of how quickly IT innovations diffuse in secondary care settings – an issue that requires increased attention in research and health policy in the light of increasingly fast innovation cycles. We therefore conducted a retrospective longitudinal observational study to research the diffusion dynamics of RIS and PACS in German hospitals between 2005 and 2017. Based upon data points collected within the “IT Report Healthcare” and building on Rogers’ Diffusion of Innovation (DOI) theory, we applied a novel methodological technique by fitting Bayesian Bass Diffusion Models on past adoption rates. The Bass models showed acceptable goodness of fit to the data and the results indicated similar growth rates of RIS and PACS implementations and suggest that market saturation is almost reached. Adoption rates of PACS showed a slightly higher coefficient of imitation (q = 0.25) compared to RIS (q = 0.11). However, the diffusion process expands over approximately two decades for both systems which points at the need for further research into how innovation diffusion can be accelerated effectively. Furthermore, the Bayesian approach to Bass modelling showed to have several advantages over the classical frequentists approaches and should encourage adoption and diffusion research to adapt similar techniques.
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.
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.
Frequent users of emergency departments (ED) pose a significant challenge to hospital emergency services. Despite a wealth of studies in this field, it is hardly understood, what medical conditions lead to frequent attendance. We examine (1) what ambulatory care sensitive conditions (ACSC) are linked to frequent use, (2) how frequent users can be clustered into subgroups with respect to their diagnoses, acuity and admittance, and (3) whether frequent use is related to higher acuity or admission rate. We identified several ACSC that highly increase the risk for heavy ED use, extracted four major diagnose subgroups and found no significant effect neither for acuity nor admission rate. Our study indicates that especially patients in need of (nursing) care form subgroups of frequent users, which implies that quality of care services might be crucial for tackling frequent use. Hospitals are advised to regularly analyze their ED data in the EHR to better align resources.
Health IT and communication systems are indispensable in German hospitals for clinical as well as administrative process support. However, IT is often regarded as a “black box” for hospital CEOs. Thus, the question arises how can CEOs decide if they do not know what is in the box? In order to answer this question, half-structured interviews with 14 German hospital CEOs were conducted. They revealed three principle decision processes: the supported decision, the joint decision and the corporate level decision. In all cases, the hospital CEO and the CIO interacted to reach the final decision, most strongly in the joint decision mode and least strongly in the corporate decision mode. Only the joint decision mode definitely forced the CEO to open the “black box” of IT. In the era of digitalisation, however, CEOs must develop better competencies to decide over complex matters.
Background: IT is getting an increasing importance in hospitals. In this
context, major IT decisions are often made by CEOs who are not necessarily IT
experts. Objectives: Therefore, this study aimed at a) exploring different types of IT
decision makers at CEO level, b) identifying hypotheses if trust exists between these
different types of CEOs and their CIOs and c) building hypotheses on potential
consequences regarding risk taking and innovation. Methods: To this end, 14
qualitative interviews with German hospital CEOs were conducted to explore the
research questions. Results: The study revealed three major types: IT savvy CEOs,
IT enthusiastic CEOs and IT indifferent CEOs. Depending on these types, their
relationship with the CIO varied in terms of trust and common language. In case of
IT indifferent CEOs, a potential vicious circle of lack of IT knowledge, missing trust,
low willingness to take risks and low innovation power could be identified.
Conclusion: In order to break of this circle, CEOs seem to need more IT knowledge
and / or greater trust in their CIO.
As health IT supports processes along the entire patient trajectory and involves different types of professional groups, eHealth is inter-professional by nature. The aim of this study, therefore, is to investigate which competencies are at the intersection of the individual groups of health professionals. 718 international experts provided relevance ratings of eHealth competencies for different professional roles in an online survey. Communication and leadership proved to be important competencies across all professions, not only for executives. None or very little differences between professions were found between physicians and nurses, between IT experts at different levels and between IT experts and executives. However, there were a number of competencies rated differently when contrasting direct patient care specialists with executives. These findings should encourage organisations issuing educational recommendations to specify areas of shared competencies more extensively.
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.
Health IT adoption research is rooted in Rogers' Diffusion of Innovation theory, which is based on longitudinal analyses. However, many studies in this field use cross-sectional designs. The aim of this study therefore was to design and implement a system to (i) consolidate survey data sets originating from different years (ii) integrate additional secondary data and (iii) query and statistically analyse these longitudinal data. Our system design comprises a 5-tier-architecture that embraces tiers for data capture, data representation, logics, presentation and integration. In order to historicize data properly and to separate data storage from data analytics a data vault schema was implemented. This approach allows the flexible integration of heterogeneous data sets and the selection of comparable items. Data analysis is prepared by compiling data in data marts and performed by R and related tools. IT Report Healthcare data from 2011, 2013 and 2017 could be loaded, analysed and combined with secondary longitudinal data.