Automatic Classification of Wound Images Showing Healing Complications: Towards an Optimised Approach for Detecting Maceration.

This study aims to advance the field of digital wound care by developing and evaluating convolutional neural network (CNN) architectures for the automatic classification of maceration, a significant wound healing complication, in 458 annotated wound images. Detection and classification of maceration can improve patient outcomes. Several CNN models were compared and MobileNetV2 emerged as the top-performing model, achieving the highest accuracy despite having fewer parameters.

Automation Bias in AI-Decision Support: Results from an Empirical Study.

Introduction: Automation bias poses a significant challenge to the effectiveness of Clinical Decision Support Systems (CDSS), potentially compromising diagnostic accuracy. Previous research highlights trust, self-confidence, and task difficulty as key determinants. With the increasing availability of AI-enabled CDSS, automation bias attains new attention.

What Determines the Use of Clinical Decision Support Systems in Nursing? Results of a Multiple Regression Analysis.

Introduction: In nursing, professionals are expected to base their practice on evidence-based knowledge, however the successful implementation of this knowledge into nursing practice is not always assured. Clinical Decision Support Systems (CDSS) are considered to bridge this evidence-practice gap.

Methods: This study examines the extent to which evidence-based nursing (EBN) practices influence the use of CDSS and identifies what additional factors from acceptance theories such as UTAUT play a role.

Health IT Adoption in German Hospitals: Could We See Any Changes Between 2017 and 2023?

Introduction: Increase in health IT adoption is often driven by financial support through the state. In 2020, the German Hospital Future Law passed Parliament with a schedule to see potential effects in 2023. The research question of the present study thus was if there were differences between 2017 and 2023 in selected application areas eligible for funding by the law.

Dimensions of Evidence-Based Practice in Nursing: Results of a Factor Analysis.

Clinical decision support systems (CDSS) are capable of bridging evidence and practice. However, it is unclear what dimensions determine evidence-based practice under real world conditions. To answer this question, 126 registered nurses and nursing students from the Munich municipal hospital group filled in a systematically developed and validated questionnaire with 26 items.

Information in Healthcare - From Data to Knowledge: Improving Data Literacy Competencies.

Digitalization in healthcare and the increasing availability of data demand data literacy competences of nurses and other healthcare professionals including technical, ethical and communication skills. The international Spring School 2023 "Information in Healthcare - From Date to Knowledge" aimed at these competences covering interoperability, data protection and security, data analytics and ethical issues. These topics were embedded in the overall case of data-driven quality improvement for diabetes patients in a region.

Recommended target audience, course content and learning arrangements for teaching health informatics competencies: A scoping review.

As healthcare depends on health information technology, there is a growing need for Health Informatics competencies in daily practice. This review aimed to explore how the teaching of education in HI has been arranged. 28 publications, published in English between 2016 and 2020 and obtained from selected bibliographic databases, were reviewed.

Discovering the importance of health informatics education competencies in healthcare practice. A focus group interview.

Background: As healthcare and especially health technology evolve rapidly, new challenges require healthcare professionals to take on new roles. Consequently, the demand for health informatics competencies is increasing, and achieving these competencies using frameworks, such as Technology Informatics Guiding Reform (TIGER), is crucial for future healthcare.

Aim: The study examines essential health informatics and educational competencies and health informatics challenges based on TIGER Core Competency Areas.

Differential effects of electronic patient record systems for wound care on hospital-acquired pressure injuries: Findings from a secondary analysis of German hospital data.

Introduction: Despite the improvements made in recent decades, the OECD regards hospital-acquired pressure injuries (HAPI) as high priority areas for actions to ensure patient safety. This study was aimed at investigating the degree of utilization of two types of electronic patient record systems for wound care on lowering HAPI rates. Furthermore, the effect of user satisfaction with the systems and perceived alignment with clinical processes should be studied.

Lessons Learned from an Interprofessional European Summer School in Health Informatics.

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.

Trust in Digitalization and AI: Findings from a Qualitative Study on Healthcare Professionals in Germany.

The acceptance and use of digital technologies depend on the trustworthiness attributed to them. Experts were interviewed about how they assign trust to digital technologies or AI (N=12). The data were analyzed applying the focused qualitative content analysis.

Design and Implementation of an ETL-Process to Transfer Wound-Related Data into a Standardized Common Data Model.

For observational studies, which are relevant especially for chronic conditions like chronic wounds, the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) offers a standardized database schema. In this study an ETL process for the transition of wound related data was developed. After understanding the data in general and mapping the relevant codes to concepts available in OMOP, the ETL process was implemented.

Adoption and Determinants of Assistive Technologies in the Real World: Results from the VdK Study.

Introduction: While there is growing evidence of the benefits of assistive technologies little is known about their adoption under real circumstances and prevalence for everyday use.

Objective: The aim of this analysis therefore was (i) to investigate the adoption rates in the real world and (ii) to identify potential determinants of their adoption by care-dependant persons and family caregivers.

Methods: The present study is a secondary analysis based on the data set of the VdK study on home care arrangements (n=53,678).

Predilection sites of pyoderma gangrenosum: Retrospective study of 170 clearly diagnosed patients.

Pyoderma gangrenosum (PG) is a non-infectious, neutrophilic dermatosis that was difficult to diagnose in clinical practice. Today, the PARACELSUS score is a validated tool for diagnostics. Based on this score, patients with clearly diagnosed PG were examined with regard to predilection sites.

The Representation of Trust in Artificial Intelligence Healthcare Research.

Artificial intelligence (AI) tends to emerge as a relevant component of medical care, previously reserved for medical experts. A key factor for the utilization of AI is the user's trust in the AI itself, respectively the AIt's decision process, but AI-models are lacking information about this process, the so-called Black Box, potentially affecting usert's trust in AI. This analysis' objective is the description of trust-related research regarding AI-models and the relevance of trust in comparison to other AI-related research topics in healthcare.

How Do User Participation and IT Self-Efficacy Influence User Attitudes Towards Smart Hospital Technology?

Smart hospitals aim to advance digitalization to provide better and safer care and increase user satisfaction by minimizing documentation burden. The aim of this study is to investigate the potential impact and its logic of user participation and self-efficacy on the pre-usage attitude and behavioural intention towards IT for smart barcode scanner-based workflows. A cross-sectional survey was conducted in a system of 10 hospitals in Germany that are in the process of implementing intelligent workflow technology.

Can Synthetic Images Improve CNN Performance in Wound Image Classification?

For artificial intelligence (AI) based systems to become clinically relevant, they must perform well. Machine Learning (ML) based AI systems require a large amount of labelled training data to achieve this level. In cases of a shortage of such large amounts, Generative Adversarial Networks (GAN) are a standard tool for synthesising artificial training images that can be used to augment the data set.

Effects of Hospital Digitization on Clinical Outcomes and Patient Satisfaction: Nationwide Multiple Regression Analysis Across German Hospitals.

Background: The adoption of health information technology (HIT) by health care providers is commonly believed to improve the quality of care. Policy makers in the United States and Germany follow this logic and deploy nationwide HIT adoption programs to fund hospital investments in digital technologies. However, scientific evidence for the beneficial effects of HIT on care quality at a national level remains mostly US based, is focused on electronic health records (EHRs), and rarely accounts for the quality of digitization from a hospital user perspective.

What Went Wrong in eMedCare? Formative Evaluation of an IT Project in Primary Care in Two Rural Districts.

Introduction: The interaction between nurses and physicians in the primary care setting is challenging with regard to structural, process and technical barriers. In order to overcome these barriers, the eMedCare project was launched and a commercial system was implemented.

Objective: This study aimed at a formative evaluation of the project.

Developing a professional-practice-model-based nursing organizational informatics competency model.

Background: The development of nursing informatics started late in China. There is an urgent need to develop a clinical practice model that can guide nursing managers in constructing an organizational nursing informatics competency.

Objective: The objective of this study was to develop a nursing organizational informatics competency model based on the Professional Practice Model (PPM) and to provide a reference for training in clinical nursing informatics in hospitals.

Automatic Wound Type Classification with Convolutional Neural Networks.

Chronic wounds are ulcerations of the skin that fail to heal because of an underlying condition such as diabetes mellitus or venous insufficiency. The timely identification of this condition is crucial for healing. However, this identification requires expert knowledge unavailable in some care situations.

The eHealth4all@eu Pipeline of Course Development: TIGER Recommendations in Action.

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.

Should App Self-Management Mean Self-Control? A Quantiative Study on App Supported Diabetes Self-Management.

Apps have been attested to empower patients regarding disease self-management through numerous studies. However, it is still unclear what factors determine the perception of patients whether an app is a useful tool for this purpose. A multiple regression model that was informed by the Technology Acceptance Model (TAM 2) was tested based on the answers of 235 app users with Diabetes type 1 or 2.

Patient Safety Informatics: Criteria Development for Assessing the Maturity of Digital Patient Safety in Hospitals.

With the start of the 21st century, patient safety as a topic of special interest has attracted increasing attention in both academia and clinical practice. As technology has continued to develop since then, questions and focal points surrounding the topic have also shifted. In particular, questions regarding the impact of digitalization on patient safety and its measurement are now of high interest.

An Image Based Object Recognition System for Wound Detection and Classification of Diabetic Foot and Venous Leg Ulcers.

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.