Thomas Bürkle

The lack of nursing digital competences for patient care information transmission can negatively affect the continuity of care. Identifying digital competences grounded in real-work practice is essential for developing effective professional nursing profiles. This study adopts a situated approach to competence, employing a semiological work analysis based on the course-of-action theoretical framework. The aim was to identify digital competences in real nursing situations related to the transmission of patient care information. Twenty-four nurses were observed and recorded during full shifts (approximately 24 h each) across six hospital wards, capturing authentic practices. The study identified 27 situated digital competences associated with patient care information transmission. These competences are grouped into four main categories of activity and are aligned with core digital competency domains defined in an international digital competence framework for nursing. The findings help bridge the gap between local practices and global standards and provide valuable insights for developing nursing curricula and training programs.

In a cross country comparison, we try to identify factors which may influence the degree of interaction between inpatient and ambulatory patient care. For three Scandinavian countries, the United states and Switzerland, the IT-systems in hospitals and healthcare regions as well as electronic health records are described and characterized and the results contrasted with the way healthcare is delivered and financed. As a result, the existence of a national patient identifier, a reduction in the number of hospital information systems and a common database for healthcare professionals in inpatient and outpatient care are identified as positive contributors towards seamless care pathways. In comparison, the existence of an Electronic Health Record in the hands of the patient, or the existence of a tax paid healthcare system or the amount of healthcare expenditure do not necessarily contribute to this effect, since they can be observed also in countries with intermediate or improvable linkage between inpatient and outpatient sector. Seamless patient care has no directly visible correlation to life expectancy or preventable mortality.

Background: Despite the benefits, the practical implementation of shared decision-making (SDM) is challenged by the lack of decision aids for patients. Objective: This rapid review analyses how patient journey maps (PJMs) have highlighted the need for shared healthcare decisions between patients and professionals. Methods: The extension of the PRISMA methodology for scoping reviews was used as a guideline. The MEDLINE, APA PsycInfo, Embase, Emcare and Nursing Database digital databases were queried using a reduced selection of search expressions. Resulting articles from peer-reviewed journals since 2015 were analysed. Results: 11 articles provide directions regarding the enhanced support of SDM throughout the patient journey. The utilisation of basic patient journey modelling along care trajectories has facilitated patient engagement with professionals, thereby enabling the disclosure of their needs and experiences. A generic model could be abstracted from each condition-specific PJMs, highlighting when decisions may impact patient experience. Conclusions: The development of a digital visual representation of a generic patient journey, from the onset of symptoms to the management of the condition, has the potential to serve as a valuable communication tool, assisting patients and healthcare professionals in better preparing, focusing and documenting SDM conversations.

Falls pose a substantial risk to elderly individuals, especially those over 65, often leading to severe consequences. This project investigates the potential of the tēmi robot for fall detection in care facilities and its integration into a simulated clinical workplace system. The prototype employs the YOLOv8 image recognition model to detect fallen individuals during patrols, transmitting incident data to a simulated clinical system via Fast Healthcare Interoperability Resources (FHIR). While initial tests delivered promising results, enhancements in image recognition accuracy are required for effective real-world deployment.

We present an approach to use the think aloud method for formative usability evaluation for medical software in a remote access scenario which combines researchers in two different locations and test persons distributed across five Swiss hospitals into one study using MS-Teams. We could show that a) these tests can be performed remote in a tight time schedule and b) that results valuable for the formative development of the examined mockup solution could be achieved. Two sessions had to be rescheduled for technical problems but all test persons could complete the think aloud study in 30 minutes at their usual working environment. This offers the opportunity to software providers to develop medical software with better usability in close cooperation with future users.

Objectives: Identification of diagnostic error is complex and mostly relies on expert ratings, a severely limited procedure. We developed a system that allows to automatically identify diagnostic labelling error from diagnoses coded according to the international classification of diseases (ICD), often available as routine health care data. Methods: The system developed (index test) was validated against rater based classifications taken from three previous studies of diagnostic labeling error (reference standard). The system compares pairs of diagnoses through calculation of their distance within the ICD taxonomy. Calculation is based on four different algorithms. To assess the concordance between index test and reference standard, we calculated the area under the receiver operating characteristics curve (AUROC) and corresponding confidence intervals. Analysis were conducted overall and separately per algorithm and type of available dataset. Results: Diagnoses of 1,127 cases were analyzed. Raters previously classified 24.58% of cases as diagnostic labelling errors (ranging from 12.3 to 87.2% in the three datasets). AUROC ranged between 0.821 and 0.837 overall, depending on the algorithm used to calculate the index test (95% CIs ranging from 0.8 to 0.86). Analyzed per type of dataset separately, the highest AUROC was 0.924 (95% CI 0.887–0.962). Conclusions: The trigger system to automatically identify diagnostic labeling error from routine health care data performs excellent, and is unaffected by the reference standards’ limitations. It is however only applicable to cases with pairs of diagnoses, of which one must be more accurate or otherwise superior than the other, reflecting a prevalent definition of a diagnostic labeling error.

In neurosurgery, intraoperative neurophysiological monitoring (IOM) with continuous measurements of neural electrical activity may reduce the risk of postoperative deficits. During an IOM, surgical information as well as neurophysiological, surgical and anesthesia events have to be recorded. So far, there is no common standard for this task available. In this paper, such a standardization with the aim of facilitating the data input and making the protocols data available for different sorts of analyses is described. We developed a protocol entry catalog with 200 standard expressions, which were divided into four categories: IOM, surgical procedure, anesthesia and others. An empirical assessment of the catalog by the IOM team showed the need for subcategories. In the final version of the catalog, the standard terms were grouped into 25 subcategories. The catalog is a first step to support systematic research into the occurrence of clinical events during the IOM and their association with postoperative neurological deficits that could enable improved surgical procedures in the future.

Next generation sequencing (NGS) technologies allow improved understanding of pathogens. In the upstream processing of generating genomic data, there is still a lack of process-oriented tools for managing corresponding meta data. In this paper, we provide a description of how a process-oriented software prototype was developed that allowed the capture and collation of metadata involved when doing NGS. Our question was: How to develop an interactive web application that supports the process-oriented management of genetic data independent of any sequencing technique?

Modern clinical laboratories have to confirm that the procedures used for specific tests are reliable and valid. There are several sources of errors and interferences that can invalidate the results. Medical validation refers to the plausibility check of the test results. Implausible results indicate that something might went wrong with a sample retrieved from the patient, e.g., the blood sample got contaminated with another fluid, which requires re-examination. Here, we describe how an integrated R-based business intelligence (BI) tool can be developed that increase the efficiency of the medical validation at the Institute of Clinical Chemistry (ICC) of the University Hospital Zurich. A BI software environment allowed us to digitalize steps in the validation process that were manually done in Excel worksheets, e.g., importing the data, calculating percentiles, and producing graphical outputs.

Pharmacogenetic testing can prevent adverse drug events but has rarely found its way into clinical routine. One reason is the lack of tools for smooth and automatable integration of pharmacogenetic knowledge into existing processes. Especially, electronic medical records (EMR) represent a suitable environment for such tools. We developed a modular service-oriented prototype of a pharmacogenetic decision support system within an EMR system of the Bern University Hospital. Here, we present the component architecture of our system and discuss issues required for generalizing our results.