Studies in health technology and informatics最新文献

An automated discharge summary tool has been developed using routinely collected observational data in a tertiary paediatric hospital. Adoption of this tool by rotating medical staff strongly improved timely discharge summary completion within 48 hours from 40% to 90% during the implementation phase but these improvements were not sustained. A second phase involving authorship by permanent nursing staff is ongoing.

Since 2018, The University of Queensland's (UQ) Faculty of Engineering, Architecture and Information Technology and CSIRO's Australian e-Health Research Centre (AEHRC) have collaborated on UQ's COMP3820 Digital Health Software Project course [1]. Students study an edX-based MOOC and attend lectures by domain experts to learn about healthcare, healthcare informatics and healthcare standards with a focus on SNOMED CT, HL7's Fast Healthcare Interoperability Resources (FHIR®) and the SMART on FHIR (SMART®) Application Programming Interface (API) standards. They form teams that develop SMART on FHIR based electronic health record (EHR) connected apps under the mentorship of domain experts who propose problems suitable for a FHIR app solution. In the 2024 autumn/winter semester, eighty students formed sixteen project teams. The course and the three highest rated projects are described.

High latency in large neural networks, such as bidirectional encoder representations from transformers (BERT), poses a challenge for real-time applications. This study explores reducing the size of BERT through model distillation using DistilBioBERT, CompactBioBERT, and TinyBioBERT and by removing layers, with the goal of lowering computational and memory requirements for efficient semantic search of clinical terminology. Using a newly developed clinical dataset, the performance of these compact models is evaluated against pre-trained biomedical BERT variants with progressively fewer layers.

The digital health technology readiness of nurses, nursing students, nurse academics, and nurse leaders in Australia was explored. Dominant themes included disillusionment between expectation and reality, and shared responsibility for the development of digital expertise. Adoption of existing capability and competence frameworks into curricula may be slow because of the accreditation requirements for nursing and midwifery programs. Health services collaborating with universities to provide nursing students with the opportunity for learning digital technologies while on clinical placement may enhance their confidence, enabling them to move beyond using technology effectively to focusing on learning to identify how data can inform improvements to patient care.

Prediabetes presents a critical window to prevent type 2 diabetes, a rising global health crisis, yet young adults often lack engaging preventive tools. This ongoing study aims to design and evaluate a web application to enhance health knowledge, engagement, and self-management for this at-risk group. This theoretical lens combines Design Science Research Methodology (DSRM), the theory of Task-Technology Fit (TTF), and the Unified Theory of Acceptance and Use of Technology (UTAUT). The proposed solution incorporates a unique combination of features learned through a previously conducted systematic literature review (SLR). Features include Machine Learning (ML)-based recommendations, educational modules, goal setting, gamification elements, and an artificial intelligence (AI)-incorporated chatbot. The proposed design to date is presented, in addition to the planned scenario-driven use cases to highlight the relevance of the proposed solution. A pilot study will assess usability, usefulness, satisfaction, and health knowledge via initial, midway, and final surveys mapped along with the design process. The data will be analysed via descriptive statistics and thematic analysis. This work-in-progress paper offers a streamlined, user-centred approach to designing and developing digital health interventions for prediabetes prevention while contributing insights for personalised digital health interventions.

The SNOMED Expression Constraint Language (ECL) is a powerful but complex tool for querying clinical concepts within SNOMED CT, playing a critical role in clinical decision support, data analysis, and healthcare interoperability. However, its steep learning curve - requiring both syntactic expertise and in-depth knowledge of SNOMED CT's coding system - creates significant challenges for non-specialists. To address this issue, a novel approach is proposed that leverages state-of-the-art Large Language Models (LLMs) to translate natural language questions into ECL queries. The model is designed to perform bidirectional tasks: generating ECL queries from user questions and providing natural language explanations for ECL queries, making the language more accessible and easier to understand. This work represents the first research effort to tackle this specific translation challenge, supported by the development of custom datasets and a novel pipeline that integrates multiple AI agents. Evaluation results demonstrate that the proposed model achieves 83.78% accuracy, highlighting the significant potential of LLMs for translating natural language questions into SNOMED ECL.

This article has been withdrawn from publication at the request of the correspondingauthor.

Inter-professional learning (IPL) is a key component of health workforce development. This study evaluated IPL at Health2GO, a university-based allied health clinic, using the PROLIFERATE_AI digital evaluation framework. The analysis combined participatory co-design, Bayesian modelling of survey responses, and qualitative thematic coding to assess comprehension, engagement, barriers, and motivation. Most participants reported a strong understanding and motivation, but some experienced barriers related to scheduling and accessing flexible resources. Integrated findings informed recommendations for improving session clarity, flexibility, and digital access in IPL programs.

Nurse practitioners have the clinical capability to support healthcare delivery services in geographically isolated communities and readily demonstrate a cost-effective, safe and competent alternate model of primary care for older adults. Despite carefully evaluating the pre-implementation context, recruitment challenges resulted in the ability for only one nurse practitioner to provide a telehealth support model. Guard rails to practise in the setting, necessary within the current profile of rural aged care and government policy flux, resulted in poor engagement and use of the provided advanced practice support. 'Grow your own' strategies are recommended as one potential solution.

In Australia, heatwaves result in more fatalities than any other natural disaster, underscoring their significant public health impact. Heatwaves have been associated with heightened ambulance demand, and this study examines their relationship with emergency department (ED) presentations for circulatory and respiratory diseases. The analysis, focusing on the peak heatwave months of December and January over five years, revealed a positive correlation between maximum temperatures and ED presentations. Specifically, ED presentations increased by approximately 4.2% during heatwave periods and 3.9% during non-heatwave periods for every one-degree Celsius rise in maximum temperature. These findings suggest that, alongside well-recognised factors such as population growth and an ageing population, climate change poses an additional and significant challenge to the healthcare system. As maximum temperatures rise, the increased demand for emergency healthcare services could hinder the timely delivery of critical care, necessitating proactive planning and adaptation to ensure resilience in the face of a warming climate.