Implementation of a digital coordination centre in a hospital: a qualitative evaluation of enablers, barriers and strategies.

Background: Digital Coordination Centres (DCCs) represent an innovative approach in hospital settings, designed to enhance patient flow, operational efficiency, and real-time decision-making. While their potential is widely recognised, there is limited understanding of the factors influencing their implementation. This study evaluated the implementation of a DCC in a large Australian hospital, with a focus on identifying enablers, barriers, and strategies for improvement.

Key Considerations for Governing Safe and Responsible Use of AI in Healthcare.

This study explores the governance challenges and opportunities associated with the implementation and use of AI in healthcare, offering practical insights informed by extensive stakeholder interviews. By analyzing perspectives from academia, government, clinicians, healthcare associations, and consumer groups, the research highlights critical themes, including data governance, ethical considerations, accountability, risk management, and equity. Findings highlight the need for robust frameworks to address fragmented data systems, privacy concerns, and systemic biases while recommending tiered risk management approaches to AI implementation.

Prevalence of GHB-Related Presentations to a Metropolitan Emergency Department in Melbourne.

Introduction: Gamma-hydroxybutyrate (GHB) is a commonly used recreational substance. It has a narrow therapeutic index. The management of GHB overdose in the emergency department (ED) is labour and resource intensive.

Multisite study using a customised NLP model to predict disposition in the emergency department: protocol paper.

Introduction: To address timely care in emergency departments, artificial neural networks (ANNs) with natural language processing will be applied to triage notes to predict patient disposition. This study will develop a predictive model that predicts disposition and type of admission.

Methods And Analysis: This will include data preprocessing and quality enhancement, masked language modelling, ANN-based fusion network for prediction.

Developing an AI Governance Framework for Safe and Responsible AI in Health Care Organizations: Protocol for a Multimethod Study.

Background: Artificial intelligence (AI) has the potential to improve health care delivery through enhanced diagnostics, streamlined operations, and predictive analytics. However, health care organizations face substantial challenges in implementing AI safely and responsibly. This is due to regulatory complexity, ethical considerations, and a lack of practical governance frameworks.

Reducing Unnecessary Venous Blood Gas (VBG) Testing in the Emergency Department Through Targeted Education.

Objective: Our objective was to evaluate the amount of unnecessary Venous Blood Gas (VBG) tests initiated in the Emergency Department (ED) and to assess the effectiveness of clinical intervention, such as education, in reducing VBG tests.

Methods: 497 consecutive patients were selected between 1 August and 30 September 2019. For Phase 1, 10 volunteer nurses were randomly assigned to 50 cases each and assessed whether they would perform a VBG.

Evaluating the implementation of a digital coordination centre in an Australian hospital setting: a mixed method study protocol.

Introduction: This protocol outlines a mixed methods study evaluating a new Digital Coordination Centre (DCC) at the Royal Melbourne Hospital (RMH), Melbourne, Australia. While coordination centres show potential for impact, evidence on effective implementation in the Australian context remains scarce. This study aims to address this gap.

Evaluation of the ED MHAOD Hub at St Vincent's hospital.

IntroductionIn response to the 2021 Royal Commission into Victoria's Mental Health System, the Victorian government established six purpose-built Mental Health Alcohol and Other Drug (MHAOD) emergency department (ED) Hubs. This study evaluates the MHAOD Hub at St Vincent's Hospital Melbourne (SVHM), which opened in March 2022 as metropolitan Melbourne's first multidisciplinary Mental Health and Drug or Alcohol Hub integrated into the St Vincent's Emergency Department.MethodsThis retrospective analysis covers patient admissions to the MHAOD Hub from March 2022 to June 2024, documenting demographics, clinical characteristics and outcomes.

What they did next: Using follow-up phone calls to investigate health care access patterns of patients who take their own leave.

Objectives: The purpose of the present study was to use telephone follow-up (TFU) to investigate the actions taken by patients after they took their own leave (TOL) from an ED, with a focus on priority groups who are at risk of experiencing health inequity. These included people experiencing homelessness (EH), people with a low socioeconomic status by index of relative socioeconomic disadvantage (IRSD) and First Nations people. The primary outcome was being seen by a general practitioner (GP) within 2 days of the TOL event.

Health consumers' ethical concerns towards artificial intelligence in Australian emergency departments.

Objectives: To investigate health consumers' ethical concerns towards the use of artificial intelligence (AI) in EDs.

Methods: Qualitative semi-structured interviews with health consumers, recruited via health consumer networks and community groups, interviews conducted between January and August 2022.

Results: We interviewed 28 health consumers about their perceptions towards the ethical use of AI in EDs.

Applications of natural language processing at emergency department triage: A narrative review.

Introduction: Natural language processing (NLP) uses various computational methods to analyse and understand human language, and has been applied to data acquired at Emergency Department (ED) triage to predict various outcomes. The objective of this scoping review is to evaluate how NLP has been applied to data acquired at ED triage, assess if NLP based models outperform humans or current risk stratification techniques when predicting outcomes, and assess if incorporating free-text improve predictive performance of models when compared to predictive models that use only structured data.

Methods: All English language peer-reviewed research that applied an NLP technique to free-text obtained at ED triage was eligible for inclusion.

Machine learning in clinical practice: Evaluation of an artificial intelligence tool after implementation.

Objective: Artificial intelligence (AI) has gradually found its way into healthcare, and its future integration into clinical practice is inevitable. In the present study, we evaluate the accuracy of a novel AI algorithm designed to predict admission based on a triage note after clinical implementation. This is the first of such studies to investigate real-time AI performance in the emergency setting.

Use of autologous fat grafting in reconstruction following mastectomy and breast conserving surgery: An updated systematic review protocol.

Introduction: Use of autologous fat grafting (AFG) for breast reconstructive surgery is gaining acceptance, but concerns regarding its efficacy and safety remain. We present a protocol for a systematic review that aims to update the findings since our previous systematic review on a number of outcomes of AFG.

Methods: The systematic review has been registered a priori (UIN: reviewregistry308).

A new system for comparative functional genomics of Saccharomyces yeasts.

Whole-genome sequencing, particularly in fungi, has progressed at a tremendous rate. More difficult, however, is experimental testing of the inferences about gene function that can be drawn from comparative sequence analysis alone. We present a genome-wide functional characterization of a sequenced but experimentally understudied budding yeast, Saccharomyces bayanus var.

Genome stability of Lyme disease spirochetes: comparative genomics of Borrelia burgdorferi plasmids.

Lyme disease is the most common tick-borne human illness in North America. In order to understand the molecular pathogenesis, natural diversity, population structure and epizootic spread of the North American Lyme agent, Borrelia burgdorferi sensu stricto, a much better understanding of the natural diversity of its genome will be required. Towards this end we present a comparative analysis of the nucleotide sequences of the numerous plasmids of B.

Cytometric profiling in multiple sclerosis uncovers patient population structure and a reduction of CD8low cells.

As part of a biomarker discovery effort in peripheral blood, we acquired an immunological profile of cell-surface markers from healthy control and untreated subjects with relapsing-remitting MS (RRMS). Fresh blood from each subject was screened ex vivo using a panel of 50 fluorescently labelled monoclonal antibodies distributed amongst 56 pools of four antibodies each. From these 56 pools, we derived an immunological profile consisting of 1018 'features' for each subject in our analysis using a systematic gating strategy.