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The Certified Health Informatician Australasian (CHIA) is an assessment of a candidate's capabilities measured using a core set of health informatics competencies. The aim of this paper is to describe the outcomes of the first eight years since the program's launch. This paper contributes to the competency framework and certification discourse, and knowledge of the increasing importance and recognition of health informaticians through certification. An analysis of results and possible contributing factors is discussed. [ABSTRACT FROM AUTHOR]

There is broad agreement regarding fundamental digital health competencies that clinical health professionals should possess. However, there is still no clear way to observe and assess their application, during the actual work practices undertaken in clinical settings. The present paper tackles this competencypractice gap. It describes a novel health workforce research process to evolve competency statements into entrustable professional activities (EPAs) for using digital health and informatics in a clinical profession. It illustrates the use of the EPA-DH-CP framework in the context of physiotherapy. This framework offers a systematic approach for any clinical profession to develop EPAs that set out their expectation of how practitioners will demonstrate relevant digital health competencies. It can inform pre-clinical education and continuing professional development in digital health, and implementation of changes in scopes and standards of digital health clinical practice. It can support interprofessional evaluation of digital health EPAs and other EPAs. [ABSTRACT FROM AUTHOR]

Microvascular invasion of HCC is an important factor affecting postoperative recurrence and prognosis of patients. Preoperative diagnosis of MVI is greatly significant to improve the prognosis of HCC. Currently, the diagnosis of MVI is mainly based on the histopathological examination after surgery, which is difficult to meet the requirement of preoperative diagnosis. Also, the sensitivity, specificity and accuracy of MVI diagnosis based on a single imaging feature are low. In this paper, a robust, high-precision cross-modality unified framework for clinical diagnosis is proposed for the prediction of microvascular invasion of hepatocellular carcinoma. It can effectively extract, fuse and locate multi-phase MR Images and clinical data, enrich the semantic context, and comprehensively improve the prediction indicators in different hospitals. The state-of-the-art performance of the approach was validated on a dataset of HCC patients with confirmed pathological types. Moreover, CMIR provides a possible solution for related multimodality tasks in the medical field. [ABSTRACT FROM AUTHOR]

Real-world data (RWD) could be a new way to evaluate the safety and efficacy of post-marketing drugs, while there is no common method for how to use RWD for drug evaluation. In this paper, we present a framework for real-world drug evaluation based on electronic medical record (EHR) data. We designed a data model customized for post-marketing drug evaluation and a unified post-marketing drug evaluation pipeline. The proposed framework can be applied to drug evaluations with different study paradigms for different purposes by flexible use of the proposed data model and pipeline. A prototype system has been developed according to the framework. Real-world EHRs in a tertiary hospital in China between 2010 and 2020 were converted to the proposed data model, and as a test case, we conducted a research on the risk of allergic reactions to cefodizime and ceftriaxone using the prototype system. [ABSTRACT FROM AUTHOR]

Health service managers play a crucial role in managing and leading in the digital health environment. Development of the health management workforce that is ready to lead and manage digital health transformation requires partnerships across sectors, in not only developing workforce competence but also in developing supportive mechanisms that can translate competencies into practice. A framework presenting a systematic approach in enabling the development of a competent health management workforce in the digital health era has recently been published. The purpose of this paper is to explore and discuss the application of the framework in the Australian context, informed by the findings of a PhD research project that uses an empirically validated four-step approach to confirm the health service management workforce development needs in the digital health context. The PhD project has already confirmed: 1) the paucity of Australian Health Informatics Competency Framework (AHICF) competencies being included in Australian health service management postgraduate program curricula; 2) five key strategies that contribute to developing health management workforce competency and capacity; and 3) seven key factors that enable health management workforce development in the digital health context. Further understanding of the barriers and enablers for health service managers to develop capability and manage in the digital health environment, and the factors that influence digital health policy and practice will be developed, by critically analysing findings from focus group discussions with health managers and semi-structured interviews with digital health leaders, to be completed by May 2023. [ABSTRACT FROM AUTHOR]

In the residential aged care sector medication management has been identified as a major area of concern contributing to poor outcomes and quality of life for residents. Monitoring medication management in residential aged care in Australia has been highly reliant on small, internal audits. The introduction of electronic medication administration systems provides new opportunities to establish improved methods for ongoing, timely and efficient monitoring of a range of medication indicators, made more meaningful by linking medication data with resident characteristics and outcomes. Benchmarking contemporary medication indicators provides a further opportunity for improvement and is most effective when indicator data are adjusted to take account of confounding factors, such as residents' characteristics and health conditions. Roundtables provide a structure for sharing and discussing indicator data in a trusted and supportive environment and encourage the identification of strategies which may be effective in improving medication management. This paper describes a new project to establish, implement and evaluate a National Aged Care Medication Roundtable. [ABSTRACT FROM AUTHOR]

Today, urban congestion is worsening in many countries as a result of population growth, economic growth, private car ownership, urbanization, housing development, and employment opportunities. It is very important to understand what factors cause this traffic congestion. Thus, this paper discussed on how travel demand strategies contribute to traffic congestion in Kuala Lumpur, Malaysia. Using a causal loop diagram (CLD), a hypothetical framework was developed to represent the causality of connected variables in four subsectors: transport demand, transport supply, transport system, and modal share in traffic congestion based on various reports from government agencies and existing literature reviews. A conceptual structure of CLD allows the modeler to understand the dynamic relationship between variables found in the complex transportation systems. The CLD will be used as a basis for developing a dynamic simulation model in future work. [ABSTRACT FROM AUTHOR]

Parkinson's disease is a chronic progressive neurodegenerative disease with highly heterogeneous symptoms and progression. It is helpful for patient management to establish a personalized model that integrates heterogeneous interpretation methods to predict disease progression. In the study, we propose a novel approach based on a multi-task learning framework to divide Parkinson's disease progression modeling into an unsupervised clustering task and a disease progression prediction task. On the one hand, the method can cluster patients with different progression trajectories and discover new progression patterns of Parkinson's disease. On the other hand, the discovery of new progression patterns helps to predict the future progression of Parkinson's disease markers more accurately through parameter sharing among multiple tasks. We discovered three different Parkinson's disease progression patterns and achieved better prediction performance (MAE=5.015, RMSE=7.284, r2=0.727) than previously proposed methods on Parkinson's Progression Markers Initiative datasets, which is a longitudinal cohort study with newly diagnosed Parkinson's disease. [ABSTRACT FROM AUTHOR]

Medication prescribing in paediatrics is complex and compounded by the need to provide age and weight related doses, and errors continue to be problematic. Electronic medication systems (EMS) can reduce errors through dosing calculators and computerised decision support. However, evidence on costs and benefits of these systems is limited, particularly in paediatric hospitals. This paper presents the development of a cost-benefit analysis (CBA) framework to assess the impact of an EMS implementation in a paediatric tertiary hospital. An innovative component of the framework is the incorporation of the impact of the effects of the EMS for both the health system as well as for patients and their wider family networks, allowing a net social benefit assessment. We describe the impact of non-clinical out-of-pocket costs of admission and use discrete choice experiments to measure both medication related harm and the importance of medication safety to families and members of the community. [ABSTRACT FROM AUTHOR]

Resilience research is attracting increasing attention as stressors such as pandemics and climate change impact normal life worldwide. Informatics tools can play an important role in enhancing resilience of people, communities, and organizations. We present Resilience Informatics as a sub-discipline of resilience research and propose a conceptual framework for Resilience Informatics to aid in the development and effective deployment of informatics systems for resilience. [ABSTRACT FROM AUTHOR]

The emerging cost-effective and powerful standalone VR hardware is an increasingly viable supplement to traditional clinical educational modalities. These traditional approaches are effective but can be limited by the cost of simulation infrastructure, the requirement to attend at fixed times and locations and instructor availability present challenges in meeting the needs of clinicians. One barrier facing educators looking to develop bespoke VR-based solutions is the lack of guidelines around their design, development, deployment, and evaluation. Our team has produced and deployed a number of VR-based educational applications. Through reflecting on findings from surveys, interviews, observation, we summarise a range of insights into the complexity and nuances of the clinical VR design and deployment in a framework that can inform and guide educators, clinicians and developers looking to create their own VR applications for use in healthcare. [ABSTRACT FROM AUTHOR]

The Learning Health Systems (LHS) framework demonstrates the potential for iterative interrogation of health data in real time and implementation of insights into practice. Yet, the lack of appropriately skilled workforce results in an inability to leverage existing data to design innovative solutions. We developed a tailored professional development program to foster a skilled workforce. The short course is wholly online, for interdisciplinary professionals working in the digital health arena. To transform healthcare systems, the workforce needs an understanding of LHS principles, data driven approaches, and the need for diversly skilled learning communities that can tackle these complex problems together. [ABSTRACT FROM AUTHOR]

Pericardial effusion can be a sign of significant underlying diease and, in some cases, may lead to death. Post-mortem computed tomography (PMCT) is a well-established tool to assist death investigation processes in the forensic setting. In practice, the scarcity of well-trained radiologists is a challenge in processing raw whole-body PMCT images for pericardial effusion detection. In this work, we propose a Pericardial Effusion Automatic Detection (PEAD) framework to automatically process raw whole-body PMCT images to filter out the irrelevant images with heart organ absent and focus on pericardial effusion detection. In PEAD, the standard convolutional neural network architectures of VGG and ResNet are carefully modified to fit the specific characteristics of PMCT images. The experimental results prove the effectiveness of the proposed framework and modified models. The modified VGG and ResNet models achieved superior detection accuracy than the standard architecture with reduced processing speed. [ABSTRACT FROM AUTHOR]

Clinical narratives recording behaviours and emotions of patients are available from EHRs in a forensic psychiatric centre located in Tasmania. This rich data has not been used in risk prediction. Prior work demonstrates natural language processing can be used to identify patient symptoms in these free-text records and can then be used to predict risk. Four dictionaries containing descriptive words of harm were created using the Diagnostic and Statistical Manual of Mental Disorders, the Unified Medical Language System repository, English negative and positive sentiment words, and high-frequency words from the Corpus of Contemporary American English. However, a model based only on these keywords is limited in predictive power. In this study, we introduce an improved NLP approach with a social interaction component to extract additional information about the behavioural and emotional state of patients. These social interactions are subsequently used in a machine-learning model to enhance risk prediction performance. [ABSTRACT FROM AUTHOR]

We provide an outline of the Dolores chatbot designed to gather data and provide information to people living with chronic pain. Dolores is equipped with selective language levels to provide language appropriate responses for all ages. A recent pilot study (N = 60) of adolescents, young-adults and adults was completed and the frequented topics that were accessed are summarised here. [ABSTRACT FROM AUTHOR]

This study provides an overview of recent efforts to develop technologybased interventions for patients with high treatment burden. Adoption of a technological intervention for high treatment burden will depend on a range of factors, including: the reliability and accessibility of the technology, patient factors - including age, socio-economic factors, technology literacy, overall health status and personal priorities - as well as the perceived benefits provided by the technology intervention, from the perspectives of both patients and clinicians. [ABSTRACT FROM AUTHOR]

Common syntax and data semantics are core components of healthcare interoperability standards. However, interoperable data exchange processes are also needed to enable the integration of existing systems between organizations. While solutions for healthcare delivery processes are available and have been widely adopted, support for processes targeting bio-medical research is limited. Our Data Sharing Framework creates a platform to implement research processes like cohort size estimation, reviews and approvals of research proposals, consent checks, record linkage, pseudonymization and data sharing across organizations. The described framework implements a distributed business process engine for executing BPMN 2.0 processes with synchronization and data exchange using FHIR R4 resources. Our reference implementation has been rolled out to 38 organizations across three research consortia in Germany and is available as open source under the Apache 2.0 license. [ABSTRACT FROM AUTHOR]