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Walton M.,University of Sydney | Barraclough B.,Australian e Health Research Center
BMJ Quality and Safety | Year: 2013

The evidence shows that notwithstanding efforts by health professionals and hospital managers to improve the quality and safety of healthcare, adverse events remain prevalent. Clinical supervision is understandably dominated by transferring discipline knowledge and skills but the environment today requires equal attention to integrating patient safety concepts and principles into clinical supervision. Trainees learn from supervisors who themselves often have inadequate patient safety knowledge and skills. This conundrum may partly explain why there has been no visible reduction in adverse events. Patient safety literature has emphasised that clinical errors are rarely linked with incompetent doctors or trainees with inadequate knowledge but rather to failures in appreciating the context, complexity and uncertainty of clinical decisions made under the pressure of time. It is time to consider whether clinical supervisors themselves first need to demonstrate patient safety competencies before being responsible for supervising trainees. Source


Hillis D.J.,University of Melbourne | Gorton M.W.,Russell Kennedy Lawyers | Barraclough B.H.,Australian e Health Research Center | Beckett D.,University of Melbourne
Medical Journal of Australia | Year: 2015

Objective: To gain an understanding of the relative importance of the nine surgical competencies and their 27 attributes defined by the Royal Australasian College of Surgeons (RACS), which together provide the curriculum framework for today’s surgeons. Design, setting and participants: Between 9 August and 30 September 2010, trainees and Fellows of the RACS across Australia and New Zealand actively involved in educational activities rated, via questionnaire, the importance of the RACS competencies (technical expertise, communication, professionalism, medical expertise, judgement and decision making, scholarship and teaching, collaboration and teamwork, management and leadership, and health advocacy) and associated attributes. Main outcome measures: Importance of ranking competencies and their attributes for surgical education and training. Results: Of 3054 questionnaires distributed, 1834 (60%) were returned. We identified clear priorities in the perceived relative importance of the nine competencies and 27 attributes. The most important attributes were competence, insight, and recognising conditions amenable to surgery; least important were responding to community and cultural needs, supporting others, and maintaining personal health and wellbeing. Key differences were noted for the competency of collaboration and teamwork, which was ranked as more important by trainees than by Fellows. Female trainees and Fellows regarded all attributes as more important than did male trainees and Fellows. Conclusion: In a complex environment with multiple pressures, the priorities of the competencies are important. Trainees and Fellows had a very similar approach to the prioritisation of the attributes. Of concern is the lesser importance given to attributes beyond individual expertise. © 2015, Australasian Medical Publishing Co. Ltd. All Rights Reserved. Source


Rembach A.,University of Melbourne | Ryan T.M.,University of Melbourne | Roberts B.R.,University of Melbourne | Doecke J.D.,Australian e Health Research Center | And 5 more authors.
Biomarkers in Medicine | Year: 2013

Alzheimer's disease (AD) is the most common cause of dementia in the elderly population and attempts to develop therapies have been unsuccessful because there is no means to target an effective therapeutic window. CNS biomarkers are insightful but impractical for high-throughput population-based screening. Therefore, a peripheral, blood-based biomarker for AD would significantly improve early diagnosis, potentially enable presymptomatic detection and facilitate effective targeting of disease-modifying treatments. The various constituents of blood, including plasma, platelets and cellular fractions, are now being systematically explored as a pool of putative peripheral biomarkers for AD. In this review we cover some less known peripheral biomarkers and highlight the latest developments for their clinical application. © 2013 Future Medicine Ltd. Source


Ding H.,Australian e Health Research Center
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2012

Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality in Australia and globally, and leads to a substantial burden on healthcare services. Effective and timely management of patients with COPD has been essential to alleviate COPD exacerbation, improve the quality of life, and consequently reduce the economic burden. To achieve this, a mobile and internet technologies assisted home care model (M-COPD) was developed to assist clinicians to remotely monitor and manage COPD conditions and events. This paper will focus on the technical aspect of M-COPD system by describing its setup and discussing how the M-COPD could address the clinical needs in monitoring and managing COPD conditions of patients at home. Source


Wang Y.,University of New South Wales | Lin X.,University of New South Wales | Wu L.,University of Adelaide | Zhang W.,University of New South Wales | And 2 more authors.
IEEE Transactions on Image Processing | Year: 2015

More often than not, a multimedia data described by multiple features, such as color and shape features, can be naturally decomposed of multi-views. Since multi-views provide complementary information to each other, great endeavors have been dedicated by leveraging multiple views instead of a single view to achieve the better clustering performance. To effectively exploit data correlation consensus among multi-views, in this paper, we study subspace clustering for multi-view data while keeping individual views well encapsulated. For characterizing data correlations, we generate a similarity matrix in a way that high affinity values are assigned to data objects within the same subspace across views, while the correlations among data objects from distinct subspaces are minimized. Before generating this matrix, however, we should consider that multi-view data in practice might be corrupted by noise. The corrupted data will significantly downgrade clustering results. We first present a novel objective function coupled with an angular based regularizer. By minimizing this function, multiple sparse vectors are obtained for each data object as its multiple representations. In fact, these sparse vectors result from reaching data correlation consensus on all views. For tackling noise corruption, we present a sparsity-based approach that refines the angular-based data correlation. Using this approach, a more ideal data similarity matrix is generated for multi-view data. Spectral clustering is then applied to the similarity matrix to obtain the final subspace clustering. Extensive experiments have been conducted to validate the effectiveness of our proposed approach. © 1992-2012 IEEE. Source

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