Medical negligence, causation and liability for non-disclosure of risk : a post-wallace framework and critique

Through an examination of Wallace v Kam, this article considers and evaluates the law of causation in the specific context of a medical practitioner’s duty to provide information to patients concerning material risks of treatment. To supply a contextual background for the analysis which follows, Part II summarises the basic principles of causation law, while Part III provides an overview of the case and the reasoning adopted in the decisions at first instance and on appeal. With particular emphasis upon the reasoning in the courts of appeal, Part IV then examines the implications of the case in the context of other jurisprudence in this field and, in so doing, provides a framework for a structured consideration of causation issues in future non-disclosure cases under the Australian civil liability legislation. As will become clear, Wallace was fundamentally decided on the basis of policy reasoning centred upon the purpose behind the legal duty violated. Although the plurality in Rogers v Whitaker rejected the utility of expressions such as ‘the patient’s right of self-determination’ in this context, some Australian jurisprudence may be thought to frame the practitioner’s duty to warn in terms of promoting a patient’s autonomy, or right to decide whether to submit to treatment proposed. Accordingly, the impact of Wallace upon the protection of this right, and the interrelation between it and the duty to warn’s purpose, is investigated. The analysis in Part IV also evaluates the courts’ reasoning in Wallace by questioning the extent to which Wallace’s approach to liability and causal connection in non-disclosure of risk cases: depends upon the nature and classification of the risk(s) in question; and can be reconciled with the way in which patients make decisions. Finally, Part V adopts a comparative approach by considering whether the same decision might be reached if Wallace was determined according to English law.

Medical and nursing students perceived knowledge, attitudes, and practices concerning human immunodeficiency virus

Objective. To assess medical and nursing students’ knowledge, attitudes, and practices (KAP) regarding human immunodeficiency virus (HIV) in Fiji. Methods. A cross-sectional study of 275 medical and 252 nursing students that participated in a questionnaire survey on HIV KAP. Data was analysed according to their gender, program of study, and academic year. Results. The mean HIV knowledge (HK) and attitude scores were 16.0 and 41.3, respectively. Mean HK score was significantly higher in males compared to females. Significant positive correlations were found between HK and academic year for medical () and nursing () students and between HK and attitude scores (). The majority of students indicated fear in contracting HIV through clinical practice and felt that health care workers have the right to know a patients HIV status for their own safety. The majority would wear gloves to touch a patient if suspected of HIV. Conclusions. The study found a high level of HIV knowledge and positive attitude towards HIV patients. However, respondents also displayed negative attitudes and unacceptable practices probably due to fear. Training institutions need to ensure that students gain accurate knowledge on HIV especially on transmission routes to allay the fear of caring for HIV-infected patients.

Approaching wicked problems through design thinking

This paper explores possible ways in which design thinking can be used to understand the issues involved in wicked problems. Following brief reviews of both the design thinking and wicked problems literature, we offer a synthesis of these two areas. This paper distinguishes the connections of the various thinking styles inherent in design thinking methodologies and approaches to the phases of wicked problems. We create links between design thinking and cognitive mechanisms such as thinking styles, simple heuristics and schemas that can deepen understanding and effective decision making in the wicked problems in our complex environments.

Statistical methods for electromyography data and associated problems

This thesis proposes three novel models which extend the statistical methodology for motor unit number estimation, a clinical neurology technique. Motor unit number estimation is important in the treatment of degenerative muscular diseases and, potentially, spinal injury. Additionally, a recent and untested statistic to enable statistical model choice is found to be a practical alternative for larger datasets. The existing methods for dose finding in dual-agent clinical trials are found to be suitable only for designs of modest dimensions. The model choice case-study is the first of its kind containing interesting results using so-called unit information prior distributions.

Adaptive finite element analysis of elliptic problems based on bubble-type local mesh generation

A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.

Translocation of bats as a conservation strategy : previous attempts and potential problems

Translocation is an increasingly popular conservation tool from which a wide range of taxa have benefited. However, to our knowledge, bats have not been translocated successfully. Bats differ behaviourally, morphologically and physiologically from the taxa for which translocation the- ory has been developed, so existing guidelines may not be directly transferable. We review previous translocations of bats and discuss characteristics of bats that may require special consideration dur- ing translocation. Their vagility and homing ability, coloniality, roost requirements, potential ability to transmit diseases, susceptibility to anthropomorphic impacts, and cryptic nature have implications for establishing populations, effects of these populations on the release site, and ability to monitor translocation success following release. We hope that our discussion of potential problems will be able to supplement the existing, more generic guidelines to provide a starting point for the planning of bat translocations.

Meta-analysis of prevalence

Meta-analysis is a method to obtain a weighted average of results from various studies. In addition to pooling effect sizes, meta-analysis can also be used to estimate disease frequencies, such as incidence and prevalence. In this article we present methods for the meta-analysis of prevalence. We discuss the logit and double arcsine transformations to stabilise the variance. We note the special situation of multiple category prevalence, and propose solutions to the problems that arise. We describe the implementation of these methods in the MetaXL software, and present a simulation study and the example of multiple sclerosis from the Global Burden of Disease 2010 project. We conclude that the double arcsine transformation is preferred over the logit, and that the MetaXL implementation of multiple category prevalence is an improvement in the methodology of the meta-analysis of prevalence.

Using upper bounds on attainable discrimination to select discrete valued features

Selection of features that will permit accurate pattern classification is a difficult task. However, if a particular data set is represented by discrete valued features, it becomes possible to determine empirically the contribution that each feature makes to the discrimination between classes. This paper extends the discrimination bound method so that both the maximum and average discrimination expected on unseen test data can be estimated. These estimation techniques are the basis of a backwards elimination algorithm that can be use to rank features in order of their discriminative power. Two problems are used to demonstrate this feature selection process: classification of the Mushroom Database, and a real-world, pregnancy related medical risk prediction task - assessment of risk of perinatal death.

Stefan problems for melting nanoscaled particles

Under certain conditions, the mathematical models governing the melting of nano-sized particles predict unphysical results, which suggests these models are incomplete. This thesis studies the addition of different physical effects to these models, using analytic and numerical techniques to obtain realistic and meaningful results. In particular, the mathematical "blow-up" of solutions to ill-posed Stefan problems is examined, and the regularisation of this blow-up via kinetic undercooling. Other effects such as surface tension, density change and size-dependent latent heat of fusion are also analysed.

Nursing Management : Fluid, Electrolyte, and Acid-Base Imbalances

Lewis’s Medical-Surgical Nursing: Assessment and Management of Clinical Problems, 4th Edition is the most comprehensive go-to reference for essential information about all aspects of professional nursing care of patients. Using the nursing process as a framework for practice, the fourth edition has been extensively revised to reflect the rapid changing nature of nursing practice and the increasing focus on key nursing care priorities. Building on the strengths of the third Australian and New Zealand edition and incorporating relevant global nursing research and practice from the prominent US title Medical-Surgical Nursing, 9Th Edition, Lewis’s Medical-Surgical Nursing, 4th Edition is an essential resource for students seeking to understand the role of the professional nurse in the contemporary health environment.

Altered Immune Responses and Transplantation

Lewis’s Medical-Surgical Nursing: Assessment and Management of Clinical Problems, 4th Edition is the most comprehensive go-to reference for essential information about all aspects of professional nursing care of patients. Using the nursing process as a framework for practice, the fourth edition has been extensively revised to reflect the rapid changing nature of nursing practice and the increasing focus on key nursing care priorities. Building on the strengths of the third Australian and New Zealand edition and incorporating relevant global nursing research and practice from the prominent US title Medical-Surgical Nursing, 9Th Edition, Lewis’s Medical-Surgical Nursing, 4th Edition is an essential resource for students seeking to understand the role of the professional nurse in the contemporary health environment.

Multi-modal deformable medical image registration

Non-rigid image registration is an essential tool required for overcoming the inherent local anatomical variations that exist between images acquired from different individuals or atlases. Furthermore, certain applications require this type of registration to operate across images acquired from different imaging modalities. One popular local approach for estimating this registration is a block matching procedure utilising the mutual information criterion. However, previous block matching procedures generate a sparse deformation field containing displacement estimates at uniformly spaced locations. This neglects to make use of the evidence that block matching results are dependent on the amount of local information content. This paper presents a solution to this drawback by proposing the use of a Reversible Jump Markov Chain Monte Carlo statistical procedure to optimally select grid points of interest. Three different methods are then compared to propagate the estimated sparse deformation field to the entire image including a thin-plate spline warp, Gaussian convolution, and a hybrid fluid technique. Results show that non-rigid registration can be improved by using the proposed algorithm to optimally select grid points of interest.