Medicine (RMH) - Research Publications
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ItemRe-thinking the brain. new insights into early experience and brain development(Elsevier, 2013-08-18)The brain is a self-organizing system that adapts to its specific environment throughout pre- and postnatal life (Braun and Bock, 2011). Self-organization refers to the spontaneous formation of patterns and pattern change in open nonequilibrium systems. Edelman’s theory of neuronal group selection (Edelman, 1989) highlights this process. Groups of neurons are ‘selected’ or organized into groups or networks that are dynamically organized through epigenetic factors and experience. Developmental selection occurs largely before birth. Processes such as cell division, differentiation and programmed cell death and the mechanisms of neuronal migration are regulated by epigenetic factors. While genetics provides a general blueprint for neural development, the developmental processes are not precisely prespecified by genes, and produce unique patterns of neurons and neuronal groups in every brain. The result is a diverse pattern of connectivity forming primary repertoires of different neuronal groups. Structural diversity occurs through selective mechanical and chemical events regulated by cell and substrate adhesion molecules. A second process called experiential selection occurs postnatally through behavioural experience, resulting in modifications in the strength of synaptic connections, and creating diverse secondary repertoires. Finally, re-entrant signalling leads to the development of dynamic ‘maps’, an interconnected series of neuronal groups that independently receive inputs from the real world and create coherent perceptual constructs.
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ItemClinical data linkages in spinal cord injuries (SCI) in Australia: What are the concerns?(IGI Global, 2014-10-31)Clinical data linkage amongst patients with Spinal Cord Injury (SCI) is a challenge, as the Australian Health System is fragmented and there is lack of coordination between multiple data custodians at the state and federal levels, private and public hospitals, and acute and allied health sectors. This is particularly problematic in chronic conditions such as SCI, where multiple data custodians collect data on patients over long periods of time. The author presents findings based on interviews with a range of data custodians for SCI categorized as clinical, statutory, and financial data custodians. It is found that data are kept in different silos, which are not coordinated, hence duplication exists and patient information that exists on many different databases is inconsistently updated. This chapter describes the importance of Clinical Data Linkage for healthcare in predicting disease trajectories for SCI and discusses how administrative and clinical data are collected and stored and some of the challenges in linking these datasets.
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ItemOverview of clinical decision support systems in healthcare(IGI Global, 2016-07-18)Clinical Decision Support Systems (CDSS) are software designed to help clinicians to make decisions about patient diagnosis using technical devices such as desktops, laptops and iPads, and mobile devices, to obtain medical information and set up alert systems to monitor medication. A Clinical Decision Support System has been suggested by many as a key to a solution for improving patient safety together with Physician Based Computer Order Entry. This technology could prove to be very important in conditions such as chronic diseases where health outlay is high and where self-efficacy can affect health outcomes. However, the success of CDSS relies on technology, training and ongoing support. This chapter includes a historical overview and practical application of CDSS in medicine, and discusses challenges involved with implementation of such systems. It discusses new frontiers of CDSS and implications of self-management using social computing technologies, in particular in the management of chronic disease.