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Tag: health research

Health, Passion, Career: A chat with Director of Health Services Management Centre about her journey

Health PhD candidate Jo Khoo was a guest host alongside Dr Amalie Dyda on the soundcloud podcast “Stories in Public Health”  interviewing with the Director of Health Services Management Centre Professor Judith Smith, University of Birmingham. In the podcast, Professor Judith Smith shares her professional journey into health services research and management. Her own research

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PhD Candidate published in Health Journal

Congratulations to our health PhD James John, who published his paper in the International Journal of Environmental Research and Public Health. John’s paper provides an understanding of the various social determinants and health behavioural risk factors associated with dental caries among primary school children in the rural community of Lithgow. Mr James John partners with

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DAVID JONAS FEATURED IN HEALTH IT NEWS

Health IT News has published David Jonas’s article on their online magazine. In this article Mr Jonas highlights that there is a strong case for digital health research and development that will improve individuals’ and communities’ health and well being, and this can advance the Australian economy by helping to enable a more connected, transparent and competitive

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CMCRC HEALTH PHD STUDENTS AT HSRAANZ CONFERENCE

The 10th Health Services and Policy Research Conference was held from 1-3 November 2017 at Surfers Paradise Marriott on the Gold Coast. The conference theme was “Shifting priorities: balancing acute and primary care services”. The conference was presented by the Health Services Research Association of Australia and New Zealand and hosted by the Australian Centre

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CMCRC HEALTH PHD PRESENTS AT HEALTH FORUM

Well done to Health PhD Amir Marashi who presented his work at the ’45 and Up Study Annual Forum 2017’. Mr Marashi spoke on the association between physical activity and incidence of chronic health conditions in the Australian population aged 45 years and over which was well received. Recently, Amir also appeared with two of

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HEALTH TEAM’S MEDICATION MANAGEMENT WORKSHOP A SUCCESS

Professor Libby Roughead from University of South Australia shared some of her valuable experiences and topical insights into the issue of medication management at CMCRC recently with selected industry partners and researchers. Professor Roughead is the lead academic on medication management in the proposed Digital Health CRC. The result of the first round bid for

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JOINT PREDICTION OF ONSET CHRONIC CONDITIONS

Chronic conditions can be costly but also preventable as well as predictable. We develop a model to predict in the short term (2-3 years) the onset of one or more chronic conditions. Five chronic conditions are considered: heart disease, stroke, diabetes, hypertension and cancer. Predictions are made on the basis of standard demographic/socio-economic variables, risk

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PREDICTING CHRONIC DISEASES FROM HEALTHCARE DATA-A FRAMEWORK BASED ON GRAPH THEORY AND SOCIAL NETWORK MEASURES

The study illustrates a framework to predict the progression of chronic diseases from a new perspective using graph theory and social network analysis methods. The framework utilizes large and untapped longitudinal administrative data sets that contain ICD-10-AM disease codes that describe the principal and secondary diagnosis recorded during hospital admissions. The primary focus of the

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ADAPTING GRAPH THEORY AND SOCIAL NETWORK MEASURES ON HEALTHCARE DATA – A NEW FRAMEWORK TO UNDERSTAND CHRONIC DISEASE PROGRESSION

The paper presents an approach that applies social network theory to understand chronic disease progression. Submitted to the Australasian Workshop on Health Informatics and Knowledge Management  https://cs.anu.edu.au/conf/acsw2016/sub-confs/hikm.html Author(s): Arif Khan, Shahadat Uddin and Uma Srinivasan

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LEVERAGING BIG DATA ANALYTICS TO REDUCE HEALTHCARE COSTS

The healthcare sector deals with large volumes of electronic data related to patient services. This article describes two novel applications that leverage big data to detect fraud, abuse, waste, and errors in health insurance claims, thus reducing recurrent losses and facilitating enhanced patient care. The results indicate that claim anomalies detected using these applications help

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