Issues facing the future health care workforce: the importance of demand modelling

This article examines issues facing the future health care workforce in Australia in light of factors such as population ageing. It has been argued that population ageing in Australia is affecting the supply of health care professionals as the health workforce ages and at the same time increasing the demand for health care services and the health care workforce

Falls, Depression and Antidepressants in Later Life: A Large Primary Care Appraisal

BACKGROUND: Depression and falls are common and co-exist for older people. Safe management of each of these conditions is important to quality of life. METHODS: A cross-sectional survey was used to examine medication use associated with injurious and non-injurious falls in 21,900 community-dwelling adults, aged 60 years or over from 383 Australian general practices recruited for the DEPS-GP Project. Falls and injury from falls, medication use, depressive symptoms (Primary Health Questionnaire (PHQ-9)), clinical morbidity, suicidal ideation and intent, health status (SF-12 Health Survey), demographic and lifestyle information was reported in a standardised survey. FINDINGS: Respondents were 71.8 years (sd 7.7) of age and 58.4% were women. 24% 11% and 8% reported falls, fall related injury, and sought medical attention respectively. Antidepressant use (odds ratio, OR: 1.46; 95% confidence interval, 95%CI: 1.25, 1.70), questionable depression (5-14 on PHQ OR: 1.32, 95%CI: 1.13, 1.53) and clinically significant symptoms of depression (15 or more on PHQ OR: 1.70, 95%CI: 1.14, 1.50) were independently associated with multiple falls. SSRI use was associated with the highest risk of multiple falls (OR: 1.66, 95%CI: 1.36, 2.02) amongst all psychotropic medications. Similar associations were observed for injurious falls. Over 60% of those with four accumulated risk factors had multiple falls in the previous year (OR: 3.40, 95%CI: 1.79, 6.45); adjusted for other demographic and health factors. INTERPRETATION: Antidepressant use (particularly SSRIs) was strongly associated with falls regardless of presence of depressive symptoms. Strategies to prevent falls should become a routine part of the management of older people with depression

Incorporating Texture Information into Dimensionality Reduction for High-Dimensional Images

High-dimensional imaging is becoming increasingly relevant in many fields from astronomy and cultural heritage to systems biology. Visual exploration of such high-dimensional data is commonly facilitated by dimensionality reduction. However, common dimensionality reduction methods do not include spatial information present in images, such as local texture features, into the construction of low-dimensional embeddings. Consequently, exploration of such data is typically split into a step focusing on the attribute space followed by a step focusing on spatial information, or vice versa. In this paper, we present a method for incorporating spatial neighborhood information into distance-based dimensionality reduction methods, such as t-Distributed Stochastic Neighbor Embedding (t-SNE). We achieve this by modifying the distance measure between high-dimensional attribute vectors associated with each pixel such that it takes the pixel's spatial neighborhood into account. Based on a classification of different methods for comparing image patches, we explore a number of different approaches. We compare these approaches from a theoretical and experimental point of view. Finally, we illustrate the value of the proposed methods by qualitative and quantitative evaluation on synthetic data and two real-world use cases.</p

Incorporating Texture Information into Dimensionality Reduction for High-Dimensional Images

High-dimensional imaging is becoming increasingly relevant in many fields from astronomy and cultural heritage to systems biology. Visual exploration of such high-dimensional data is commonly facilitated by dimensionality reduction. However, common dimensionality reduction methods do not include spatial information present in images, such as local texture features, into the construction of low-dimensional embeddings. Consequently, exploration of such data is typically split into a step focusing on the attribute space followed by a step focusing on spatial information, or vice versa. In this paper, we present a method for incorporating spatial neighborhood information into distance-based dimensionality reduction methods, such as t-Distributed Stochastic Neighbor Embedding (t-SNE). We achieve this by modifying the distance measure between high-dimensional attribute vectors associated with each pixel such that it takes the pixel's spatial neighborhood into account. Based on a classification of different methods for comparing image patches, we explore a number of different approaches. We compare these approaches from a theoretical and experimental point of view. Finally, we illustrate the value of the proposed methods by qualitative and quantitative evaluation on synthetic data and two real-world use cases.Comp Graphics & Visualisatio

Prefabrication and Preassembly Trends and Effects on the Construction Workforce

The purpose of this project was to determine prefabrication and preassembly trends and effects on the construction workforce. Twenty-nine managers from across the United States were surveyed. Based on their responses, it was estimated that prefabrication and preassembly increased by approximately 86% from 1984 to 1999. For prefabrication and preassembly work, those surveyed generally agreed that productivity and safety levels are higher, skill levels are the same, and wage levels are lower. These results can be factored into future project and supply chain strategiesRay Marshall Center for the Study of Human Resource