Influences on doctors' prescribing: Is geographical remoteness a factor?

Objective: To identify factors influencing the prescribing of medicines by general practitioners in rural and remote Australia. Design: A qualitative study using a questionnaire to determine attitudes about prescribing, specific prescribing habits and comments on prescribing in ‘rural practice’. Setting: General practice in rural and remote Queensland. Subjects: General practitioners practising in rural and remote settings in Queensland (n = 258). Main outcome measures: The factors perceived to influence the prescribing of medicines by medical practitioners in rural environments. Results: A 58% response rate (n = 142) was achieved. Most respondents agreed that they prescribe differently in rural compared with city practice. The majority of respondents agreed that their prescribing was influenced by practice location, isolation of patient home location, limited diagnostic testing and increased drug monitoring. Location issues and other issues were more likely to be identified as ‘influential’ by the more isolated practitioners. Factors such as access to continuing medical education and specialists were confirmed as having an influence on prescribing. The prescribing of recently marketed drugs was more likely by doctors practising in less remote rural areas. Conclusion: Practising in rural and remote locations is perceived to have an effect on prescribing. These influences need to be considered when developing quality use of medicines policies and initiatives for these locations. What is already known: Anecdotal and audit based studies have shown that rural general practice differs to urban-based practice in Australia, including some limited data showing some variations in prescribing patterns. No substantiated explanations for these variations have been offered. It is known that interventions to change prescribing behaviour are more likely to be effective if they are perceived as relevant and hence increasing our knowledge of rural doctors’ perceptions of differences in rural practice prescribing is required. What this study adds: Rural doctors believed that they prescribe differently in rural compared with city practice and they described a range of influences. The more remotely located doctors were more likely to report the ‘rural’ influences on prescribing, however, most results failed to reach statistical significance when compared to the less remotely located doctors. These perceptions should be considered when developing medicines policy and education for rural medical practitioners to ensure it is perceived rurally relevant.

Non-linear principal components analysis: an alternative method for finding patterns in environmental data

The main purpose of this article is to gain an insight into the relationships between variables describing the environmental conditions of the Far Northern section of the Great Barrier Reef, Australia, Several of the variables describing these conditions had different measurement levels and often they had non-linear relationships. Using non-linear principal component analysis, it was possible to acquire an insight into these relationships. Furthermore. three geographical areas with unique environmental characteristics could be identified. Copyright (c) 2005 John Wiley & Sons, Ltd.

The genetic structure of Australasian green turtles (Chelonia mydas): exploring the geographical scale of genetic exchange

Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Phi = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.

The National Mental Health Strategy and Geographical Access to Mental Health Services: Some empirical results

In 1992 the Australian Government adopted the National Mental Health Strategy in an attempt to improve the provision of mental health services. A component was to improve geographical access to hospital-based mental health services. This paper is concerned with determining if this objective has been achieved. Time-series data on patients (at a regional level) with mental illness in the State of Queensland are available for the years from 1968-69 to 2002-03. A change in regional classification by the Australian Bureau of Statistics complicates the analysis by precluding certain empirical tests such as converging utilisation rates by region. To overcome this problem, it was decided to apply concepts of concentration and equality that are commonly employed in industrial economics to the regional data. The empirical results show no evidence of improving regional access following the National Mental Health Strategy: in fact the statistical results show the opposite, i.e. declining regional access.

Incorporating level set methods in Geographical Information Systems (GIS) for land-surface process modelling

Land-surface processes include a broad class of models that operate at a landscape scale. Current modelling approaches tend to be specialised towards one type of process, yet it is the interaction of processes that is increasing seen as important to obtain a more integrated approach to land management. This paper presents a technique and a tool that may be applied generically to landscape processes. The technique tracks moving interfaces across landscapes for processes such as water flow, biochemical diffusion, and plant dispersal. Its theoretical development applies a Lagrangian approach to motion over a Eulerian grid space by tracking quantities across a landscape as an evolving front. An algorithm for this technique, called level set method, is implemented in a geographical information system (GIS). It fits with a field data model in GIS and is implemented as operators in map algebra. The paper describes an implementation of the level set methods in a map algebra programming language, called MapScript, and gives example program scripts for applications in ecology and hydrology.

On aggregation issues in spatial data management

Large amounts of information can be overwhelming and costly to process, especially when transmitting data over a network. A typical modern Geographical Information System (GIS) brings all types of data together based on the geographic component of the data and provides simple point-and-click query capabilities as well as complex analysis tools. Querying a Geographical Information System, however, can be prohibitively expensive due to the large amounts of data which may need to be processed. Since the use of GIS technology has grown dramatically in the past few years, there is now a need more than ever, to provide users with the fastest and least expensive query capabilities, especially since an approximated 80 % of data stored in corporate databases has a geographical component. However, not every application requires the same, high quality data for its processing. In this paper we address the issues of reducing the cost and response time of GIS queries by preaggregating data by compromising the data accuracy and precision. We present computational issues in generation of multi-level resolutions of spatial data and show that the problem of finding the best approximation for the given region and a real value function on this region, under a predictable error, in general is "NP-complete.