Summary Geographic variation in health care use has been demonstrated in many countries over many years. Such variation can be warranted — in response to patient need or preference for care — or unwarranted. Unwarranted variation raises concerns about equity and appropriateness of care. Recent analyses of health care provision in the Australian atlas of healthcare variation show that when routinely available Australian data are mapped by residence of patient, there are wide variations in rates of use of diagnostic tests, dispensing of prescriptions for a range of indications, surgical procedures and hospital admission rates. Despite the wealth of studies demonstrating variation in care internationally, there is relatively little research that explores the best ways of responding to unwarranted variation. Recommendations for action in the Australian Atlas focus on some approaches that could be used in Australia.

In this paper, trends in hospital service provision are measured using data on the numbers and nature of hospitals, on hospital expenditure and on hospital activity over recent years. The number of public acute care hospitals was fairly stable, however, bed numbers decreased. Hospital numbers rose for private hospitals, as did numbers of beds, particularly for group for-profit private hospitals. Recurrent health expenditure on hospitals as a proportion of all recurrent health expenditure fell, although it rose for private hospitals, and real increases in expenditure occurred for both public acute and private hospitals. Population rates for separations and patient days rose for private hospitals and were stable and fell, respectively, for public acute hospitals. Average length of stay decreased for both public acute and private hospitals, with increasing numbers of separations occurring on a same day basis. Increasing proportions of procedures were undertaken during same day stays, and in private hospitals. Separation rates varied geographically, with highest rates overall, and for public hospitals and overnight separations, for patients resident in remote centres and other remote areas. Highest rates for private hospitals were for patients resident in capital cities, other metropolitan centres and large rural centres.

This issue of the Health Information ManagementJournal has as its theme 'Health Information Management in epidemiological research', and all four papers illustrate differing ways in which Health Information Management can contribute to epidemiological endeavours. More than that, though, the papers also convey valuable messages about the importance of appropriate use of routinely collected data, and of understanding and improving the quality of the data and the infrastructures that underpin the data collections. These messages are all important for epidemiological research and other analytical uses of Australia's routinely collected health data.Michelle Bramley's paper (Bramley 2005) provides a comprehensive guide to the evaluation of health classifications, which are core components of health data collection infrastructures. The paper includes useful background information comparing classifications and terminologies, and describes the important attributes of classifications, including their mono-hierarchical structure, comprehensiveness, aggregation of multiple concepts within rubrics, and meaningful coding systems. It also details the features that good classifications should have, covering the administrative, structural, content and usability domains by which classifications can be evaluated. Practical examples of evaluating health classifications include the Anatomical, Therapeutic, Chemical classification with Defined Daily Doses (ATC/DDD) drugs classification that has been submitted for inclusion in the Australian Family of Health Classifications, and is being evaluated against the criteria for inclusion in the Family (AIHW 2005a).To guide evaluations of classifications, the paper provides useful examples to illustrate the nature of classifications and the characteristics of good classifications. This comprehensive array also provides valuable information for those who use classifications in data analysis work, including epidemiology. In addition to the explanation of mono-hierarchical structures and aggregation of multiple concepts within rubrics, the paper explains the existence of 'residual' categories: multiaxial structures; revision processes and mappings between versions; appropriate use of category descriptors; and the importance of definitions, indexes and guidelines that accompany classifications. The paper also urges readers to consider the suitability of classifications to the use proposed for them (for example, in terms of granularity), and their comparability with other classifications used in related domains or internationally. All these are important messages for data analysts.Andrew Miller's paper (Miller 2005) is an example of an endeavour that is likely to become more common: optimising interactions between data collections established for clinical purposes (increasingly as electronic health records) and data collected for administrative or epidemiological purposes, with an aim of improving the quality of data for research and monitoring activities.The paper argues that the epidemiological ...