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Geographical classifications to guide rural health policy in Australia

Geographical classifications to guide rural health policy in Australia The Australian Government's recent decision to replace the Rural Remote and Metropolitan Area (RRMA) classification with the Australian Standard Geographical Classification - Remoteness Areas (ASGC-RA) system highlights the ongoing significance of geographical classifications for rural health policy, particularly in relation to improving the rural health workforce supply. None of the existing classifications, including the government's preferred choice, were designed specifically to guide health resource allocation, and all exhibit strong weaknesses when applied as such. Continuing reliance on these classifications as policy tools will continue to result in inappropriate health program resource distribution. Purely 'geographical' classifications alone cannot capture all relevant aspects of rural health service provision within a single measure. Moreover, because many subjective decisions (such as the choice of algorithm and breakdown of groupings) influence a classification's impact and acceptance from its users, policy-makers need to specify explicitly the purpose and role of their different programs as the basis for developing and implementing appropriate decision tools such as 'rural-urban' classifications. Failure to do so will continue to limit the effectiveness that current rural health support and incentive programs can have in achieving their objective of improving the provision of health care services to rural populations though affirmative action programs. result of no longer qualifying for additional incentive pay- Introduction "From 1 July 2009, the outdated and flawed Rural, ments associated with degree of rurality and remoteness. Remote and Metropolitan Areas (RRMA) system will be In addition to the direct impact, the indirect effects of replaced by the Australian Standard Geographical Classi- income supplementation in attracting health workforce to fication - Remoteness Areas (ASGC-RA) system" [1]. The areas that are traditionally difficult to recruit and retain ongoing significance of geographical classification have major repercussions for residents and services in schema as the basis for significant health resource alloca- these areas. Although there is no 'natural' classification of tion was highlighted again with the above announcement what constitutes 'rural' or 'remote', it is recognised that the in the Australian Government 2009 Budget. The implica- way in which populations and communities are delimited tions and impacts of these changes have already been as urban, rural and remote has important implications for noted in the media [2-6], with health practitioners, organ- health care planning and policy. Rural Australia, which isations and professional associations immediately contains approximately one-third of the population expressing concern about potential loss of income as a (ASGC-RA, excluding Major Cities), is extremely heteroge- Page 1 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 neous, comprising vast regions of sparsely populated and SLAs) by utilising a one kilometre grid that covers all mostly uninhabitable areas along with small isolated of Australia. The ARIA classification, intentionally rural towns and larger regional centres. Vast distances sep- designed to measure geographical remoteness, is cal- arating many of these localities, often in combination culated using road distances separating localities from with their small population base, mean that the delivery four levels of service centres distinguished by popula- of health care services to most of rural and remote Aus- tion size. The final ARIA score is determined by aggre- tralia requires funding assistance through the allocation gating these four measures of remoteness, which are of resources to compensate for disadvantages associated then separated into five hierarchical ('natural break') with geography [7]. Decisions underpinning the distribu- categories. tion of these resources need to be made using geographi- cal classification formulae. Since this issue was discussed iii. In 2001, the Australian Bureau of Statistics (ABS) a decade ago [8], significant policy changes have occurred adopted a slightly altered methodology, referred to as that have only served to heighten the significance of how ARIA+ [14,15], with one key difference being the addi- different classifications, which form the basis for resource tion of a fifth service centre level. From this, a new funding, are determined. The aim of this paper is to show classification known as ASGC-RA superseded ARIA. why geographical classifications have such an important Additionally, ASGC-RA adopted a different set of hier- influence for workforce recruitment and retention policies archical categories, with five defined again but utilis- and incentives in non-metropolitan areas. In particular, ing a different range of scores and a different set of this paper critically reviews the design of current geo- category labels. graphical classifications used in Australia and their appro- priateness as the basis for rural health workforce policy Table 1 summarises some of the strengths and weaknesses and resource allocation. identified within these three classifications [15-17]. The key strength of the ARIA and ASGC-RA classifications is that they were designed to directly address all the weak- Current geographical classifications used in nesses of RRMA by improving the flexibility, precision, Australia Australia has always been a key player in the development stability and clearer conceptualisation [15,18]. However, of geographical classifications designed to capture or until now, RRMA remains a key classification within rural measure comparative degrees of rurality and remoteness health policy, with many specific purpose programs still (see for example Lonsdale & Holmes [9]; Logan et al. using it as a decision tool [19]. This is mainly due to its [10]). Three classifications, the Rural, Remote and Metro- simple and intuitive application and because the ARIA politan Area (RRMA), the Accessibility/Remoteness Index and ASGC-RA classifications are not viewed as being supe- of Australia (ARIA) and the Australian Standard Geo- rior measures for many rural populations [17,20]. All graphical Classification Remoteness Areas (ASGC-RA, three classifications are deeply ingrained within Austral- originating from ARIA), have dominated recent rural ian rural health policy, even though none were originally health policy in Australia: designed or intended for use as resource allocation deci- sion tools. i. The RRMA classification had its origins in the Department of Primary Industries and Energy and the The significance of geographical classifications Department of Community Services and Health, and for rural health policy was released in 1994 [11]. This classification divides In Australia and internationally, the supply of health care all Statistical Local Areas (SLAs) of Australia into three practitioners is problematic in many rural areas. Rural zones, namely metropolitan, rural and remote and a populations generally experience decreased accessibility total of seven categories across these zones. The sepa- and diminished availability of health care services, partic- ration of rural and remote zones is determined using a ularly as distance from capital or major cities increases method earlier developed by Arundell [12], by weight- and local population size decreases. This occurs most ing five indicators that measure population density notably in the case of GPs because of their critical role and straight - line distances to various population cen- within the health care system [21,22], but also for other tres. Significantly, after the identification of remote important services including those provided by dentists, areas, separation into the seven categories of rurality pharmacists and allied health professionals [19,23,24]. was determined solely based on the size of the largest Recruitment and retention difficulties of the rural and population centre within each SLA. remote health workforce stem from many associated fac- tors, including practice characteristics and professional ii. The ARIA classification, developed by GISCA, was support, personal/family lifestyle issues, and geographi- released in 1999 [13]. Unlike RRMA, ARIA is not cal/community factors [25]. In response, over the last restricted to using pre - defined spatial units (e.g. twenty years the Australian Government has provided Page 2 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 Table 1: Summary of strengths and weaknesses of the RRMA, ARIA and ASGC Remoteness classifications Classification Strengths Weaknesses RRMA • RRMA is a simple tool to apply both for research and � The restriction to SLA boundaries, resulting in large, administration purposes, including the allocation of health heterogeneous areas being equally classified. resources. � Due to the strong influence of population size, RRMA often � The use of straight-line distances and SLA centroids, which equally classifies towns of similar size (intuitive). can result in highly imprecise measures. � The use of three zones (metropolitan, rural and remote) is � The use of population density is meaningless because of the reasonably logical. varying size and nature of SLA boundaries. � RRMA is preferred by many national organisations over ASGC � RRMA has never been updated and still uses 1991 Remoteness population counts. ARIA � The flexibility to measure remoteness at any geographic � Only measures geographical remoteness, giving many boundary level by using a one kilometre grid. examples of highly dissimilar towns having the same classification (e.g. Port Macquarie and Gundagai). � The additional precision from using road distances and service � The separation of the five remoteness categories is town locations, rather than straight line distances and SLA somewhat subjective. centroids. � The clearer conceptualisation of measuring only geographical � Penalises smaller, more densely populated states (e.g. over remoteness of localities (e.g. not muddied by also measuring 75% of rural Victoria's population is defined as 'highly density). accessible'. � Use of the category label 'accessible' and the term 'accessibility' within its name (it is not a measure of access) ASGC-RA � All points listed under ARIA, plus: � All points listed under ARIA (except the last point), plus: � More refined methodology � Extreme heterogeneity within some areas, especially Inner (additional service centre category, better separation of major Regional and sometimes Outer Regional cities) � A change of labels including the use of 'regional' rather than 'accessible' � Updated by ABS as part of the ASGC additional incentives and resources to rural and remote affects the eligibility and amount that different rural com- areas characterised as difficult to recruit to or retain serv- munities receive and consequently how well the problem ices within. At last count (mid - 2009), the Department of of workforce shortages in rural areas is addressed. As we Health and Ageing manages approximately 66 current see in Table 1, all classifications have weaknesses. The programs along with a number of additional state-based Australian Government has recognised, to some degree, programs, largely because mainstream programs do not the inappropriateness of currently used classifications rec- adequately meet the needs of practitioners in rural and ognised for rural health policy decisions [27,28], though remote communities [26]. In order to target the distribu- their recent response of selecting ASGC-RA highlights the tion of these limited resources, some variant of the RRMA, lack of any explicit rationale for their adoption of what is ARIA or ASGC-RA classifications have frequently been arguably a sub-optimal solution. used as the basis for differentiating both entitlement to, and nature of, financial and support incentives. For exam- What determines a satisfactory solution? ple, the Rural Retention Program uses the GPARIA classi- To date, there appears to have been a desire by policy- fication (a variant of ARIA, which measures both makers and others for a single all-purpose classification to population remoteness and GP professional isolation), guide the distribution of health care resources to rural while rural loadings which range from 15% to 50% in the communities, without significant debate about whether Practice Incentives Program (PIP) are based on RRMA cat- the defining variable is the degree of 'rurality' or 'remote- egories. ness' or some other aspect of accessibility, disadvantage or contextual factor that underpins the problems associated A critical question is whether these classifications are the with health care provision in these eligible areas. Numer- most appropriate bases for the distribution of these ous authors have debated "what is rural" and sought def- important but limited resources. Given that there is no initions based on characteristics such as low population 'natural' rural urban classification, it follows that deci- density and small population centres, isolated popula- sions made about where you draw the boundary differen- tions and large distances, as well as observed environmen- tiating 'urban' from 'rural' or 'rural' from 'remote' directly tal, agricultural and other economic activities [29-33]. In Page 3 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 reality, the related concepts of rurality and remoteness are i. The Griffith Service Access Frame (GSAF) is one clas- multi-faceted, thus precluding agreement on one univer- sification that measures access disadvantage in rela- sally accepted classification [8,31,34]. Nonetheless, gov- tion to education services, and is intentionally ernments continue to seek some agreed objective measure designed as a tool for resource allocation [48,49]. The or classification on which to base their resource allocation GSAF is characterised by measuring access only to the decisions. This search is not limited to Australia, with a nearest service option, and has been adopted by many number of alternate classifications in existence [35-42], Australian states in the distribution of rural (educa- but generally these too only capture similar elements of tion) resources. Such an option may be an appropriate rurality and so they offer no significant design alternative method for measuring access to hospital and specialist to the Australian classifications. care services in the field of health. Table 2 provides a summary of important characteristics ii. More recently, McGrail's new index of rural access, and related required decisions associated with any geo- tested in Victoria, has been developed as a more graphical classification. The first and most important dis- appropriate measure of access to primary care services tinction is to be clear about its purpose; that is, what is the in rural areas [50,51]. This index is specifically classification designed to measure. For example, the designed to include the key elements of access to GPs ASGC-RA classification was unambiguously designed to (availability, proximity, mobility and health needs), measure geographical remoteness of populations. On the utilise more appropriate advanced accessibility meth- other hand, the RRMA classification captures some ele- ods (modified two-step floating catchment areas ments of 'rurality' including population size and density. [52,53]) and use the smallest feasible geographical Within each classification method, subjective decisions units (collection districts). are required that determine its outcomes and the conse- quent degree of acceptance by users. These decision points iii. The GPARIA classification, a modified version of include the choice of algorithm, the number of groupings the ARIA classification, was specifically developed for and how they are determined, as well as the size of spatial the purpose of distributing Rural Retention Program units. The RRMA classification, despite its inherent weak- grants to GPs working in rural and remote communi- nesses, is still preferred by many groups over the ASGC-RA ties. GPARIA measures both remoteness and isolation classification [43-47], chiefly because of its ability to dis- by incorporating proximity to nearby GPs of both the criminate between areas at a finer geographical scale, population and GPs in its construction. How well this thereby giving somewhat more homogenous groupings. classification adequately differentiates all aspects of Rather than continue to search for a single solution that factors affecting retention decisions across rural and suits all applications, it is more appropriate to develop remote communities is a moot point. classifications closely aligned with a specific defined pur- pose. A number of examples illustrate what can be iv. The District of Workforce Shortage (DWS) status is achieved: a simple yes or no stratification for all Statistical Local Table 2: Summary of decisions required regarding important characteristics of geographical classifications Important characteristics Decisions required - sources of subjectivity Be clear on specific objectives and purpose of the classification as this Is it remoteness, isolation, access, disadvantage, rurality or something determines what is being measured else? If it is an access classification, then what aspect of access is being measured, and in relation to what service - (e.g. GPs as a measure of primary care) The choice of algorithm or procedure for grouping similar clusters Accessibility can be measured by distance to nearest service, service matters provider to population ratios, or increasingly sophisticated methods such as floating catchments and distance-decay The criteria and cut-off points underpinning groups matters How many groups do you want? At what point do you differentiate between groups? (e.g. Is the decision based on minimising within-group and maximising between- group variance, or is the number arbitrarily defined by convenience for the end-user?) The choice of spatial units matters RRMA is often criticised for its use of Statistical Local Areas (which can be large in rural areas), but the more extreme use of 1 km grids such as ASGC-RA is typically not an option for most data required. Page 4 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 Areas (SLAs), which has been regularly updated every priately applied--arguably the case with the use of the quarter for over 10 years using Medicare data [54]. An RRMA, ARIA and ASGC-RA classifications in rural health area's DWS status reflects whether the ratio between policy in Australia. We argue that the recent 'official' selec- population size and the number of services provided tion of the ASGC-RA classification over RRMA or ARIA for within an SLA is below the national average. It should resource allocation in Australia will see the continuation be noted, however, that its value is questionable of inappropriate distribution of many rural health pro- because population-provider ratios are a poor meas- grams. This review has highlighted the improbability that ure of access, particularly for 'small' rural areas [52,55] one solution can be satisfactorily applied in all purposes. and its dichotomous definition does not allow small In relation to rural health funding distribution, programs areal variations to be detected. However, new methods are designed as incentives or compensation for working in such as McGrail's index of access can improve its appli- areas characterised by aspects such as low levels of access, cation. high isolation, high disadvantage, small population base and greater complexity of activity. Geographical classifica- In addition to forming the basis for resource allocation tions by themselves cannot capture all these aspects decisions, geographical classifications are often used as within a single measure. It may be more appropriate to statistical tools to guide rural health research, and, in par- develop a suite of classifications that are explicitly and ticular, the presentation of results such as health outcome unambiguously designed to meet the requirements of a measures in evaluating the effectiveness and quality of specific purpose, such as McGrail's new index of rural health care [56,57], or through measuring service utilisa- access or the Griffith Service Access Frame. Any classifica- tion rates as an indicator of need for services [22]. A few tion of rural communities must ensure that people experi- other examples include the association between cancer encing similar characteristics and problems of location survival rates and ARIA [58], the association between pri- and environment fall within similar categories. mary care management of chronic heart failure and RRMA [59], the association between Attention Deficit Hyperac- Arguably, this is a major weakness of the preferred ASGC- tivity Disorder (ADHD) treatment and ASGC-RA [60], or RA classification, because it often categorises highly dis- the association between mental health status and RRMA similar localities as being 'equal' (such as Bendigo-- large [61] or ARIA [62]. Measures of the extent to which services regional centre with a population of almost 100,000 and and interventions are resulting in improvements in the Rushworth--small rural town with a population of only health status of rural Australians are contingent upon how 1,000). Clearly, clinicians based in locations such as these rural is defined. are likely to experience contrasting issues that require dif- ferent support policies. It follows that any adjustment to The use of inappropriate classifications can serve to mask the current formulae underpinning resource allocation or average-out important health inequities that character- will inevitably create 'winners' and 'losers'. However, fail- ise rural communities. Many authors have failed to fully ure to do so limits the effectiveness that these programs appreciate the significance of rural delimitation. Simply can have in achieving their objective of maintaining or bundling together places of diversity (heterogeneous) improving the equitable provision of health care services into convenient (presumed homogenous) categories to rural populations. often obscures the inherent variations within rural areas [63] and seriously affects the resultant pattern of health Competing interests status and differentiation [64]. Many possible covariates, The authors declare that they have no competing interests. such as differing demographics, socio-economic status, access to health services and health behaviour, are fre- Authors' contributions quently not included within statistical reports that are MM conceived and developed the main themes of this broken down by geography, despite their possible influ- manuscript. MM and JH collaborated in drafting and ence on the extent to which apparent associations with approving the final manuscript. rurality are significant. In short, while significant associa- tions between geographical classifications and various References 1. Department of Health and Ageing: Health Budget 2009 - 2010: health and health service outcomes are interesting, they Rudd Government Confronts the Rural Health Challenge. often conceal the true effect within rural populations. [http://www.health.gov.au/internet/budget/publishing.nsf/Content/ budget2009-hmedia04.htm]. 2. Ferguson H: The great divide. Australian Doctor 2009. Conclusion 3. East M: Rural reform backlash. Australian Doctor 2009. Geographical classifications are a significant part of rural 4. Edwards V: Town suffers loss of its rural status. The Australian health workforce policy, as the government endeavours to 2009. 5. McNaught M: Country Victorian GPs to flock back to city. Her- improve or at least maintain the rural health workforce ald Sun 2009. supply. However, these classifications are often inappro- Page 5 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 6. Shanahan L: Zone plan 'will close' hospitals in rural areas. The 30. Halfacree KH: Locality and social representation: space, dis- Age 2009. course and alternative defintions of the rural. J Rural Stud 1993, 7. Humphreys JS, Wakerman J, Wells R: What do we mean by sus- 9:23-37. tainable rural health services? Implications for rural health 31. Hart LG, Larson EH, Lishner DM: Rural definitions for health pol- research. Aust J Rural Health 2006, 14:33-35. icy and research. Am J Public Health 2005, 95:1149-1155. 8. Humphreys J: Delimiting 'rural': implications of an agreed 32. Hoggart K: Not a definition of rural. Area 1988, 20:35-40. 'rurality' index for healthcare planning and resource alloca- 33. Bosak J, Perlman B: A review of the definition of rural. J Rural tion. Aust J Rural Health 1998, 6:212-216. Commun Psychol 1982, 3:3-34. 9. Lonsdale R, Holmes JH: Settlement systems in sparsely populated regions: 34. Humphreys J: Differential designations of 'rural':Implications the United States and Australia New York, N.Y.: Pergamon Press; 1981. for health research, policy and programs. 3rd National Confer- 10. Logan M, Maher C, McKay J, Humphreys JS: Urban and regional Aus- ence on Health Research in Rural and Remote Canada: Methodological tralia: analysis and policy issues Malvern, Vic: Sorrett Publishing; 1975. Issues of Rurality and Rural Health Workshop; October 23; Halifax, Nova 11. Department of Primary Industries and Energy and Department of Scotia 2002. Human Services and Health: Rural, remote and metropolitan 35. Swan G, Selvaraj S, Godden D: Clinical peripherality: character- areas classification 1991 census edition. Canberra: Australian ising remote and rural primary care. Report to Scottish Execu- Government Publishing Service; 1994. tive Remote and Rural Areas Resource Initiative: University of 12. Arundell L: Rural, remote and metropolitan zones classifica- Aberdeen, Centre for Rural Health; 2004. tion: a classification of Australia as at 30 June 1986 and a 36. Leduc E: Defining rurality: a general practice rurality index for methodology for 1991 census data. Canberra: Rural & Provincial Canada. Can J Rural Med 1997, 2:125-131. Policy Unit, Department of Primary Industries and Energy; 1991. 37. Janes R, London M: Rural general practitioners in New Zea- 13. Department of Health and Aged Care, National Key Centre for Social land: November 1999 census. N Z Fam Physician 2001, Applications of Geographical Information Systems: Accessibility/ 28:244-249. Remoteness Index of Australia (ARIA). In Occasional Papers 38. Ocana-Riola R, Sanchez-Cantalejo C: Rurality index for small Series No. 6 Canberra: DHAC; 1999. areas in Spain. SocIndic Res 2005, 73:247-266. 14. Australian Bureau of Statistics: ASGC remoteness classification: 39. Harrington V, O'Donoghue D: Rurality in England and Wales purpose and use. In Census Paper No. 03/01 Canberra: ABS; 2003. 1991: a replication and extension of the 1981 rurality index. 15. Department of Health and Aged Care: Measuring remoteness: Sociol Ruralis 1998, 38:178-203. Accessibility/Remoteness Index of Australia (ARIA). In Occa- 40. du Plessis V, Beshiri R, Bollman RD, Clemenson H: Definitions of sional Papers: New Series Number 14 Canberra: DHAC; 2001. "rural". In Agriculture and Rural Working Paper No. 61, Cat. No. 21 - 16. Australian Institute of Health and Welfare: Rural, regional and 601 - MIE Ottawa, Ontario: Statistics Canada; 2002. remote health: a guide to remoteness classifications. In AIHW 41. Hewitt M: Defining "rural" areas: impact on health care policy Cat. No. PHE 53 Canberra: AIHW; 2004. and research. Staff Paper: Office of Technology Assessment; 1989. 17. Griffith DA: Chalk or cheese? Distinguishing between access 42. Ricketts TC, Johnson-Webb KD, Taylor P: Definitions of rural: a disadvantage and geographic classifications in Australia. 11th handbook for health policy makers and researchers. Federal Biennial Conference of the Australian Population Association; 2 - 4 October; Office of Rural Health Policy; 1998. Sydney, Australia 2002. 43. Australian Rural & Remote Workforce Agencies Group: Review of 18. Aylward R, Bamford E, Hugo G, Taylor D: A comparison of the the Rural and Remote Metropolitan Areas (RRMA) classifi- ARIA (Accessibility/Remoteness Index of Australia) and cation system. Melbourne: ARRWAG; 2005. RRMA (Rural, Remote and Metropolitan Areas Classifica- 44. Rural Doctors Association of Australia: Review of the Rural, tion) methodologies for measuring remoteness inAustralia. Remote and Metropolitan Areas (RRMA) classification. Can- Final Draft to the Commonwealth Department of Health and Aged berra: RDAA; 2005. Care:National Key Centre for Social Applications of Geographical 45. Australian Divisions of General Practice: The Australian Divisions Information Systems(GISCA); 2000. of General Practice response to the review of the Rural, 19. Department of Health and Ageing: Report on the audit of health Remote and Metropolitan Areas (RRMA) classification: dis- workforce in rural and regional Australia. Canberra: Common- cussion paper. Canberra: ADGP; 2005. wealth of Australia; 2008. 46. Australian Medical Association: Submission to the review of the 20. Kosmina S, Greacen J: Access to health services in densely pop- Rural, Remote and Metropolitan Areas (RRMA) classifica- ulated rural regions. 7th National Rural Health Conference; Hobart, tion. Canberra: AMA; 2005. Australia 2003. 47. Royal Australian College of General Practitioners: RACGP submis- 21. Starfield B, Shi L, Macinko J: Contribution of primary care to sion to the Australian Government Department of Health health systems and health. Milbank Q 2005, 83:457-502. and Ageing's review of the RRMA classification. Melbourne: 22. Department of Health and Ageing: General practice in Australia: RACGP; 2005. 2004. Canberra:DoHA; 2005. 48. Griffith DA: Quantifying access to services in remote and rural 23. Access Economics: An analysis of the widening gap between Australia. Rural Education and Research Association Conference; 15-19 community need and the availability of GP services. Can- February; Alice Springs, Australia 1992. berra: Access Economics; 2002. 49. Griffith DA: Development of a spatial model to quantify 24. Primary Health Care Research & Information Service: Key division access to services in rural and remote areas of Australia. In of general practice characteristics 2005-2006. [http:www.phc- PhD Northern Territory University, Faculty of Arts; 1997. ris.org.au/products/asd/keycharacteristic/KeyDGPstatis tics.xls]. 50. McGrail MR, Humphreys JS: The index of rural access: an inno- 25. Humphreys J, Jones J, Jones M, Hugo G, Bamford E, Taylor D: A crit- vative integrated approach for measuring primary care ical review of rural medical workforce retention in Australia. access. BMC Health Serv Res 2009, 9:124. Aust Health Rev 2001, 24:91-102. 51. McGrail MR, Humphreys JS: A new index of access to primary 26. Department of Health and Ageing: Programs and initiatives. care services in rural areas. Aust N Z J Public Health 2009, [http://www.health.gov.au/internet/main/publishing.nsf/Content/pro 33:418-423. grams-initiatives-all]. 52. McGrail MR, Humphreys JS: Measuring spatial accessibility to 27. Australian Labour Party: Media release: workforce audit reveals primary care in rural areas: improving the effectiveness of challenges for rural health. [http://www.health.gov.au/internet/ the two - step floating catchment area method. Appl Geogr ministers/publishing.nsf/Content/ 2009, 29:533-541. 17880E40910B58A9CA25743B0015866C/$File/nr056.pdf]. 53. Wang F, Luo W: Assessing spatial and nonspatial factors for 28. Department of Health and Ageing: Review of the Rural, Remote healthcare access: towards an integrated approach to defin- and Metropolitan Areas (RRMA) classification. In Discussion ing health professional shortage areas. Health Place 2005, Paper (without prejudice) Canberra: DHAC; 2005. 11:131-146. 29. Miller M, Luloff A: Who is rural? A typological approach to the 54. Department of Health and Ageing: District of Workforce Short- examination of rurality. Rural Sociol 1981, 46:608-625. age. [http://www.doctorconnect.gov.au/internet/otd/Publishing.nsf/ Content/District+of+Workforce+Shortage]. Page 6 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 55. Guagliardo MF: Spatial accessibility of primary care:concepts, methods and challenges. Int J Health Geogr 2004, 3:3. 56. Australian Institute of Health and Welfare: Health in rural and remote Australia. In AIHW Cat. No. PHE 6 Canberra: AIHW; 1998. 57. Australian Institute of Health and Welfare: Rural, regional and remote health: indicators of health status and determinants of health. Rural health series no. 9. In AIHW Cat. No. PHE 97 Canberra: AIHW; 2008. 58. Jong KE, Smith DP, Yu XQ, O'Connell DL, Goldstein D, Armstrong BK: Remoteness of residence and survival from cancer in New South Wales. Med J Aust 2004, 180:618-622. 59. Clark RA, Eckert KA, Stewart S, Phillips SM, Yallop J, Tonkin A, Krum H: Rural and urban differentials in primary care management of chronic heart failure: new data from the CASE study. Med J Aust 2007, 186:441-445. 60. Calver J, Preen D, Bulsara M, Sanfilippo F: Stimulant prescribing for the treatment of ADHD in Western Australia: socioeco- nomic and remoteness differences. Med J Aust 2007, 186:124-127. 61. Caldwell TM, Jorm AF, Dear KBG: Suicide and mental health in rural, remote and metropolitan areas in Australia. Med J Aust 2004, 181:S10-S14. 62. Murray G, Judd F, Jackson H, Fraser C, Komiti A, Hodgins G, Pattison P, Humphreys J, Robins G: Rurality and mental health: the role of accessibility. Aust N Z J Psychiatry 2004, 38:629-634. 63. Higgs G: Investigating trends in rural health outcomes: a research agenda. Geoforum 1999, 30:203-221. 64. Smith KB, Humphreys JS, Wilson MGA: Addressing the health dis- advantage of rural populations: How does epidemiological evidence inform rural health policies and research? Aust J Rural Health 2008, 16:56-66. Publish with Bio Med Central and every scientist can read your work free of charge "BioMed Central will be the most significant development for disseminating the results of biomedical researc h in our lifetime." 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Geographical classifications to guide rural health policy in Australia

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Springer Journals
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Copyright © 2009 by McGrail and Humphreys; licensee BioMed Central Ltd.
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Medicine & Public Health; Public Health; Social Policy
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1743-8462
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1743-8462
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10.1186/1743-8462-6-28
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19995449
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Abstract

The Australian Government's recent decision to replace the Rural Remote and Metropolitan Area (RRMA) classification with the Australian Standard Geographical Classification - Remoteness Areas (ASGC-RA) system highlights the ongoing significance of geographical classifications for rural health policy, particularly in relation to improving the rural health workforce supply. None of the existing classifications, including the government's preferred choice, were designed specifically to guide health resource allocation, and all exhibit strong weaknesses when applied as such. Continuing reliance on these classifications as policy tools will continue to result in inappropriate health program resource distribution. Purely 'geographical' classifications alone cannot capture all relevant aspects of rural health service provision within a single measure. Moreover, because many subjective decisions (such as the choice of algorithm and breakdown of groupings) influence a classification's impact and acceptance from its users, policy-makers need to specify explicitly the purpose and role of their different programs as the basis for developing and implementing appropriate decision tools such as 'rural-urban' classifications. Failure to do so will continue to limit the effectiveness that current rural health support and incentive programs can have in achieving their objective of improving the provision of health care services to rural populations though affirmative action programs. result of no longer qualifying for additional incentive pay- Introduction "From 1 July 2009, the outdated and flawed Rural, ments associated with degree of rurality and remoteness. Remote and Metropolitan Areas (RRMA) system will be In addition to the direct impact, the indirect effects of replaced by the Australian Standard Geographical Classi- income supplementation in attracting health workforce to fication - Remoteness Areas (ASGC-RA) system" [1]. The areas that are traditionally difficult to recruit and retain ongoing significance of geographical classification have major repercussions for residents and services in schema as the basis for significant health resource alloca- these areas. Although there is no 'natural' classification of tion was highlighted again with the above announcement what constitutes 'rural' or 'remote', it is recognised that the in the Australian Government 2009 Budget. The implica- way in which populations and communities are delimited tions and impacts of these changes have already been as urban, rural and remote has important implications for noted in the media [2-6], with health practitioners, organ- health care planning and policy. Rural Australia, which isations and professional associations immediately contains approximately one-third of the population expressing concern about potential loss of income as a (ASGC-RA, excluding Major Cities), is extremely heteroge- Page 1 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 neous, comprising vast regions of sparsely populated and SLAs) by utilising a one kilometre grid that covers all mostly uninhabitable areas along with small isolated of Australia. The ARIA classification, intentionally rural towns and larger regional centres. Vast distances sep- designed to measure geographical remoteness, is cal- arating many of these localities, often in combination culated using road distances separating localities from with their small population base, mean that the delivery four levels of service centres distinguished by popula- of health care services to most of rural and remote Aus- tion size. The final ARIA score is determined by aggre- tralia requires funding assistance through the allocation gating these four measures of remoteness, which are of resources to compensate for disadvantages associated then separated into five hierarchical ('natural break') with geography [7]. Decisions underpinning the distribu- categories. tion of these resources need to be made using geographi- cal classification formulae. Since this issue was discussed iii. In 2001, the Australian Bureau of Statistics (ABS) a decade ago [8], significant policy changes have occurred adopted a slightly altered methodology, referred to as that have only served to heighten the significance of how ARIA+ [14,15], with one key difference being the addi- different classifications, which form the basis for resource tion of a fifth service centre level. From this, a new funding, are determined. The aim of this paper is to show classification known as ASGC-RA superseded ARIA. why geographical classifications have such an important Additionally, ASGC-RA adopted a different set of hier- influence for workforce recruitment and retention policies archical categories, with five defined again but utilis- and incentives in non-metropolitan areas. In particular, ing a different range of scores and a different set of this paper critically reviews the design of current geo- category labels. graphical classifications used in Australia and their appro- priateness as the basis for rural health workforce policy Table 1 summarises some of the strengths and weaknesses and resource allocation. identified within these three classifications [15-17]. The key strength of the ARIA and ASGC-RA classifications is that they were designed to directly address all the weak- Current geographical classifications used in nesses of RRMA by improving the flexibility, precision, Australia Australia has always been a key player in the development stability and clearer conceptualisation [15,18]. However, of geographical classifications designed to capture or until now, RRMA remains a key classification within rural measure comparative degrees of rurality and remoteness health policy, with many specific purpose programs still (see for example Lonsdale & Holmes [9]; Logan et al. using it as a decision tool [19]. This is mainly due to its [10]). Three classifications, the Rural, Remote and Metro- simple and intuitive application and because the ARIA politan Area (RRMA), the Accessibility/Remoteness Index and ASGC-RA classifications are not viewed as being supe- of Australia (ARIA) and the Australian Standard Geo- rior measures for many rural populations [17,20]. All graphical Classification Remoteness Areas (ASGC-RA, three classifications are deeply ingrained within Austral- originating from ARIA), have dominated recent rural ian rural health policy, even though none were originally health policy in Australia: designed or intended for use as resource allocation deci- sion tools. i. The RRMA classification had its origins in the Department of Primary Industries and Energy and the The significance of geographical classifications Department of Community Services and Health, and for rural health policy was released in 1994 [11]. This classification divides In Australia and internationally, the supply of health care all Statistical Local Areas (SLAs) of Australia into three practitioners is problematic in many rural areas. Rural zones, namely metropolitan, rural and remote and a populations generally experience decreased accessibility total of seven categories across these zones. The sepa- and diminished availability of health care services, partic- ration of rural and remote zones is determined using a ularly as distance from capital or major cities increases method earlier developed by Arundell [12], by weight- and local population size decreases. This occurs most ing five indicators that measure population density notably in the case of GPs because of their critical role and straight - line distances to various population cen- within the health care system [21,22], but also for other tres. Significantly, after the identification of remote important services including those provided by dentists, areas, separation into the seven categories of rurality pharmacists and allied health professionals [19,23,24]. was determined solely based on the size of the largest Recruitment and retention difficulties of the rural and population centre within each SLA. remote health workforce stem from many associated fac- tors, including practice characteristics and professional ii. The ARIA classification, developed by GISCA, was support, personal/family lifestyle issues, and geographi- released in 1999 [13]. Unlike RRMA, ARIA is not cal/community factors [25]. In response, over the last restricted to using pre - defined spatial units (e.g. twenty years the Australian Government has provided Page 2 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 Table 1: Summary of strengths and weaknesses of the RRMA, ARIA and ASGC Remoteness classifications Classification Strengths Weaknesses RRMA • RRMA is a simple tool to apply both for research and � The restriction to SLA boundaries, resulting in large, administration purposes, including the allocation of health heterogeneous areas being equally classified. resources. � Due to the strong influence of population size, RRMA often � The use of straight-line distances and SLA centroids, which equally classifies towns of similar size (intuitive). can result in highly imprecise measures. � The use of three zones (metropolitan, rural and remote) is � The use of population density is meaningless because of the reasonably logical. varying size and nature of SLA boundaries. � RRMA is preferred by many national organisations over ASGC � RRMA has never been updated and still uses 1991 Remoteness population counts. ARIA � The flexibility to measure remoteness at any geographic � Only measures geographical remoteness, giving many boundary level by using a one kilometre grid. examples of highly dissimilar towns having the same classification (e.g. Port Macquarie and Gundagai). � The additional precision from using road distances and service � The separation of the five remoteness categories is town locations, rather than straight line distances and SLA somewhat subjective. centroids. � The clearer conceptualisation of measuring only geographical � Penalises smaller, more densely populated states (e.g. over remoteness of localities (e.g. not muddied by also measuring 75% of rural Victoria's population is defined as 'highly density). accessible'. � Use of the category label 'accessible' and the term 'accessibility' within its name (it is not a measure of access) ASGC-RA � All points listed under ARIA, plus: � All points listed under ARIA (except the last point), plus: � More refined methodology � Extreme heterogeneity within some areas, especially Inner (additional service centre category, better separation of major Regional and sometimes Outer Regional cities) � A change of labels including the use of 'regional' rather than 'accessible' � Updated by ABS as part of the ASGC additional incentives and resources to rural and remote affects the eligibility and amount that different rural com- areas characterised as difficult to recruit to or retain serv- munities receive and consequently how well the problem ices within. At last count (mid - 2009), the Department of of workforce shortages in rural areas is addressed. As we Health and Ageing manages approximately 66 current see in Table 1, all classifications have weaknesses. The programs along with a number of additional state-based Australian Government has recognised, to some degree, programs, largely because mainstream programs do not the inappropriateness of currently used classifications rec- adequately meet the needs of practitioners in rural and ognised for rural health policy decisions [27,28], though remote communities [26]. In order to target the distribu- their recent response of selecting ASGC-RA highlights the tion of these limited resources, some variant of the RRMA, lack of any explicit rationale for their adoption of what is ARIA or ASGC-RA classifications have frequently been arguably a sub-optimal solution. used as the basis for differentiating both entitlement to, and nature of, financial and support incentives. For exam- What determines a satisfactory solution? ple, the Rural Retention Program uses the GPARIA classi- To date, there appears to have been a desire by policy- fication (a variant of ARIA, which measures both makers and others for a single all-purpose classification to population remoteness and GP professional isolation), guide the distribution of health care resources to rural while rural loadings which range from 15% to 50% in the communities, without significant debate about whether Practice Incentives Program (PIP) are based on RRMA cat- the defining variable is the degree of 'rurality' or 'remote- egories. ness' or some other aspect of accessibility, disadvantage or contextual factor that underpins the problems associated A critical question is whether these classifications are the with health care provision in these eligible areas. Numer- most appropriate bases for the distribution of these ous authors have debated "what is rural" and sought def- important but limited resources. Given that there is no initions based on characteristics such as low population 'natural' rural urban classification, it follows that deci- density and small population centres, isolated popula- sions made about where you draw the boundary differen- tions and large distances, as well as observed environmen- tiating 'urban' from 'rural' or 'rural' from 'remote' directly tal, agricultural and other economic activities [29-33]. In Page 3 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 reality, the related concepts of rurality and remoteness are i. The Griffith Service Access Frame (GSAF) is one clas- multi-faceted, thus precluding agreement on one univer- sification that measures access disadvantage in rela- sally accepted classification [8,31,34]. Nonetheless, gov- tion to education services, and is intentionally ernments continue to seek some agreed objective measure designed as a tool for resource allocation [48,49]. The or classification on which to base their resource allocation GSAF is characterised by measuring access only to the decisions. This search is not limited to Australia, with a nearest service option, and has been adopted by many number of alternate classifications in existence [35-42], Australian states in the distribution of rural (educa- but generally these too only capture similar elements of tion) resources. Such an option may be an appropriate rurality and so they offer no significant design alternative method for measuring access to hospital and specialist to the Australian classifications. care services in the field of health. Table 2 provides a summary of important characteristics ii. More recently, McGrail's new index of rural access, and related required decisions associated with any geo- tested in Victoria, has been developed as a more graphical classification. The first and most important dis- appropriate measure of access to primary care services tinction is to be clear about its purpose; that is, what is the in rural areas [50,51]. This index is specifically classification designed to measure. For example, the designed to include the key elements of access to GPs ASGC-RA classification was unambiguously designed to (availability, proximity, mobility and health needs), measure geographical remoteness of populations. On the utilise more appropriate advanced accessibility meth- other hand, the RRMA classification captures some ele- ods (modified two-step floating catchment areas ments of 'rurality' including population size and density. [52,53]) and use the smallest feasible geographical Within each classification method, subjective decisions units (collection districts). are required that determine its outcomes and the conse- quent degree of acceptance by users. These decision points iii. The GPARIA classification, a modified version of include the choice of algorithm, the number of groupings the ARIA classification, was specifically developed for and how they are determined, as well as the size of spatial the purpose of distributing Rural Retention Program units. The RRMA classification, despite its inherent weak- grants to GPs working in rural and remote communi- nesses, is still preferred by many groups over the ASGC-RA ties. GPARIA measures both remoteness and isolation classification [43-47], chiefly because of its ability to dis- by incorporating proximity to nearby GPs of both the criminate between areas at a finer geographical scale, population and GPs in its construction. How well this thereby giving somewhat more homogenous groupings. classification adequately differentiates all aspects of Rather than continue to search for a single solution that factors affecting retention decisions across rural and suits all applications, it is more appropriate to develop remote communities is a moot point. classifications closely aligned with a specific defined pur- pose. A number of examples illustrate what can be iv. The District of Workforce Shortage (DWS) status is achieved: a simple yes or no stratification for all Statistical Local Table 2: Summary of decisions required regarding important characteristics of geographical classifications Important characteristics Decisions required - sources of subjectivity Be clear on specific objectives and purpose of the classification as this Is it remoteness, isolation, access, disadvantage, rurality or something determines what is being measured else? If it is an access classification, then what aspect of access is being measured, and in relation to what service - (e.g. GPs as a measure of primary care) The choice of algorithm or procedure for grouping similar clusters Accessibility can be measured by distance to nearest service, service matters provider to population ratios, or increasingly sophisticated methods such as floating catchments and distance-decay The criteria and cut-off points underpinning groups matters How many groups do you want? At what point do you differentiate between groups? (e.g. Is the decision based on minimising within-group and maximising between- group variance, or is the number arbitrarily defined by convenience for the end-user?) The choice of spatial units matters RRMA is often criticised for its use of Statistical Local Areas (which can be large in rural areas), but the more extreme use of 1 km grids such as ASGC-RA is typically not an option for most data required. Page 4 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 Areas (SLAs), which has been regularly updated every priately applied--arguably the case with the use of the quarter for over 10 years using Medicare data [54]. An RRMA, ARIA and ASGC-RA classifications in rural health area's DWS status reflects whether the ratio between policy in Australia. We argue that the recent 'official' selec- population size and the number of services provided tion of the ASGC-RA classification over RRMA or ARIA for within an SLA is below the national average. It should resource allocation in Australia will see the continuation be noted, however, that its value is questionable of inappropriate distribution of many rural health pro- because population-provider ratios are a poor meas- grams. This review has highlighted the improbability that ure of access, particularly for 'small' rural areas [52,55] one solution can be satisfactorily applied in all purposes. and its dichotomous definition does not allow small In relation to rural health funding distribution, programs areal variations to be detected. However, new methods are designed as incentives or compensation for working in such as McGrail's index of access can improve its appli- areas characterised by aspects such as low levels of access, cation. high isolation, high disadvantage, small population base and greater complexity of activity. Geographical classifica- In addition to forming the basis for resource allocation tions by themselves cannot capture all these aspects decisions, geographical classifications are often used as within a single measure. It may be more appropriate to statistical tools to guide rural health research, and, in par- develop a suite of classifications that are explicitly and ticular, the presentation of results such as health outcome unambiguously designed to meet the requirements of a measures in evaluating the effectiveness and quality of specific purpose, such as McGrail's new index of rural health care [56,57], or through measuring service utilisa- access or the Griffith Service Access Frame. Any classifica- tion rates as an indicator of need for services [22]. A few tion of rural communities must ensure that people experi- other examples include the association between cancer encing similar characteristics and problems of location survival rates and ARIA [58], the association between pri- and environment fall within similar categories. mary care management of chronic heart failure and RRMA [59], the association between Attention Deficit Hyperac- Arguably, this is a major weakness of the preferred ASGC- tivity Disorder (ADHD) treatment and ASGC-RA [60], or RA classification, because it often categorises highly dis- the association between mental health status and RRMA similar localities as being 'equal' (such as Bendigo-- large [61] or ARIA [62]. Measures of the extent to which services regional centre with a population of almost 100,000 and and interventions are resulting in improvements in the Rushworth--small rural town with a population of only health status of rural Australians are contingent upon how 1,000). Clearly, clinicians based in locations such as these rural is defined. are likely to experience contrasting issues that require dif- ferent support policies. It follows that any adjustment to The use of inappropriate classifications can serve to mask the current formulae underpinning resource allocation or average-out important health inequities that character- will inevitably create 'winners' and 'losers'. However, fail- ise rural communities. Many authors have failed to fully ure to do so limits the effectiveness that these programs appreciate the significance of rural delimitation. Simply can have in achieving their objective of maintaining or bundling together places of diversity (heterogeneous) improving the equitable provision of health care services into convenient (presumed homogenous) categories to rural populations. often obscures the inherent variations within rural areas [63] and seriously affects the resultant pattern of health Competing interests status and differentiation [64]. Many possible covariates, The authors declare that they have no competing interests. such as differing demographics, socio-economic status, access to health services and health behaviour, are fre- Authors' contributions quently not included within statistical reports that are MM conceived and developed the main themes of this broken down by geography, despite their possible influ- manuscript. MM and JH collaborated in drafting and ence on the extent to which apparent associations with approving the final manuscript. rurality are significant. In short, while significant associa- tions between geographical classifications and various References 1. Department of Health and Ageing: Health Budget 2009 - 2010: health and health service outcomes are interesting, they Rudd Government Confronts the Rural Health Challenge. often conceal the true effect within rural populations. [http://www.health.gov.au/internet/budget/publishing.nsf/Content/ budget2009-hmedia04.htm]. 2. Ferguson H: The great divide. Australian Doctor 2009. Conclusion 3. East M: Rural reform backlash. Australian Doctor 2009. Geographical classifications are a significant part of rural 4. Edwards V: Town suffers loss of its rural status. The Australian health workforce policy, as the government endeavours to 2009. 5. McNaught M: Country Victorian GPs to flock back to city. Her- improve or at least maintain the rural health workforce ald Sun 2009. supply. However, these classifications are often inappro- Page 5 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 6. Shanahan L: Zone plan 'will close' hospitals in rural areas. The 30. Halfacree KH: Locality and social representation: space, dis- Age 2009. course and alternative defintions of the rural. J Rural Stud 1993, 7. Humphreys JS, Wakerman J, Wells R: What do we mean by sus- 9:23-37. tainable rural health services? Implications for rural health 31. Hart LG, Larson EH, Lishner DM: Rural definitions for health pol- research. Aust J Rural Health 2006, 14:33-35. icy and research. Am J Public Health 2005, 95:1149-1155. 8. Humphreys J: Delimiting 'rural': implications of an agreed 32. Hoggart K: Not a definition of rural. Area 1988, 20:35-40. 'rurality' index for healthcare planning and resource alloca- 33. Bosak J, Perlman B: A review of the definition of rural. J Rural tion. Aust J Rural Health 1998, 6:212-216. Commun Psychol 1982, 3:3-34. 9. Lonsdale R, Holmes JH: Settlement systems in sparsely populated regions: 34. Humphreys J: Differential designations of 'rural':Implications the United States and Australia New York, N.Y.: Pergamon Press; 1981. for health research, policy and programs. 3rd National Confer- 10. Logan M, Maher C, McKay J, Humphreys JS: Urban and regional Aus- ence on Health Research in Rural and Remote Canada: Methodological tralia: analysis and policy issues Malvern, Vic: Sorrett Publishing; 1975. Issues of Rurality and Rural Health Workshop; October 23; Halifax, Nova 11. Department of Primary Industries and Energy and Department of Scotia 2002. Human Services and Health: Rural, remote and metropolitan 35. Swan G, Selvaraj S, Godden D: Clinical peripherality: character- areas classification 1991 census edition. Canberra: Australian ising remote and rural primary care. Report to Scottish Execu- Government Publishing Service; 1994. tive Remote and Rural Areas Resource Initiative: University of 12. Arundell L: Rural, remote and metropolitan zones classifica- Aberdeen, Centre for Rural Health; 2004. tion: a classification of Australia as at 30 June 1986 and a 36. Leduc E: Defining rurality: a general practice rurality index for methodology for 1991 census data. Canberra: Rural & Provincial Canada. Can J Rural Med 1997, 2:125-131. Policy Unit, Department of Primary Industries and Energy; 1991. 37. Janes R, London M: Rural general practitioners in New Zea- 13. Department of Health and Aged Care, National Key Centre for Social land: November 1999 census. N Z Fam Physician 2001, Applications of Geographical Information Systems: Accessibility/ 28:244-249. Remoteness Index of Australia (ARIA). In Occasional Papers 38. Ocana-Riola R, Sanchez-Cantalejo C: Rurality index for small Series No. 6 Canberra: DHAC; 1999. areas in Spain. SocIndic Res 2005, 73:247-266. 14. Australian Bureau of Statistics: ASGC remoteness classification: 39. Harrington V, O'Donoghue D: Rurality in England and Wales purpose and use. In Census Paper No. 03/01 Canberra: ABS; 2003. 1991: a replication and extension of the 1981 rurality index. 15. Department of Health and Aged Care: Measuring remoteness: Sociol Ruralis 1998, 38:178-203. Accessibility/Remoteness Index of Australia (ARIA). In Occa- 40. du Plessis V, Beshiri R, Bollman RD, Clemenson H: Definitions of sional Papers: New Series Number 14 Canberra: DHAC; 2001. "rural". In Agriculture and Rural Working Paper No. 61, Cat. No. 21 - 16. Australian Institute of Health and Welfare: Rural, regional and 601 - MIE Ottawa, Ontario: Statistics Canada; 2002. remote health: a guide to remoteness classifications. In AIHW 41. Hewitt M: Defining "rural" areas: impact on health care policy Cat. No. PHE 53 Canberra: AIHW; 2004. and research. Staff Paper: Office of Technology Assessment; 1989. 17. Griffith DA: Chalk or cheese? Distinguishing between access 42. Ricketts TC, Johnson-Webb KD, Taylor P: Definitions of rural: a disadvantage and geographic classifications in Australia. 11th handbook for health policy makers and researchers. Federal Biennial Conference of the Australian Population Association; 2 - 4 October; Office of Rural Health Policy; 1998. Sydney, Australia 2002. 43. Australian Rural & Remote Workforce Agencies Group: Review of 18. Aylward R, Bamford E, Hugo G, Taylor D: A comparison of the the Rural and Remote Metropolitan Areas (RRMA) classifi- ARIA (Accessibility/Remoteness Index of Australia) and cation system. Melbourne: ARRWAG; 2005. RRMA (Rural, Remote and Metropolitan Areas Classifica- 44. Rural Doctors Association of Australia: Review of the Rural, tion) methodologies for measuring remoteness inAustralia. Remote and Metropolitan Areas (RRMA) classification. Can- Final Draft to the Commonwealth Department of Health and Aged berra: RDAA; 2005. Care:National Key Centre for Social Applications of Geographical 45. Australian Divisions of General Practice: The Australian Divisions Information Systems(GISCA); 2000. of General Practice response to the review of the Rural, 19. Department of Health and Ageing: Report on the audit of health Remote and Metropolitan Areas (RRMA) classification: dis- workforce in rural and regional Australia. Canberra: Common- cussion paper. Canberra: ADGP; 2005. wealth of Australia; 2008. 46. Australian Medical Association: Submission to the review of the 20. Kosmina S, Greacen J: Access to health services in densely pop- Rural, Remote and Metropolitan Areas (RRMA) classifica- ulated rural regions. 7th National Rural Health Conference; Hobart, tion. Canberra: AMA; 2005. Australia 2003. 47. Royal Australian College of General Practitioners: RACGP submis- 21. Starfield B, Shi L, Macinko J: Contribution of primary care to sion to the Australian Government Department of Health health systems and health. Milbank Q 2005, 83:457-502. and Ageing's review of the RRMA classification. Melbourne: 22. Department of Health and Ageing: General practice in Australia: RACGP; 2005. 2004. Canberra:DoHA; 2005. 48. Griffith DA: Quantifying access to services in remote and rural 23. Access Economics: An analysis of the widening gap between Australia. Rural Education and Research Association Conference; 15-19 community need and the availability of GP services. Can- February; Alice Springs, Australia 1992. berra: Access Economics; 2002. 49. Griffith DA: Development of a spatial model to quantify 24. Primary Health Care Research & Information Service: Key division access to services in rural and remote areas of Australia. In of general practice characteristics 2005-2006. [http:www.phc- PhD Northern Territory University, Faculty of Arts; 1997. ris.org.au/products/asd/keycharacteristic/KeyDGPstatis tics.xls]. 50. McGrail MR, Humphreys JS: The index of rural access: an inno- 25. Humphreys J, Jones J, Jones M, Hugo G, Bamford E, Taylor D: A crit- vative integrated approach for measuring primary care ical review of rural medical workforce retention in Australia. access. BMC Health Serv Res 2009, 9:124. Aust Health Rev 2001, 24:91-102. 51. McGrail MR, Humphreys JS: A new index of access to primary 26. Department of Health and Ageing: Programs and initiatives. care services in rural areas. Aust N Z J Public Health 2009, [http://www.health.gov.au/internet/main/publishing.nsf/Content/pro 33:418-423. grams-initiatives-all]. 52. McGrail MR, Humphreys JS: Measuring spatial accessibility to 27. Australian Labour Party: Media release: workforce audit reveals primary care in rural areas: improving the effectiveness of challenges for rural health. [http://www.health.gov.au/internet/ the two - step floating catchment area method. Appl Geogr ministers/publishing.nsf/Content/ 2009, 29:533-541. 17880E40910B58A9CA25743B0015866C/$File/nr056.pdf]. 53. Wang F, Luo W: Assessing spatial and nonspatial factors for 28. Department of Health and Ageing: Review of the Rural, Remote healthcare access: towards an integrated approach to defin- and Metropolitan Areas (RRMA) classification. In Discussion ing health professional shortage areas. Health Place 2005, Paper (without prejudice) Canberra: DHAC; 2005. 11:131-146. 29. Miller M, Luloff A: Who is rural? A typological approach to the 54. Department of Health and Ageing: District of Workforce Short- examination of rurality. Rural Sociol 1981, 46:608-625. age. [http://www.doctorconnect.gov.au/internet/otd/Publishing.nsf/ Content/District+of+Workforce+Shortage]. Page 6 of 7 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:28 http://www.anzhealthpolicy.com/content/6/1/28 55. Guagliardo MF: Spatial accessibility of primary care:concepts, methods and challenges. Int J Health Geogr 2004, 3:3. 56. Australian Institute of Health and Welfare: Health in rural and remote Australia. In AIHW Cat. No. PHE 6 Canberra: AIHW; 1998. 57. Australian Institute of Health and Welfare: Rural, regional and remote health: indicators of health status and determinants of health. Rural health series no. 9. In AIHW Cat. No. PHE 97 Canberra: AIHW; 2008. 58. Jong KE, Smith DP, Yu XQ, O'Connell DL, Goldstein D, Armstrong BK: Remoteness of residence and survival from cancer in New South Wales. Med J Aust 2004, 180:618-622. 59. Clark RA, Eckert KA, Stewart S, Phillips SM, Yallop J, Tonkin A, Krum H: Rural and urban differentials in primary care management of chronic heart failure: new data from the CASE study. Med J Aust 2007, 186:441-445. 60. Calver J, Preen D, Bulsara M, Sanfilippo F: Stimulant prescribing for the treatment of ADHD in Western Australia: socioeco- nomic and remoteness differences. Med J Aust 2007, 186:124-127. 61. Caldwell TM, Jorm AF, Dear KBG: Suicide and mental health in rural, remote and metropolitan areas in Australia. Med J Aust 2004, 181:S10-S14. 62. Murray G, Judd F, Jackson H, Fraser C, Komiti A, Hodgins G, Pattison P, Humphreys J, Robins G: Rurality and mental health: the role of accessibility. Aust N Z J Psychiatry 2004, 38:629-634. 63. Higgs G: Investigating trends in rural health outcomes: a research agenda. Geoforum 1999, 30:203-221. 64. Smith KB, Humphreys JS, Wilson MGA: Addressing the health dis- advantage of rural populations: How does epidemiological evidence inform rural health policies and research? Aust J Rural Health 2008, 16:56-66. Publish with Bio Med Central and every scientist can read your work free of charge "BioMed Central will be the most significant development for disseminating the results of biomedical researc h in our lifetime." Sir Paul Nurse, Cancer Research UK Your research papers will be: available free of charge to the entire biomedical community peer reviewed and published immediately upon acceptance cited in PubMed and archived on PubMed Central yours — you keep the copyright BioMedcentral Submit your manuscript here: http://www.biomedcentral.com/info/publishing_adv.asp Page 7 of 7 (page number not for citation purposes)

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