Abstract
A number of small area geographies are used in Australia to investigate primary care relevant outcomes/behaviours and to manage the supply of Primary Care Providers (PCP) that influence these outcomes. However, very little research exists on the choice of a small area geography suitable for these purposes. We evaluated a large basket of Australian small area geographies to determine which geography is optimal for investigating relationships between PCP supply and the use of PCP services. We used linked data to evaluate the relationship between PCP supply and the likelihood of a patient visiting a PCP, after adjusting for individual level covariates. PCP supply was measured at different geographies including Local Government Areas (LGAs), Primary Health Networks (PHNs), Statistical Areas-1/2/3 and Remoteness Areas. Overall, the strongest relationships between PCP density and PCP use were found when LGAs were used to measure PCP density. Large geographies such as PHNs also detected strong relationships while custom built geographies such as Primary Care Service Areas were not significantly better than the rest. Existing geographies such as LGAs may be suitable for investigating the effect of PCP supply at state or national scales.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The FWE workload metric is similar to the Full Time Equivalent metric, except that it does not cap the maximum workload at 1. The FWE metric assumes a given number of hours (pre-set) as having workload equivalent of 1 FWE or full time. Any hours worked beyond that pre-set threshold are accounted into the FWE calculation. Thus someon e working 20% more than full time is 1.2 FWE.
References
ABS (2016a). 2033.0.55.001- Census of Population and Housing: Socio-economic indexes for areas (SEIFA), Australia, 2011. Accessed November, 2016 2016.
ABS (2016b). Remoteness Structure. http://www.abs.gov.au/websitedbs/d3310114.nsf/home/remoteness+structure. Accessed November, 30 2016.
Amrhein, C. G. (1995). Searching for the elusive aggregation effect: evidence from statistical simulations. Environment and Planning A, 27(1), 105–119.
Andersen, R., & Aday, L. A. (1978). Access to medical Care in the U.S.: realized and potential. Medical Care, 16(7), 533–546.
Andersen, R. M. (1995). Revisiting the Behavioral Model and Access to Medical Care: Does it Matter? Journal of Health and Social Behavior, 36(1), 1–10%* Copyright © 1995 American Sociological Association %U http://www.jstor.org/stable/2137284.
Banks, E., Redman, S., Jorm, L., Armstrong, B., Bauman, A., Beard, J., et al. (2008). Cohort profile: the 45 and up study. International Journal of Epidemiology, 37(5), 941–947. https://doi.org/10.1093/ije/dym184.
Dartmouth Institute (2010). New South Wales Health Care Atlas Final Report. http://trove.nla.gov.au/work/152260401?selectedversion=NBD47125956: The Dartmouth institute of health policy and clinical practice.
DoctorConnect (2016). District of workforce shortage. http://www.doctorconnect.gov.au/internet/otd/publishing.nsf/content/dwsfactsheet. Accessed November 18 2016.
Duckett, S., & Breadon, P. (2013). Access all areas: New solutions for GP shortages in rural Australia (pp. 5–9). Melbourne: Grattan Institute.
Glover, J., Hetzel, D., Glover, L., Tennant, S., & Page, A. (2016). A social health atlas of South Australia. Adelaide: The University of Adelaide.
Hames Sharley (2013). Stirling city Centre community needs assessment. Hames Sharley.
HealthStats NSW (2016). General practitioner visits by children, prevalence. http://www.healthstats.nsw.gov.au/Indicator/bod_gpvisitkid/bod_gpvisitkid_lhn. Accessed 30 November 2016.
Hill, A. B. (1965). The environment and disease: Association or causation? Proceedings of the Royal Society of Medicine, 58(5), 295.
Léonard, C., Stordeur, S., & Roberfroid, D. (2009). Association between physician density and health care consumption: a systematic review of the evidence. Health Policy, 91(2), 121–134.
López-Pellicer, F. J., Florczyk, A. J., Lacasta, J., Zarazaga-Soria, F. J., & Muro-Medrano, P. R. (2008). Administrative units, an ontological perspective. In I. Song, M. Piattini, Y. Chen, S. Hartmann, F. Grandi, J. Trujillo, et al. (Eds.), Advances in conceptual modeling – challenges and opportunities. ER 2008. Lecture Notes in Computer Science (Vol. 5232, pp. 354–363). Berlin, Heidelberg: Springer.
Mazumdar, S., Butler, D., Bagheri, N., Konings, P., Girosi, F., Feng, X., & McRae, I. (2016). How useful are primary care service areas? Evaluating PCSAs as a tool for measuring primary care practitioner access. Applied Geography, 72, 47–54.
Mazumdar, S., Feng, X., Konings, P., McRae, I., & Girosi, F. (2014a). A brief report on primary care service area catchment geographies in new South Wales Australia. International Journal of Health Geographics, 13, 38.
Mazumdar, S., Konings, P., Butler, D., & McRae, I. S. (2013). General practitioner (family physician) workforce in Australia: comparing geographic data from surveys, a mailing list and medicare. BMC Health Services Research, 13(1).
Mazumdar, S., Konings, P., Hewett, M., Bagheri, N., McRae, I., & Del Fante, P. (2014b). Protecting the privacy of individual general practice patient electronic records for geospatial epidemiology research. Australian and New Zealand Journal of Public Health, 38(6), 548–552.
Mazumdar, S., & McRae, I. (2015). Doctors on the move: National estimates of geographical mobility among general practitioners in Australia. Australian Family Physician, 44(10), 747–751.
Mazumdar, S., Pinzari, L., Bagheri, N., Konings, P., Girosi, F., & Mcrae, I. (2017). A new generation of primary care service areas or general practice catchment areas. Transactions in GIS, Early View, 21, 1379–1390. https://doi.org/10.1111/tgis.12287.
McGrail, M., & Humphreys, J. (2009). Measuring spatial accessibility to primary care in rural areas: Improving the effectiveness of the two-step floating catchment area method. Applied Geography, 29(4), 533–541.
McGrail, M., & Humphreys, J. (2015). Spatial access disparities to primary health care in rural and remote Australia. Geospatial Health, 10(2).
Meadows, G. N., Enticott, J. C., Inder, B., Russell, G. M., & Gurr, R. (2015). Better access to mental health care and the failure of the Medicare principle of universality. The Medical Journal of Australia, 202(4), 190–194.
Medicare Australia Statistics (2016). Divisions of General Practice Statistics Reports. Accessed 30 April 2017.
NHPA (2013). Healthy Communities: Avoidable deaths and life expectancies in 2009–2011. http://www.myhealthycommunities.gov.au/Content/publications/downloads/NHPA_HC_Report_Avoidable_deaths_life_expectancy_December_2013.pdf: National Health Performance Authority.
NHPA (2015). Healthy Communities: Potentially preventable hospitalisations in 2013–14. http://www.myhealthycommunities.gov.au/Content/publications/downloads/NHPA_HC_Report_PPH_December_2015.pdf?t=1497911968207: National Health Performance Authority.
Norman, P., Charles-Edwards, E., & Wilson, T. (2016). Relationships between population change, deprivation change and health change at small area level: Australia 2001–2011. In T. Wilson, E. Charles-Edwards, & M. Bell (Eds.), Demography for planning and policy: Australian case studies (Vol. 7, pp. 197–214). Cham: Springer.
Ong, E. (2012). 2012 Areas of Unmet Health Care Need in rural Oregon report. http://www.ohsu.edu/xd/outreach/oregon-rural-health/data/upload/2012-Unmet-Need-Report.pdf: The Oregon Office of Rural Health, Oregon Health & Science University.
Openshaw, S. (1984). Ecological fallacies and the analysis of areal census data. Environment and Planning A, 16(1), 17–31.
Pink, B. (2009). Health Services: Patient Experiences in Australia. http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/4839.0.55.0012009: Australian Bureau of Statistics.
Ricketts, T. C., & Randolph, R. (2007). Urban-rural flows of physicians. The Journal of Rural Health, 23(4), 277–285.
Starfield, B., Shi, L., & Mackinko, J. (2005). Contribution of primary care to health systems and health. Milbank Quarterly, 83(3), 457–502.
Acknowledgements
This research was initiated at the Australian Primary Health Care Research Institute which was a key component of the Australia government funded Primary Health Care Research, Evaluation and Development (2000-2014) strategy. This research was completed using data collected through the 45 and Up Study (www.saxinstitute.org.au). The 45 and Up Study is managed by the Sax Institute in collaboration with major partner Cancer Council NSW; and partners: the National Heart Foundation of Australia (NSW Division); NSW Ministry of Health; beyondblue; NSW Government Family & Community Services – Carers, Ageing and Disability Inclusion; and the Australian Red Cross Blood Service. We thank the many thousands of people participating in the 45 and Up Study. The linked Medicare Benefits Scheme and Pharmaceutical Benefits Scheme data were supplied to the 45 and Up Study by the Commonwealth Department of Human Services.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mazumdar, S., Bagheri, N., Konings, P. et al. Measuring Relationships between Doctor Densities and Patient Visits: A Dog’s Breakfast of Small Area Health Geographies. Appl. Spatial Analysis 12, 631–645 (2019). https://doi.org/10.1007/s12061-018-9261-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12061-018-9261-y