Register      Login
Australian Health Review Australian Health Review Society
Journal of the Australian Healthcare & Hospitals Association
RESEARCH ARTICLE (Open Access)

The link between out-of-pocket costs and inequality in specialist care in Australia

Mohammad Habibullah Pulok https://orcid.org/0000-0002-9168-5732 A B § * , Kees van Gool A and Jane Hall A
+ Author Affiliations
- Author Affiliations

A Centre for Health Economics Research and Evaluation (CHERE), University of Technology Sydney (UTS), Australia, PO Box 123 Broadway, NSW 2007, Australia.

B Department of Medicine, Geriatric Medicine Research, Dalhousie University, 1314, Camp Hill Veteran’s Memorial Building, 5955 Veteran’s Memorial Lane, Halifax, NS B3H 2E1, Canada.

* Correspondence to: mohammad.pulok@barcelonagse.eu

Australian Health Review 46(6) 652-659 https://doi.org/10.1071/AH22126
Submitted: 20 May 2022  Accepted: 6 September 2022   Published: 30 September 2022

© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of AHHA. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Objective Out-of-pocket (OOP) costs could act as a potential barrier to accessing specialist services, particularly among low-income patients. The aim of this study is to examine the link between OOP costs and socioeconomic inequality in specialist services in Australia.

Methods This study is based on population-level data from the Medicare Benefits Schedule of Australia in 2014–15. Three outcomes of specialist care were used: all visits, visits without OOP costs (bulk-billed services), and visits with OOP costs. Logistic and zero-inflated negative binomial regression models were used to examine the association between outcome variables and area-level socioeconomic status after controlling for age, sex, state of residence, and geographic remoteness. The concentration index was used to quantify the extent of inequality.

Results Our results indicate that the distribution of specialist visits favoured the people living in wealthier areas of Australia. There was a pro-rich inequality in specialist visits associated with OOP costs. However, the distribution of the visits incurring zero OOP cost was slightly favourable to the people living in lower socioeconomic areas. The pro-poor distribution of visits with zero OOP cost was insufficient to offset the pro-rich distribution among the visits with OOP costs.

Conclusions OOP costs for specialist care might partly undermine the equity principle of Medicare in Australia. This presents a challenge to the government on how best to influence the rate and distribution of specialists’ services.

Keywords: Australia, bulk-billing, concentration index, inequality, out-of-pocket cost, policy, socioeconomic status, specialist visit.


References

[1]  Wagstaff A, van Doorslaer E. Equity in health care finance and delivery. In: Culyer AJ, Newhouse JP, editors. Handbook of health economics. Amsterdam: Elsevier (North-Holland); 2000, pp. 1803–1862.

[2]  Pulok MH, Hajizadeh M. Equity in the use of physician services in Canada’s universal health system: a longitudinal analysis of older adults. Soc Sci Med 2022; 307 115186
Equity in the use of physician services in Canada’s universal health system: a longitudinal analysis of older adults.Crossref | GoogleScholarGoogle Scholar |

[3]  O’Donnell O, van Doorslaer E, Wagstaff A, et al. Analyzing health equity using household survey data: A guide to techniques and their implementation. The World Bank; 2008.
| Crossref |

[4]  Devaux M. Income-related inequalities and inequities in health care services utilisation in 18 selected OECD countries. Eur J Health Econ 2015; 16 21–33.
Income-related inequalities and inequities in health care services utilisation in 18 selected OECD countries.Crossref | GoogleScholarGoogle Scholar |

[5]  Allin S, Hurley J. Inequity in publicly funded physician care: what is the role of private prescription drug insurance? Health Econ 2009; 18 1218–1232.
Inequity in publicly funded physician care: what is the role of private prescription drug insurance?Crossref | GoogleScholarGoogle Scholar |

[6]  Morris S, Sutton M, Gravelle H. Inequity and inequality in the use of health care in England: an empirical investigation. Soc Sci Med 2005; 60 1251–1266.
Inequity and inequality in the use of health care in England: an empirical investigation.Crossref | GoogleScholarGoogle Scholar |

[7]  Sözmen K, Ünal B. Explaining inequalities in health care utilization among Turkish adults: findings from Health Survey 2008. Health Policy 2016; 120 100–110.
Explaining inequalities in health care utilization among Turkish adults: findings from Health Survey 2008.Crossref | GoogleScholarGoogle Scholar |

[8]  van Doorslaer E, Koolman X, Jones AM. Explaining income-related inequalities in doctor utilisation in Europe. Health Econ 2004; 13 629–647.
Explaining income-related inequalities in doctor utilisation in Europe.Crossref | GoogleScholarGoogle Scholar |

[9]  Kiil A, Houlberg K. How does copayment for health care services affect demand, health and redistribution? A systematic review of the empirical evidence from 1990 to 2011. Eur J Health Econ 2014; 15 813–828.
How does copayment for health care services affect demand, health and redistribution? A systematic review of the empirical evidence from 1990 to 2011.Crossref | GoogleScholarGoogle Scholar |

[10]  Pulok MH, van Gool K, Hall J. Inequity in physician visits: the case of the unregulated fee market in Australia. Soc Sci Med 2020; 255 113004
Inequity in physician visits: the case of the unregulated fee market in Australia.Crossref | GoogleScholarGoogle Scholar |

[11]  Pulok MH, van Gool K, Hall J. Horizontal inequity in the utilisation of healthcare services in Australia. Health Policy 2020; 124 1263–1271.
Horizontal inequity in the utilisation of healthcare services in Australia.Crossref | GoogleScholarGoogle Scholar |

[12]  Johar M, Mu C, van Gool K, et al. Bleeding hearts, profiteers, or both: specialist physician fees in an unregulated market. Health Econ 2017; 26 528–535.
Bleeding hearts, profiteers, or both: specialist physician fees in an unregulated market.Crossref | GoogleScholarGoogle Scholar |

[13]  Department of Health. Annual Medicare Statistics 2019. Available at https://www1.health.gov.au/internet/main/publishing.nsf/Content/Medicare%20Statistics-1[Accessed 26 January 2022]

[14]  Australian Institute of Health and Welfare. Patients’ out-of-pocket spending on Medicare services, 2016–17. Cat. no. HPF 35. Canberra: AIHW; 2018. Available at https://www.aihw.gov.au/reports/health-welfare-expenditure/patient-out-pocket-spending-medicare-2016-17/contents/summary

[15]  Dalziel KM, Huang L, Hiscock H, et al. Born equal? The distribution of government Medicare spending for children. Soc Sci Med 2018; 208 50–54.
Born equal? The distribution of government Medicare spending for children.Crossref | GoogleScholarGoogle Scholar |

[16]  Hua X, Erreygers G, Chalmers J, et al. Using administrative data to look at changes in the level and distribution of out-of-pocket medical expenditure: an example using Medicare data from Australia. Health Policy 2017; 121 426–433.
Using administrative data to look at changes in the level and distribution of out-of-pocket medical expenditure: an example using Medicare data from Australia.Crossref | GoogleScholarGoogle Scholar |

[17]  Meadows GN, Enticott JC, Inder B, et al. Better access to mental health care and the failure of the Medicare principle of universality. Med J Aust 2015; 202 190–194.
Better access to mental health care and the failure of the Medicare principle of universality.Crossref | GoogleScholarGoogle Scholar |

[18]  Department of Health and Aged Care. Statistics under Medicare. Department of Health and Aged Care; 2022. Available at https://www1.health.gov.au/internet/main/publishing.nsf/Content/Medicare%20Statistics-1 [Accessed 14 July 2022].

[19]  Australian Bureau of Statistics. 2013 Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2011. ABS; 2013. Available at https://www.abs.gov.au/ausstats/abs@.nsf/DetailsPage/2033.0.55.0012011

[20]  Strobel NA, Peter S, McAuley KE, et al. Effect of socioeconomic disadvantage, remoteness and Indigenous status on hospital usage for Western Australian preterm infants under 12 months of age: a population-based data linkage study. BMJ Open 2017; 7 e013492
Effect of socioeconomic disadvantage, remoteness and Indigenous status on hospital usage for Western Australian preterm infants under 12 months of age: a population-based data linkage study.Crossref | GoogleScholarGoogle Scholar |

[21]  Jones AM. Applied econometrics for health economists: a practical guide, 2nd edn. Oxford: Radcliffe Medical Publishing; 2007.

[22]  Pulok MH, van Gool K, Hajizadeh M, et al. Measuring horizontal inequity in healthcare utilisation: a review of methodological developments and debates. Eur J Health Econ 2020; 21 171–180.
Measuring horizontal inequity in healthcare utilisation: a review of methodological developments and debates.Crossref | GoogleScholarGoogle Scholar |

[23]  Korda RJ, Joshy G, Jorm LR, et al. Inequalities in bariatric surgery in Australia: findings from 49 364 obese participants in a prospective cohort study. Med J Aust 2012; 197 631–636.
Inequalities in bariatric surgery in Australia: findings from 49 364 obese participants in a prospective cohort study.Crossref | GoogleScholarGoogle Scholar |

[24]  McGrail KM. Income-related inequities: cross-sectional analyses of the use of medicare services in British Columbia in 1992 and 2002. Open Med 2008; 2 e91–e98.

[25]  Chaix B, Boëlle P-Y, Guilbert P, et al. Area-level determinants of specialty care utilization in France: a multilevel analysis. Public Health 2005; 119 97–104.
Area-level determinants of specialty care utilization in France: a multilevel analysis.Crossref | GoogleScholarGoogle Scholar |

[26]  Or Z, Jusot F, Yilmaz E. Impact of health care system on socioeconomic inequalities in doctor use. Vol. 17. Paris: IRDES Institut for Research and Information in Health Economics; 2008.

[27]  Carpenter A, Islam MM, Yen L, et al. Affordability of out-of-pocket health care expenses among older Australians. Health Policy 2015; 119 907–914.
Affordability of out-of-pocket health care expenses among older Australians.Crossref | GoogleScholarGoogle Scholar |

[28]  Freed GL, Allen AR. Variation in outpatient consultant physician fees in Australia by specialty and state and territory. Med J Aust 2017; 206 176–180.
Variation in outpatient consultant physician fees in Australia by specialty and state and territory.Crossref | GoogleScholarGoogle Scholar |

[29]  Turrell G, Oldenburg BF, Harris E, et al. Social inequality: utilisation of general practitioner services by socio-economic disadvantage and geographic remoteness. Aust N Z J Public Health 2008; 28 152–158.
Social inequality: utilisation of general practitioner services by socio-economic disadvantage and geographic remoteness.Crossref | GoogleScholarGoogle Scholar |

[30]  Day SE, Alford K, Dunt D, et al. Strengthening Medicare: will increasing the bulk-billing rate and supply of general practitioners increase access to Medicare-funded general practitioner services and does rurality matter? Aust N Z Health Policy 2005; 2 18
Strengthening Medicare: will increasing the bulk-billing rate and supply of general practitioners increase access to Medicare-funded general practitioner services and does rurality matter?Crossref | GoogleScholarGoogle Scholar |

[31]  Wong CY, Greene J, Dolja-Gore X, et al. The rise and fall in out-of-pocket costs in Australia: an analysis of the strengthening Medicare reforms. Health Econ 2017; 26 962–979.
The rise and fall in out-of-pocket costs in Australia: an analysis of the strengthening Medicare reforms.Crossref | GoogleScholarGoogle Scholar |

[32]  Cookson R, Laudicella M, Donni PL. Measuring change in health care equity using small-area administrative data – evidence from the English NHS 2001–2008. Soc Sci Med 2012; 75 1514–1522.
Measuring change in health care equity using small-area administrative data – evidence from the English NHS 2001–2008.Crossref | GoogleScholarGoogle Scholar |