Role of Cost on Failure to Access Prescribed Pharmaceuticals: The Case of Statins

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In Australia, as in many other Western countries, patient surveys suggest the costs of medicines lead to deferring or avoiding filling of prescriptions. The Australian Pharmaceutical Benefits Scheme provides approved prescription medicines at subsidised prices with relatively low patient co-payments. The Pharmaceutical Benefits Scheme defines patient co-payment levels per script depending on whether patients are “concessional” (holding prescribed pension or other government concession cards) or “general”, and whether they have reached a safety net defined by total out-of-pocket costs for Pharmaceutical Benefits Scheme-approved medicines.


The purpose of this study was to explore the impact of costs on adherence to statins in this relatively low-cost environment.


Using data from a large-scale survey of older Australians in the state of New South Wales linked to administrative data from the national medical and pharmaceutical insurance schemes, we explore the relationships between adherence to medication regimes for statins and out-of-pocket costs of prescribed pharmaceuticals, income, other health costs, and a wide set of demographic and socio-economic control variables using both descriptive analysis and logistic regressions.


Within the general non-safety net group, which has the highest co-payment, those with lowest income have the lowest adherence, suggesting that the general safety threshold may be set at a level that forms a major barrier to statin adherence. This is reinforced by over 75% of those who were not adherent before reaching the safety net threshold becoming adherent after reaching the safety net with its lower co-payments.


The main financial determinant of adherence is the concessional/general and safety net category of the patient, which means the main determinant is the level of co-payment.

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  1. 1.

    Menzies Centre for Health Policy. 2008 Menzies Nous Australian Health Survey, Report 2 Financial Stress and Health. 2008.

  2. 2.

    Schoen C, Osborn R, Squires D, Doty MM, Pierson R, Applebaum S. How health insurance design affects access to care and costs, by income, in eleven countries. Health Aff (Millwood). 2010;29(12):2323–34. doi:10.1377/hlthaff.2010.0862.

    Article  PubMed  Google Scholar 

  3. 3.

    Australian Bureau of Statistics. Health experience survey 2015–2916. Canberra (ACT): Australian Bureau of Statistics; 2016.

  4. 4.

    Eaddy MT, Cook CL, O’Day K, Burch SP, Cantrell CR. How patient cost-sharing trends affect adherence and outcomes: a literature review. P T. 2012;37(1):45–55.

    PubMed  PubMed Central  Google Scholar 

  5. 5.

    Hynd A, Roughead EE, Preen DB, Glover J, Bulsara M, Semmens J. The impact of co-payment increases on dispensings of government-subsidised medicines in Australia. Pharmacoepidemiol Drug Saf. 2008;17(11):1091–9. doi:10.1002/pds.1670.

    Article  PubMed  Google Scholar 

  6. 6.

    Schafheutle EI, Hassell K, Noyce PR, Weiss MC. Access to medicines: cost as an influence on the views and behaviour of patients. Health Soc Care Community. 2002;10(3):187–95.

    Article  PubMed  Google Scholar 

  7. 7.

    Briesacher BA, Gurwitz JH, Soumerai SB. Patients at-risk for cost-related medication nonadherence: a review of the literature. J Gen Intern Med. 2007;22(6):864–71. doi:10.1007/s11606-007-0180-x.

    Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Laba TL, Brien JA, Jan S. Understanding rational non-adherence to medications: a discrete choice experiment in a community sample in Australia. BMC Fam Pract. 2012;13:61. doi:10.1186/1471-2296-13-61.

    Article  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Warren JR, Falster MO, Fox D, Jorm L. Factors influencing adherence in long-term use of statins. Pharmacoepidemiol Drug Saf. 2013;22(12):1298–307. doi:10.1002/pds.3526.

    CAS  Article  PubMed  Google Scholar 

  10. 10.

    Warren JR, Falster MO, Tran B, Jorm L. Association of continuity of primary care and statin adherence. PLoS One. 2015;10(10):e0140008. doi:10.1371/journal.pone.0140008.

    Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Department of Social Services. Demographic, December 2015.

  12. 12.

    Banks E, Redman S, Jorm L, Armstrong B, Bauman A, Beard J, et al. Cohort profile: the 45 and up study. Int J Epidemiol. 2008;37(5):941–7. doi:10.1093/ije/dym184.

    Article  PubMed  Google Scholar 

  13. 13.

    Johar M, Savage E. Healthcare expenditure profile of older Australians: evidence from linked survey and health administrative data. Econ Pap. 2012;31(4):451–63.

    Article  Google Scholar 

  14. 14.

    Mealing NM, Banks E, Jorm LR, Steel DG, Clements MS, Rogers KD. Investigation of relative risk estimates from studies of the same population with contrasting response rates and designs. BMC Med Res Methodol. 2010;10:26. doi:10.1186/1471-2288-10-26.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    LuizaVL, Chaves LA, SilvaRM, Emmerick ICM, ChavesGC, Fonseca deAraújo SC et al. Pharmaceutical policies: effects of cap and co-payment on rational use of medicines. 2015 Contract No.: Art. No.: CD007017.

  16. 16.

    Dawda P, McRae IS, Yen L, Islam MM, Bagheri N, Jowsey T, et al. Does it matter who organises your health care? Int J Integr Care. 2015;15:e022.

    Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Andrews G, Slade T. Interpreting scores on the Kessler Psychological Distress Scale (K10). Aust N Z J Public Health. 2001;25(6):494–7.

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Chowdhury R, Khan H, Heydon E, Shroufi A, Fahimi S, Moore C, et al. Adherence to cardiovascular therapy: a meta-analysis of prevalence and clinical consequences. Eur Heart J. 2013;34(38):2940–8. doi:10.1093/eurheartj/eht295.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Shrank WH, Patrick AR, Alan Brookhart M. Healthy user and related biases in observational studies of preventive interventions: a primer for physicians. J Gen Intern Med. 2011;26(5):546–50. doi:10.1007/s11606-010-1609-1.

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Whiteford P. Tales of Robin Hood (part 1): welfare myths and realities in the United Kingdom and Australia Australian Review of Public Affairs. Digest, September 2015.

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This research was completed using data collected through the 45 and Up Study ( The 45 and Up Study is managed by the Sax Institute in collaboration with its major partner, Cancer Council New South Wales; and partners: the National Heart Foundation of Australia (New South Wales Division); New South Wales Ministry of Health; New South Wales Government Family and Community Services—Carers, Ageing and Disability Inclusion; and the Australian Red Cross Blood Service. 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. We thank the many thousands of people participating in the 45 and Up Study.

Author information




IM developed the initial design of the project based on an idea of LY. JH and KG assisted in finalising the design. IM undertook the analysis and the initial drafting. All authors contributed to the editing, redrafting and finalising of the paper.

Corresponding author

Correspondence to Ian McRae.

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The research was funded by the Research in the Finance and Economics of Primary Health Care Centre of Research Excellence (ReFinE-PHC) under the Australian Primary Health Care Research Institute’s Centres of Research Excellence funding scheme, which is supported by a grant from the Australian Government Department of Health. The article does not necessarily reflect the views of the Australian Primary Health Care Research Institute or the Australian Government.

Conflict of interest

Ian McRae, Kees van Gool, Jane Hall and Laurann Yen have no conflicts of interest directly relevant to the contents of this article.

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McRae, I., van Gool, K., Hall, J. et al. Role of Cost on Failure to Access Prescribed Pharmaceuticals: The Case of Statins. Appl Health Econ Health Policy 15, 625–634 (2017).

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