Applied Health Economics and Health Policy

, Volume 15, Issue 5, pp 625–634 | Cite as

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

  • Ian McRaeEmail author
  • Kees van Gool
  • Jane Hall
  • Laurann Yen
Original Research Article



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.



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 Contributions

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.

Compliance with Ethical Standards


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.

Supplementary material

40258_2017_336_MOESM1_ESM.docx (52 kb)
Supplementary material 1 (DOCX 51 kb)


  1. 1.
    Menzies Centre for Health Policy. 2008 Menzies Nous Australian Health Survey, Report 2 Financial Stress and Health. 2008.Google Scholar
  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.CrossRefPubMedGoogle Scholar
  3. 3.
    Australian Bureau of Statistics. Health experience survey 2015–2916. Canberra (ACT): Australian Bureau of Statistics; 2016.Google Scholar
  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.PubMedPubMedCentralGoogle 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.CrossRefPubMedGoogle 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.CrossRefPubMedGoogle 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.CrossRefPubMedPubMedCentralGoogle 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.CrossRefPubMedPubMedCentralGoogle 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.CrossRefPubMedGoogle 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.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Department of Social Services. Demographic, December 2015.Google Scholar
  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.CrossRefPubMedGoogle 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.CrossRefGoogle 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.CrossRefPubMedPubMedCentralGoogle 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.Google Scholar
  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.CrossRefPubMedPubMedCentralGoogle 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.CrossRefPubMedGoogle 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.CrossRefPubMedGoogle 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.CrossRefPubMedPubMedCentralGoogle 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.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Centre for Research on Ageing, Health and Wellbeing, Research School of Population HealthThe Australian National UniversityActonAustralia
  2. 2.Centre for Health Economics Research and EvaluationUniversity of Technology SydneySydneyAustralia
  3. 3.Department of Health Services Research and Policy, Research School of Population HealthThe Australian National UniversityActonAustralia

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