Health for all? Patterns and predictors of allied health service use in Australia
Michele Foster A E , Martin O’Flaherty B , Michele Haynes B , Geoffrey Mitchell C and Terrence P. Haines DA School of Social Work and Human Services, The University of Queensland, St Lucia, Qld 4072, Australia.
B Institute of Social Science Research, The University of Queensland, St Lucia, Qld 4072, Australia. Email: m.oflaherty@uq.edu.au, m.haynes@uq.edu.au
C The University of Queensland Ipswich Campus, Salisbury Road, Ipswich, Qld 4305, Australia. Email: g.mitchell@uq.edu.au
D Southern Health Victoria, Monash University, Melbourne, Vic. 3800, Australia. Email: terrence.haines@monash.edu.au
E Corresponding author. Email: m.foster@social.uq.edu.au
Australian Health Review 37(3) 389-396 https://doi.org/10.1071/AH12040
Submitted: 23 July 2012 Accepted: 5 February 2013 Published: 17 May 2013
Abstract
Objective To examine patterns and predictors of allied health service use among the Australian population.
Methods Data from the 2007–08 longitudinal National Health Survey conducted by the Australian Bureau of Statistics in Australia were used to examine differences in use of allied health services among the population. The survey is based on 15 779 adult respondents. Multivariate logistic regression models were used to model the probability of visiting an allied health service contingent on multiple factors of interest.
Results Men, less educated people and people from non-English speaking backgrounds were low users compared with other groups. Interestingly, people with type 2 diabetes were substantially higher users compared with people with other chronic diseases, or no reported chronic disease, and ancillary health insurance had a strong positive effect on use.
Discussion Further investigation of the social and economic circumstances surrounding allied health service use is required to determine areas of under use or unmet need. High use among people with diabetes might indicate the impact of policy incentives to enhance use. Yet, whether all those in need are able to access services is unknown. Further investigation of use among groups with different health needs and by type of financing will enhance policy.
What is known about the topic? Inequities and variations in access to allied health services are commonplace. Effective policy initiatives to improve access, particularly among patients with chronic disease, will depend on improving the knowledge base about patterns of use of allied health services, and what determines use.
What does this paper add? This paper reveals the high and low users of allied health services among the Australian population, those population groups who might be missing out and what might explain these patterns. This information will enable policy makers to target areas of potential unmet need.
What are the implications for practitioners? Multidisciplinary team care is advocated in the management of chronic disease. Practitioners have a vital role in framing the benefits of allied health services to patients and in developing the evidence base about best practice in the management of chronic disease for diverse patient groups.
References
[1] Caughey G, Vitry A, Gilbert A, Roughead E. Revalence of comorbidity of chronic diseases in Australia. BMC Public Health 2008; 8 221| Revalence of comorbidity of chronic diseases in Australia.Crossref | GoogleScholarGoogle Scholar | 18582390PubMed |
[2] Redondo-Sendino A, Guallar-Castillón P, Ramón Banegas J, Rodríguez-Artalejo F. Gender differences in the utilization of health care services among the older adult population of Spain. BMC Public Health 2006; 6 155
| Gender differences in the utilization of health care services among the older adult population of Spain.Crossref | GoogleScholarGoogle Scholar | 16780576PubMed |
[3] Shalev V, Chodick G, Heymann AD, Kokia E. Gender differences in healthcare utilization and medical indicators among patients with diabetes. Public Health 2005; 119 45–9.
| Gender differences in healthcare utilization and medical indicators among patients with diabetes.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD2crovVyhtQ%3D%3D&md5=e5d92a44e7ae0db5c2b6bfff4dfdf38eCAS | 15560901PubMed |
[4] Chaix B, Boëlle P-Y, Guilbert P, Chauvin P. 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 | 1:STN:280:DC%2BD2M%2FmslCrsg%3D%3D&md5=3ad18fb366deeedbaa061dd132cbad4eCAS | 15694956PubMed |
[5] Wilson C, Alam R, Latif S, Knighting K, Williamson S, Beaver K. Patient access to healthcare services and optimization of self-management for ethnic minority populations living with diabetes: a systematic review. Health Soc Care Community 2012; 20 1–19.
| Patient access to healthcare services and optimization of self-management for ethnic minority populations living with diabetes: a systematic review.Crossref | GoogleScholarGoogle Scholar | 21749529PubMed |
[6] Andersen R, Newman J. Societal and individual determinants of medical care utilization in the United States. Milbank Mem Fund Q Health Soc 1973; 51 95–124.
| Societal and individual determinants of medical care utilization in the United States.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaE3s3jtlOnsA%3D%3D&md5=8194850990e6ac2383793497c9ddbeefCAS | 4198894PubMed |
[7] Meer J, Rosen H. Insurance and the utilization of medical services. Soc Sci Med 2004; 58 1623–32.
| Insurance and the utilization of medical services.Crossref | GoogleScholarGoogle Scholar | 14990364PubMed |
[8] Van Doorslaer Clarke E, Savage E, Hall J. Horizontal inequities in Australia’s mixed public/private health care system. Health Policy 2008; 86 97–108.
| Horizontal inequities in Australia’s mixed public/private health care system.Crossref | GoogleScholarGoogle Scholar |
[9] Wong IO, Chan WS, Choi S, Lo SV, Leung GM. Moral hazard or realised access to care? Empirical observations in Hong Kong. Health Policy 2006; 75 251–61.
| Moral hazard or realised access to care? Empirical observations in Hong Kong.Crossref | GoogleScholarGoogle Scholar | 16399169PubMed |
[10] Turnbull C, Grimmer-Somers K, Kumar S, May E, Law D, Ashworth E. Allied, scientific and complementary health professionals: a new model for Australian allied health. Aust Health Rev 2009; 33 27–37.
| Allied, scientific and complementary health professionals: a new model for Australian allied health.Crossref | GoogleScholarGoogle Scholar | 19203331PubMed |
[11] Ackermann EW, Mitchell GK. An audit of structured diabetes care in rural general practice. Med J Aust 2006; 185 69–72.
| 16842058PubMed |
[12] Wagner EH, Austin BT, Davis C, Hindmarsh M, Schaefer J, Bonomi A. Improving chronic illness care: translating evidence into action. Health Aff (Millwood) 2001; 20 64–78.
| Improving chronic illness care: translating evidence into action.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD38%2FovVagug%3D%3D&md5=7e7614884d7974990880bdb4bbee59a6CAS |
[13] World Health Organization. 2008–2013 Action Plan for the Global Strategy for the Prevention and Control of Noncommunicable Diseases. Geneva: WHO Press, World Health Organization; 2008.
[14] Cant RP, Foster MM. Investing in big ideas: utilization and cost of Medicare allied health services in Australia under the Chronic Disease Management initiative. Aust Health Rev 2011; 35 468–74.
| 22126951PubMed |
[15] Foster MM, Mitchell G, Haines T, Tweedy S, Cornwell P, Fleming J. Does Enhanced Primary Care enhance primary care? Policy-induced dilemmas for allied health professionals. Med J Aust 2008; 188 29–32.
| 18205560PubMed |
[16] Menz HB. Utilisation of podiatry services in Australia under the Medicare Enhanced Primary Care program, 2004–2008. J Foot Ankle Res 2009; 2 30
| Utilisation of podiatry services in Australia under the Medicare Enhanced Primary Care program, 2004–2008.Crossref | GoogleScholarGoogle Scholar | 19878562PubMed |
[17] Marinko LN, Chacko JM, Dalton D, Chacko CC. The effectiveness of therapeutic exercise for painful shoulder conditions: a meta-analysis. J Shoulder Elbow Surg 2011; 20 1351–9.
| The effectiveness of therapeutic exercise for painful shoulder conditions: a meta-analysis.Crossref | GoogleScholarGoogle Scholar | 21889366PubMed |
[18] De Jaegher K, Jegers M. A model of physician behaviour with demand inducement. J Health Econ 2000; 19 231–58.
| A model of physician behaviour with demand inducement.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3M%2FgsVGlsA%3D%3D&md5=e8a7997dc8b1cc517618b33a2a9e01e8CAS | 10947578PubMed |
[19] Roos LL. Issues in studying ancillary services. Soc Sci Med 1982; 16 1583–90.
| Issues in studying ancillary services.Crossref | GoogleScholarGoogle Scholar | 6813974PubMed |
[20] Groenendijk JJ, Swinkels IC, de Bakker D, Dekker J, van den Ende CH. Physical therapy management of low back pain has changed. Health Policy 2007; 80 492–9.
| Physical therapy management of low back pain has changed.Crossref | GoogleScholarGoogle Scholar | 16787681PubMed |
[21] Schokkaert E, van Ourti T, De Grave D, Lecluyse A, Van De Voorde C. Supplemental health insurance in Belgium. Health Econ 2010; 19 377–95.
| Supplemental health insurance in Belgium.Crossref | GoogleScholarGoogle Scholar | 19353529PubMed |
[22] Haines TP, Foster MM, Cornwell P, Fleming J, Tweedy S, Hart A. Mitchell G. Impact of enhanced primary care on equitable access to and economic efficiency of allied health services: a qualitative investigation. Aust Health Rev 2010; 34 30–5.
| Impact of enhanced primary care on equitable access to and economic efficiency of allied health services: a qualitative investigation.Crossref | GoogleScholarGoogle Scholar | 20334753PubMed |
[23] Colombo F, Tapay N. Private health insurance in Australia: a case study. OECD Health Working Papers, No. 8. Paris: OECD Publishing; 2003.
[24] Australian Bureau of Statistics. National Health Survey (NHS) 2007/08. Canberra: Australian Bureau of Statistics. 2009.
[25] Schoen C, Davis K, DesRoches C, Donelan K, Blendon R. Health insurance markets and income inequality: findings from an international health policy survey. Health Policy 2000; 51 67–85.
| Health insurance markets and income inequality: findings from an international health policy survey.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3M%2Fgs1agtA%3D%3D&md5=0be72d04e8f3b1265c8710cd92459adfCAS | 10699676PubMed |
[26] Scott IA. Is modern medicine at risk of losing the plot? Med J Aust 2006; 185 213–16.
| 16922667PubMed |
[27] Parslow R, Jorm A, Christensen H, Jacomb P, Rodgers B. Gender differences in factors affecting use of health services: an analysis of a community study of middle-aged and older Australians. Soc Sci Med 2004; 59 2121–9.
| Gender differences in factors affecting use of health services: an analysis of a community study of middle-aged and older Australians.Crossref | GoogleScholarGoogle Scholar | 15351477PubMed |
[28] Studdert DM, Britt HC, Pan Y, Fahridin S, Bayram CF, Gurrin LC. Are rates of pathology test ordering higher in general practices co-located with pathology collection centres? Med J Aust 2010; 193 114–9.
| 20642420PubMed |
[29] Bywood P, Katteri R, Lunnay R. Disparities in primary health care utilisation: Who are the disadvantaged groups? How are they disadvantaged? What interventions work? PHCRIS Policy Issue Review. Adelaide: Primary Health Care Research and Information Service; 2001.