Factors associated with the health care cost in older Australian women with arthritis: an application of the Andersen's Behavioural Model of Health Services Use

• Published in: Public health (London) Vol. 134; pp. 64 - 71
• Main Authors: Lo, T.K.T, Parkinson, L, Cunich, M, Byles, J
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01-05-2016
• Subjects: Aged; Aged, 80 and over; Andersen's Behavioural Model; Arthritis; Arthritis - economics; Arthritis - epidemiology; Arthritis - physiopathology; Arthritis - therapy; Australia; Australia - epidemiology; Cohort study; Comorbidity; Complementary Therapies - utilization; Economic burden; Female; Health care costs; Health Care Costs - statistics & numerical data; Humans; Infectious Disease; Insurance Coverage - statistics & numerical data; Insurance, Health - statistics & numerical data; Internal Medicine; Longitudinal Studies; Models, Psychological; Patient Acceptance of Health Care - psychology; Patient Acceptance of Health Care - statistics & numerical data; Regression Analysis; Residence Characteristics - statistics & numerical data; Socioeconomic Factors; Australia; Health care costs; Andersen's Behavioural Model; Arthritis; Economic burden; Australia; Cohort study
• ISSN: 0033-3506; 1476-5616
• DOI: 10.1016/j.puhe.2015.11.018

Abstract Objective Factors associated with the utilisation of health care have not been rigorously examined in people with arthritis. The objective of this study was to examine the determinants of health care utilisation and costs in older women with arthritis using the Andersen's behavioural model as a framework. Study design Longitudinal cohort study. Methods Participants of Surveys 3 to 5 of the Australian Longitudinal Study on Women's Health who reported arthritis were included in the study. Information about health care utilisation and unit prices were based on linked Medicare Australia data, which included prescription medicines and health services. Total health care costs of participants with arthritis were measured for the years 2002 to 2003, 2005 to 2006, and 2008 to 2009, which corresponded to the survey years. Potential explanatory variables of the health care cost and other characteristics of the participants were collected from the health surveys. Explanatory variables were grouped into predisposing characteristics, enabling factors and need variables conforming to the Andersen's Behavioural Model of Health Services Use. Longitudinal data analysis was conducted using generalized estimating equations. Results A total of 5834 observations were included for the three periods. Regression analysis results show that higher health care cost in older Australian women with arthritis was significantly associated with residing in an urban area, having supplementary health insurance coverage, more comorbid conditions, using complementary and alternative medicine, and worse physical functioning. It was also found that predisposing characteristics (such as the area of residence) and enabling factors (such as health insurance coverage) accounted for more variance in the health care cost than need variables (such as comorbid conditions). Conclusion These results may indicate an inefficient and unfair allocation of subsidised health care among older Australian women with arthritis, where individuals with less enabling resources and more socio-economic disadvantages have a lower level of health care utilisation. Future research may focus on evaluating the effectiveness of policies designed to reduce excessive out-of-pocket costs and to improve equity in health care access in the older population.