Socioeconomic disparities in the management of coronary heart disease in 438 general practices in Australia

被引:17
作者
Mnatzaganian, George [1 ]
Lee, Crystal Man Ying [2 ,3 ]
Robinson, Suzanne [4 ]
Sitas, Freddy [5 ,6 ]
Chow, Clara K. [7 ,8 ,9 ]
Woodward, Mark [9 ,10 ]
Huxley, Rachel R. [9 ,11 ]
机构
[1] La Trobe Univ, La Trobe Rural Hlth Sch, HS1 2-39,POB 199, Bendigo, Vic 3552, Australia
[2] La Trobe Univ, Sch Psychol & Publ Hlth, Bendigo, Vic, Australia
[3] Univ Sydney, Boden Collaborat Obes Nutr Exercise & Eating Dis, Sydney, NSW, Australia
[4] Curtin Univ, Sch Publ Hlth, Perth, WA, Australia
[5] Univ New South Wales, Ctr Primary Hlth Care & Equ, Sch Publ Hlth & Community Med, Sydney, NSW, Australia
[6] Univ Sydney, Menzies Ctr Hlth Policy, Sch Publ Hlth, Sydney, NSW, Australia
[7] Univ Sydney, Westmead Appl Res Ctr, Sydney, NSW, Australia
[8] Westmead Hosp, Dept Cardiol, Sydney, NSW, Australia
[9] Univ New South Wales, George Inst Global Hlth, Sydney, NSW, Australia
[10] Univ Oxford, George Inst Global Hlth, Oxford, England
[11] Deakin Univ, Fac Hlth, Geelong, Vic, Australia
关键词
Coronary heart disease; health targets; management; socioeconomic gradients;
D O I
10.1177/2047487320912087
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background This population-based cross-sectional and panel study investigated disparities in the management of coronary heart disease (CHD) by level of socioeconomic status. Methods CHD patients (aged >= 18 years), treated in 438 general practices in Australia, with >= 3 recent encounters with their general practitioners, with last encounter being during 2016-2018, were included. Secondary prevention prescriptions and number of treatment targets achieved were each modelled using a Poisson regression adjusting for demographics, socioeconomic indicators, remoteness of patient's residence, comorbidities, lifetime follow-up, number of patient-general practitioner encounters and cluster effect within the general practices. The latter model was constructed using the Generalised Estimating Equations approach. Sensitivity analysis was run by comorbidity. Results Of 137,408 patients (47% women), approximately 48% were prescribed >= 3 secondary prevention medications. However, only 44% were screened for CHD-associated risk factors. Of the latter, 45% achieved >= 5 treatment targets. Compared with patients from the highest socioeconomic status fifth, those from the lowest socioeconomic status fifth were 8% more likely to be prescribed more medications for secondary prevention (incidence rate ratio (95% confidence interval): 1.08 (1.04-1.12)) but 4% less likely to achieve treatment targets (incidence rate ratio: 0.96 (0.95-0.98)). These disparities were also observed when stratified by comorbidities. Conclusion Despite being more likely to be prescribed medications for secondary prevention, those who are most socioeconomically disadvantaged are less likely to achieve treatment targets. It remains to be determined whether barriers such as low adherence to treatment, failure to fill prescriptions, low income, low level of education or other barriers may explain these findings.
引用
收藏
页码:400 / 407
页数:8
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