title: Variation in the use of primary care services for diabetes management according to country of birth and geography among older Australians.
abstract: OBJECTIVE
  To investigate variation according to country of birth and geography in the use of primary care services funded through Medicare Australia-Australian universal health insurance-for diabetes annual cycle of care among older overseas-born Australians with type-2 diabetes.
  
  
  METHODS
  Records of Medicare claims for medical services were linked to self-administered questionnaire data for people with type-2 diabetes enrolled in the 45 and Up Study, including 840 participants born in Italy, Greece, Vietnam, Lebanon, China, India, or the Philippines and 12,444 participants born in Australia, living in 195 statistical local areas (SLAs) in New South Wales, Australia. Study outcomes included ≥6 claims for general practitioner (GP) visits, at least one claim for specialist, optometrist, Practice Incentive Payment for completion of diabetes annual cycle of care (PIP), GP Management Plan or Team Care Arrangement (GPMP/TCA), allied health, blood tests for glycosylated haemoglobin (HbA1c) and cholesterol, and urine test for micro-albumin. Multivariable multilevel logistic regression was performed, controlling for personal socio-demographic and health characteristics and geographical area remoteness and socio-economic status.
  
  
  RESULTS
  Compared with Australia-born participants, people born in Vietnam and China had significantly lower rates of claims for allied health services (odds ratio [OR] 0.14, 95% confidence interval [CI] 0.05-0.43, and OR 0.40, 95%CI 0.18-0.87, respectively), those born in Italy had lower rates of PIP claims (OR 0.60, 95%CI 0.39-0.92) and micro-albuminuria testings (OR 0.65, 95%CI 0.47-0.89), and those born in the Philippines had lower claims for specialist services (OR 0.59, 95%CI 0.38-0.91). Participants born in Greece and China (GP visits), Vietnam (optometrist services), and India (micro-albuminuria tests) were more likely to claims for these services than Australia-born people. Significant geographic variation was observed for all study outcomes, with the greatest variations in claims for allied health services (variation 9.3%, median odds ratio [MOR] 1.74, 95% credible interval [CrI] 1.60-2.01), PIP (7.8%, MOR 1.65, 95%CrI 1.55-1.83), and GPMP/TCA items (6.6%, MOR 1.58, 95%CrI 1.49-1.73).
  
  
  CONCLUSIONS
  Different approach among geographical areas and intervention programs for identified cultural groups and their providers are warranted to improve disparities in diabetes care.
authors.affiliation: Centre for Big Data Research in Health - Faculty of Medicine, UNSW Australia (The University of New South Wales), UNSW Sydney, NSW 2052, Australia. Electronic address: Danielle.Tran@unsw.edu.au.
authors.forename: Duong Thuy
authors.initials: DT
authors.lastname: Tran
authors.affiliation: Centre for Big Data Research in Health - Faculty of Medicine, UNSW Australia (The University of New South Wales), UNSW Sydney, NSW 2052, Australia. Electronic address: L.Jorm@unsw.edu.au.
authors.forename: Louisa R
authors.initials: LR
authors.lastname: Jorm
authors.affiliation: Centre for Big Data Research in Health - Faculty of Medicine, UNSW Australia (The University of New South Wales), UNSW Sydney, NSW 2052, Australia; Centre for Health Research - School of Medicine, University of Western Sydney, Locked Bag 1797, Penrith, NSW 2751, Australia. Electronic address: Alys.Havard@unsw.edu.au.
authors.forename: Alys
authors.initials: A
authors.lastname: Havard
authors.affiliation: Centre for Primary Health Care and Equity, UNSW Australia, UNSW Sydney, NSW 2052, Australia. Electronic address: m.f.harris@unsw.edu.au.
authors.forename: Mark F
authors.initials: MF
authors.lastname: Harris
authors.affiliation: Centre for Primary Health Care and Equity, UNSW Australia, UNSW Sydney, NSW 2052, Australia. Electronic address: e.comino@unsw.edu.au.
authors.forename: Elizabeth Jean
authors.initials: EJ
authors.lastname: Comino
mesh_terms: D000367:Age Factors; D000368:Aged; D000375:Aging / Q000208:ethnology*; D003466:Cultural Characteristics; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis / Q000208:ethnology / Q000523:psychology / Q000628:therapy*; D054242:Emigrants and Immigrants / Q000523:psychology; D005260:Female; D007722:Health Knowledge, Attitudes, Practice / Q000208:ethnology*; D006297:Health Services Accessibility; D054625:Healthcare Disparities / Q000208:ethnology; D006801:Humans; D016015:Logistic Models; D008297:Male; D008499:Medical Records; D008875:Middle Aged; D015999:Multivariate Analysis; D009517:New South Wales / Q000453:epidemiology; D016017:Odds Ratio; D010342:Patient Acceptance of Health Care / Q000208:ethnology* / Q000523:psychology; D011320:Primary Health Care; D044469:Racial Groups / Q000523:psychology; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires
keywords: Administrative claim data; Australia; Diabetes annual cycle of care; Ethnicity; Health service use; Immigrants