title: Explaining health care expenditure variation: large-sample evidence using linked survey and health administrative data.
abstract: Explaining individual, regional, and provider variation in health care spending is of enormous value to policymakers but is often hampered by the lack of individual level detail in universal public health systems because budgeted spending is often not attributable to specific individuals. Even rarer is self-reported survey information that helps explain this variation in large samples. In this paper, we link a cross-sectional survey of 267 188 Australians age 45 and over to a panel dataset of annual healthcare costs calculated from several years of hospital, medical and pharmaceutical records. We use this data to distinguish between cost variations due to health shocks and those that are intrinsic (fixed) to an individual over three years. We find that high fixed expenditures are positively associated with age, especially older males, poor health, obesity, smoking, cancer, stroke and heart conditions. Being foreign born, speaking a foreign language at home and low income are more strongly associated with higher time-varying expenditures, suggesting greater exposure to adverse health shocks.
authors.affiliation: Department of Economics, Boston University, Boston, MA, USA.
authors.forename: Randall P
authors.initials: RP
authors.lastname: Ellis
authors.forename: Denzil G
authors.initials: DG
authors.lastname: Fiebig
authors.forename: Meliyanni
authors.initials: M
authors.lastname: Johar
authors.forename: Glenn
authors.initials: G
authors.lastname: Jones
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Savage
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D003695:Delivery of Health Care / Q000191:economics / Q000458:organization & administration* / Q000706:statistics & numerical data; D011307:Drug Prescriptions / Q000706:statistics & numerical data; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006304:Health Status; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D007348:Insurance, Health / Q000706:statistics & numerical data; D008297:Male; D008498:Medical Record Linkage; D008875:Middle Aged; D008962:Models, Theoretical; D009517:New South Wales / Q000453:epidemiology; D012737:Sex Factors
keywords: health expenditure; health insurance; panel data; risk adjustment