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Epidemiology and policy
P1-160 Healthcare expenditure in the last years of life for out-of-hospital medicare benefits schedule funded services in Western Australia: a population-based data linkage study
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  1. R Moorin1,2,
  2. D Gibson1,
  3. D' A Holman1
  1. 1Curtin University, Perth, Western Australia, Australia
  2. 2University of Western Australia, Perth, Western Australia, Australia

Abstract

Introduction Persistent debate over the relationship between time-to-death, age and healthcare expenditure may be the result of overgeneralised modelling. Single-population total health service utilisation models may not take into account differing patterns of use between out-of-hospital services. We explored the relationship between time-to-death, age and healthcare expenditure for government funded out-of-hospital services in last years of life to determine effects of service type and the stability of this relationship over time.

Methods Records of all deaths in Western Australia from 1990 to 2004 extracted from the mortality register and linked to records from the Medicare Benefit Scheme. Claims 5 years prior to death were identified from all Medicare Benefit Scheme claims originating in Western Australia between 1984 and 2004. Out-of-hospital costs were assigned to all services within 5 years of death from five major causes using Medicare Benefit Scheme costing information.

Results Out-of-hospital healthcare expenditure increased for primary care services during last 2 months of life. A similar trend was observed in specialist services and diagnostic and therapeutic services, however an earlier increase in expenditure occurred during the penultimate year before death.

Conclusion Primary care service cost patterns varied for specialist services and diagnostic and therapeutic services for both time to death and age. Significant differences in relationship between time to death, age and healthcare expenditure were identified between service types, highlighting potential shortcomings in using single population models to predict future healthcare expenditure.

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