The cost of in-patient care in Western Australia in the last years of life: a population-based data linkage study.
OBJECTIVE
This study aimed to explore patterns of health expenditure for in-patient care in the last 3 years of life so as to understand how age and time to death contribute to health-care expenditure.


METHODS
Records of all deaths occurring in Western Australia from 1997 to 2000 inclusive were extracted from the WA mortality register and linked to records from the hospital morbidity data system (HMDS) via the WA Data Linkage System. Inflation adjusted hospital costs were assigned to all in-patient events occurring within 3 years of death from five major causes of death using DRG costing information.


RESULTS
Prior to the last 5 months of life the mean cost of hospitalisation was positively associated with age; however, the magnitude of the cost increase in the last 5 months of life was inversely related to age such that the cost in the last month of life was similar across age groups.


CONCLUSIONS
The finding that increased costs are associated with proximity to death, but that the magnitude of the increase is inversely associated with age, has implications for the ongoing debate about whether proximity to death or age is the dominant driver of health-care costs. The results of this study suggest that models forecasting future health-care expenditure should take into account the interaction of age, time to death and cause of death. In addition, we propose that due to the differences observed across causes of death it may be that a single general population model may not be capable of fully capturing the relationship and that this may be why the debate regarding age and time to death has yet to be resolved in the literature.
Moorin
Rachael Elizabeth
RE
Australian Centre for Economic Research on Health (UWA node), School of Population Health, The University of Western Australia, Crawley, WA, Australia. rachael.moorin@uwa.edu.au
Holman
Cashel D'Arcy James
CD
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001315:Australia; D002648:Child; D002675:Child, Preschool; D003625:Data Collection; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000191:economics*; D006801:Humans; D007223:Infant; D008297:Male; D008875:Middle Aged; D012737:Sex Factors