The cost of in-patient care in Western Australia in the last years of life: A population-based data linkage study

Abstract

Objectives

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.

Method

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.

Conclusion

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.

Introduction

Over the last 30 years, a significant change in the age composition of the population has occurred in most developed countries. The proportion of people aged 80 or more years has steadily increased and this trend is expected to continue into the future. The main contributors to the ageing demographic profile are decreased fertility and increased life expectancy made possible by improved living conditions, prevention programs and innovations in medicine [1].

A report on population ageing and the economy commissioned by the Australian Government in 2001 estimated that Australia would experience significant demographic change over the next few decades. It projected that the population would reach around 25.4 million by 2051, with downward trend in population growth from around 1.2% per annum in 1999 to 0.1% per annum in 2051. Between 1976 and 2001 the proportion of the population aged over 65 years rose from 9% (1.3 million) to 12% (2.3 million) [2]. Due to the reduced population growth the future composition of the Australian population has become steadily older. It has been projected that by 2016, 16% of the population will be aged over 65 years, and that by 2051 this proportion will have risen to 25% [2].

Recognising the significance of an ageing population the Australian Government developed a national strategy to devise short, medium and longer-term policy responses to population ageing. This strategy recognised that while many of the problems associated with the economic effects of ageing are concerned with the size of the workforce (working age depopulation), wealth creation (ratio of producers to consumers) and costs of social security (relative rise in the public resources required for pensions), the future cost of health-care was also a major concern [2].

Since it has been estimated that the older population will more than double in the next 30 years it has been suggested that ageing (and the resultant rising per capita utilisation) may add to health-care costs the equivalent of 1.78% of gross domestic product (A$ 11.6 billion in 2000 dollars) by 2031 [2]. However, such estimates have generally only taken into account the number of years from birth (age) rather than the number of years from death.

In recent years a number of economic studies [3], [4], [5], [6], [7] have been concerned with conducting a critical examination of the thesis that an ageing population is the main driver of health-care expenditure (HCE). Only one study by Hitiris and Posnett [8] found that the age structure of the population was a consistently significantly predictor of HCE across developed countries once confounders such as income, education, environmental factors were controlled. In other studies [5], [9], [10], [11], [12], [13], [14], [15], the results were mixed. By contrast, numerous studies have shown that HCEs are disproportionately concentrated at the end of life. For example, in the US, it has been consistently shown that approximately 6% of Medicare recipients who die in a particular year account for approximately 28% of HCE under that scheme [16], [17], [18]. Similar results have been reported for long-term care [19].

The concerns of recent studies have primarily been with the following questions: (i) To what extent is ageing per se the driver of HCE? (ii) To what extent does the proximity to death drive HCE? (iii) To what extent does the correlation between ageing and proximity to death confound demographically based forecasts of HCE? The ‘age neutrality hypothesis’ [3] that proximity to death rather than age per se drives HCE remains largely an open question, in part due to controversies over the sampling and econometric methods that have been employed. Resolving this argument is important because the more that HCE is driven by proximity to death and the less by age per se, the more likely are aged-based forecasts of future health-care spending to be overestimates.

The aim of this study was to explore patterns of health expenditure for in-patient care in the last 3 years of life so as to understand the degree to which different groups, and especially different age groups, contribute to health-care expenditure.