Counting the time lived, the time left or illness? Age, proximity to death, morbidity and prescribing expenditures

Abstract

The objective is to understand what really drives prescription expenditure at the end of life in order to inform future expenditure projections and service planning. To achieve this objective an empirical analysis of public medication expenditure on the older population (individuals ≥ 70 years of age) in Ireland (n = 231,780) was undertaken. A two part model is used to analysis the individual effects of age, proximity to death (PTD) and morbidity using individual patient-level data from administrative pharmacy records for 2006-2009 covering the population of community medication users. Decedents (n = 14,084) consistently use more medications and incur larger expenditures than similar survivors, especially in the last 6 months of life. The data show a positive and statistically significant impact of PTD on prescribing expenditures with minimal effect for age alone even accounting for patient morbidities. Nevertheless improved measures of morbidity are required to fully test the hypothesis that age and PTD are proxies for morbidity. The evidence presented refutes age as a driver of prescription expenditure and highlights the importance of accounting for mortality in future expenditure projections.

Projections of demand for healthcare in Ireland, 2015-2030: First report from the Hippocrates Model

“…Others have argued that medical technology, rather than proximity to death impacts costs (201,202). In an Irish context, Moore et al found proximity to death, but not age, to be a significant driver of pharmaceutical costs (203), while a Danish study found that pharmaceutical costs will increase with age regardless of proximity to death (204).…”

A pragmatic method to compare hospital bed provision between countries and regions: Beds in the States of Australia

“…Hence, there is a pressing need to develop two compartment models which apply the usual factors relating to age for the non‐end‐of‐life component of care and the absolute number of deaths (and its associated volatility) into the end‐of‐life component of care. An excellent example of this approach has been recently applied to prescription costs, and the aIM is eminently suited to modification to achieve this outcome.…”

“…What the nearness to death effect observes is that health care demand rises only slowly with age but escalates dramatically as death approaches, irrespective of the age at death . Other measures such as prescription expenditure likewise accelerate as death approaches . Around half of a person's lifetime hospital admissions and bed occupancy are compressed into the last year of life …”

The calendar year fallacy: The danger of reliance on calendar year data in end‐of‐life capacity and financial planning

“…The link between death and healthcare costs arises from the nearness to death effect, where it is observed that around half of a person's lifetime hospital admissions and bed occupancy occurs in the last year of life [7][8][9][10][11][12][13][14] and more specifically in the last 6 months. 15,16 Indeed, an admission to hospital for medical care (at any age) is associated with a far higher risk of death within 1 year.…”