Title: Outcome valuation in the economic evaluation of healthcare
Abstract: Economic evaluation of healthcare interventions (such as pharmaceuticals, medical
devices and technologies) considers both the effect of the intervention on patients, and
the costs borne by the government and often the individual themselves. This
simultaneous consideration of costs and benefits is now standard practice in
reimbursement decisions, both in Australia and elsewhere. This thesis focuses on the
assessment of benefits, specifically how we place a value on the health changes
patients experience as a result of a health care intervention.
There is a well-established framework for how outcomes are valued in health care, but
this framework is built on a number of contentious assumptions. For example, health
is assumed to be the sole outcome of a healthcare system, and society is assumed to
be inequality-neutral. This thesis identifies and explains these assumptions and then
focuses on testing two of them in the empirical chapters. The overall aim of the thesis
is to explore the extent to which the current framework reflects population
preferences, and whether the framework can be adapted to be more reflective of
population preferences. The empirical chapters in this thesis consider these issues,
using a discrete choice experiment (DCE). For reasons presented in Chapters 3 and 4,
this technique offers very attractive properties for answering these types of questions.
The standard approach to valuing health outcomes uses the quality-adjusted life year,
in which the value of a health profile is the product of quality of life and length of life.
For this to be operationalised, we need to be able to describe health states in a way
which captures all relevant dimensions of quality of life that are important to people,
and then we need to assign values to health states. This thesis argues that the current
methods for assigning values to health states are very onerous for survey respondents,
and prone to significant bias. Standard valuation techniques require the respondent to
identify preferences around quality of life through the acceptance of a risk of death, or
the reduction of life expectancy to alleviate poor quality of life. However, these fail to
control for issues such as risk-aversion or time preference. The first empirical analysis
uses a DCE to value health states for the SF-6D, a health state valuation instrument
that is based on the very widely used quality of life instrument the SF-36. The use of
a DCE aims to remove (or control for) these biases. This chapter represents a
methodological advance through the use of a DCE, and produces the first Australian
algorithm for the SF-6D.
The second empirical analysis considers the assumption that the value of health
improvement is independent of who receives it. Therefore, it is conventional for an
extra year in full health to be regarded as being of the same value to society
independent of who receives it. The chapter results suggest that the average
respondent prefers giving additional health to people with low life…
Publication Year: 2012
Publication Date: 2012-01-01
Language: en
Type: dissertation
Access and Citation
Cited By Count: 1
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot