in these applications. The aim of the checklist is to provide a framework for assessing and improving the quality of research methods broadly defined as conjoint analysis, without favoring one technique over another.
Why are Preferences of Patients and other Stakeholders Important?
Understanding how patients and other stakeholders perceive and value different aspects of their health or of health-care interventions is vital to the optimal design and evaluation of programs. Incorporating these values in decision making ultimately may result in clinical, licensing, reimbursement, and policy decisions that better reflect the preferences of stakeholders, especially patients. Furthermore, aligning clinical practice, drug development, and health policy with patient preferences ultimately could improve the effectiveness of health interventions, possibly improving the adoption of, satisfaction with, and adherence to clinical treatments or public health programs.
What are Stated Preference Methods?
Stated-preference studies employ a variety of methods that are grounded in economic theory. These methods fall into two broad categories:
methods using ranking, rating, or choice designed to quantify preferences for various attributes of an intervention (often referred to as conjoint analysis, discrete-choice experiments, or stated-choice methods) and
methods using direct elicitation to estimate the monetary value of a single intervention (including methods known as contingent valuation, willingness-to-pay, and willingness to accept) (8-9).
The former methods are based on the economic theory of preferences and utility, while the latter methods are based on demand theory. Economic theories of preferences and demand are interconnected and, as such, these two approaches to stated preferences often overlap. For the purposes of this paper, we will focus on the former, and for simplicity, we will use the term conjoint analysis to describe the various related methodologies.
Conjoint Analysis in Health and Medicine
Conjoint analysis is used to measure the relative value of specific components of health status and health-care alternatives by decomposing an alternative into its constituent parts (10-13). For example, the component attributes that define a pharmaceutical intervention might include efficacy outcomes, safety and tolerability outcomes, mode of administration, and cost. In all conjoint analyses, different levels are assigned to each component attribute to create a series of profiles which study subjects are asked to evaluate through rating, ranking, or choice tasks. Subjects’ systematic evaluation of these profiles allows researchers to infer the relative importance of each component attribute as well as changes in the levels of each component attribute. In this report, we define a conjoint analysis as any study in which subjects are asked to evaluate at least two profiles, each defined by at least two component attributes with at least two possible levels for each attribute.
Stated preference methods such as conjoint analysis are particularly useful for quantifying preferences for products or outcomes in cases where no markets exist or where market choices are influenced by regulatory and
ISPOR Conjoint Analysis in Health Task Force Report