Conjoint analysis is a form of tradeoff analysis that elucidates how people make complex decisions by balancing competing factors.²⁷ Developed by Professor Paul Green at the Wharton School of the University of Pennsylvania, conjoint analysis was first widely used in the world of marketing.²⁸ This technique has since spread to product design, operations research, social sciences, and even healthcare. Recent studies have used conjoint to examine clinical decision-making in rheumatology,²⁹ spinal surgery,³⁰ diabetes management,³¹ use of transfusions in dialysis-related anemia,³² and even IBD.^33-38 This method is now considered to be a robust approach for analyzing decision-making in healthcare.²⁷

Conjoint analysis is based on the premise that any product (e.g., a good, service, or treatment) can be described by its attributes and is valued based on the levels of these attributes. As a simple example, consider someone looking to buy a new TV. Attributes for TVs can include price, screen size, and resolution, among others. Within each attribute, there are different levels. For instance, possible TV screen sizes are 40, 50, and 60 inches.

During the conjoint survey, respondents are presented with a series of side by side comparisons of competing product profiles. They then select which profile is preferable, if any. The Figure below uses our TV example. Based on the respondent’s answer to the first comparison, an algorithm selects new side by side comparisons and asks them to select the preferred profiles. The process continues until there is internal consistency and the technique collects enough data to rank their attribute preferences. For instance, some may value price over all other factors. Others may be willing to pay more as long as there is improved screen resolution.