OBJECTIVES: The purpose of this study was to investigate the development of an incremental willingness to pay curve (IWTPC) using parameters obtained from a discrete choice experiment (DCE). METHODS: The DCE was structured around a novel genetic technology that identifies genetic causes of developmental delay (DD). The DCE included three alternatives. The first two alternatives differed on three attributes: number of children receiving a genetic diagnosis, time waiting for results, and cost. The third alternative was an opt-out option to allow for non-demanders. A mixed logit (MXL) behavioural model was specified to incorporate preference heterogeneity, and hierarchical Bayes (HB) was employed to estimate the joint posterior of parameter partworths. The opt-out parameter was assumed to follow a normal distribution, a truncated normal was given to number of children diagnosed and waiting time, and the log normal distribution was assumed for cost. The HB procedures employed allow for the direct estimation of each individual's parameter estimates, which are transformed into an incremental willingness to pay (WTP) value. Under certain assumptions, the IWTPC represents the incremental WTP that each individual in society has for the technology under a given scenario. RESULTS: A total of 796 respondents from the general public were recruited using a research firm in British Columbia, Canada. Each respondent completed 16 choice questions. The parameter estimates revealed a considerable amount of preference heterogeneity, which indicated that the mean incremental WTP estimate might not accurately represent society's WTP. Individual WTP ranged from $28 to $12,000 for an increase in 14 children identified to have a genetic cause of DD and a 1-week reduction in waiting time. Fifty-one percent of respondents had an incremental WTP of at least $1041 for the scenario. CONCLUSION: Using the joint posterior of preference partworths, the IWTPC is a promising tool to characterize the value of a health care good.