Traditionally, welfare measures derived from random utility choice models estimated from choice experiments would be applicable to a “representative agent”.  Work has been undertaken to account for heterogeneity in welfare measures in various, indirect ways.  In contrast, this paper proposes a new way to allow for heterogeneity in such measures by directly calculating, rather than simulating, unique monetary values for single individuals. This is achieved by harnessing additional preference data collected in a best worst choice experiment and a new analytical approach to estimate a separate choice model for each individual, the results of which are used to directly calculate unique welfare measures per individual.  As such, it is possible to empirically characterise, rather than simulate, the distribution of monetary values in a bottom up fashion. This new approach is demonstrated in the context of a study exploring preferences and valuation of health care treatment.  Methodological and policy implications are explored.