OBJECTIVES: The aim of the current study was to develop an algorithm to map the symptom domain of the Impact of Dry Eye on Everyday Life (IDEEL) questionnaire to a preference based utility index. METHODS: Data from an IDEEL psychometric validation study including 210 participants (130 dry eye patients, 32 Sjogren’s patients and 48 controls) were used to estimate the algorithm.  Participants completed the IDEEL, EQ-5D and SF-36 at 2 time points; the first time point was used to estimate the algorithm and the second to validate the algorithm.  The mapping work was preceded by determining bivariate correlations between the IDEEL items and each utility index (EQ-5D and SF-6D), and then examining the sensitivity of each index to variability in dry eye severity.  Initial items were selected based on levels of missing data, floor and ceiling effects and correlations with the utility index.  Items were then included in an OLS regression model with age and gender interaction terms.  Following the item analysis the same procedures were applied to a domain level analysis. RESULTS: Based on the criteria outlined above, the SF-6D was selected as the utility index for the mapping algorithm.  The final OLS regression model contained 2 IDEEL symptoms items and age, and explained 28% of the variance in SF-6D utility values; root mean squared error (RMSE) = 0.105.   As the SF-6D data included few bounded or censored estimates Tobit and CLAD models were not estimated.   The validation dataset demonstrated a significant correlation between the predicted and observed SF-6D utility values (r = 0.53, p <0.001). CONCLUSIONS: This algorithm forms a good basis to estimate utility values from the IDEEL for inclusion in cost-effectiveness analysis.