OBJECTIVES: Achieving market access requires substantiating incremental value for the indicated patient population. The aim of this project was to provide an example of how mapping the relationship between clinical states and health utilities can inform early development strategy and clinical trial inclusion criteria. METHODS: US 2011 National Health and Wellness Survey data were used. Respondents with pain in the past month were included.  General linear models were used to examine the relationship between pain level in the last week (0 to 10 scale) and health utilities (using the SF6D algorithm) while controlling for sociodemographics and health history.  Models were replicated within pain subgroups (e.g., neuropathic pain, nocioceptive pain etc).  RESULTS: A total of 24,778 respondents (33.04%) reported pain in the past month (mean age = 50.24; 51.71% were female). The range of health utilities was 0.35-1.00.  Pain level was significantly associated with health utilities (b=-0.025, p<.05), though a cubic relationship was also identified whereby a 1-point reduction in pain was associated with a greater increase in utilities among those with mild pain (e.g., a reduction from 1 to 0 on the pain scale led to 0.027 increase in utilities) compared with those with severe pain (reduction from 10 to 9 lead to 0.010 increase in utilities).  Subgroups were also investigated; for example, only a significant linear relationship (no higher order trends) between pain level and health utilities was observed among those with neuropathic pain (b=-0.27, p<.05). CONCLUSIONS: The overall relationship between the level of pain and health utilities was non-linear suggesting that more incremental value could be substantiated by reducing milder pain than more severe pain. However, not all subgroups followed this pattern emphasizing the benefits of understanding the relationship between estimated treatment effects and health utilities early in the developmental process to inform clinical trial design, optimize incremental value, and drive cost effectiveness.