Purpose: Health states that describe an investigated condition are a crucial component of valuation studies. The health states need to be distinct, comprehensible, and data-driven. The objective of this study was to describe a novel application of Rasch and cluster analyses in the development of three rheumatoid arthritis health states. Methods: The Stanford Health Assessment Questionnaire (HAQ) was subjected to Rasch analysis to select the items that best represent disability. K-means cluster analysis produced health states with the levels of the selected items. The pain and discomfort domain from the EuroQol-5D was incorporated at the final stage. Results: The results demonstrate a methodology for reducing a dataset containing individual disease-specific scores to generate health states. The four selected HAQ items were bending down, climbing steps, lifting a cup to your mouth, and standing up from a chair. Conclusions: Overall, the combined use of Rasch and cluster analysis has proved to be an effective technique for identifying the most important items and levels for the construction of health states.