Health states that describe an investigated condition are a crucial component of valuation studies. The health states need to be distinct and comprehensible to those who appraise them. 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.
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 dimension from the EuroQol-5D was also incorporated.
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.
The combined use of Rasch and k-means cluster analysis has proved to be an effective technique for identifying the most important items and levels for the construction of health states.