Clustering Rasch results: a novel method for developing rheumatoid arthritis states for use in valuation studies.
OBJECTIVE
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.


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 dimension from the EuroQol-5D was also incorporated.


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
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.
McTaggart-Cowan
Helen M
HM
School ofHealth and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK. h.m.cowan@sheffield.ac.uk
Brazier
John E
JE
Tsuchiya
Aki
A
D000203:Activities of Daily Living; D001172:Arthritis, Rheumatoid / Q000145:classification* / Q000175:diagnosis; D016000:Cluster Analysis; D004185:Disability Evaluation; D006305:Health Status Indicators; D006801:Humans; D011594:Psychometrics; D019057:Quality-Adjusted Life Years; D012720:Severity of Illness Index; D011795:Surveys and Questionnaires