EMPIRICALLY DEFINED HEALTH STATES FOR DEPRESSION FROM THE SF-12

Objective. To define objectively and describe a set of clinically rele vant health states that encompass the typical effects of depression on quality of life in an actual patient population. Our model was design ed to facilitate the elicitation of patients' and the public's values (utilities) for outcomes of depression. Data Sources. From the depress ion panel of the Medical Outcomes Study. Data include scores on the IF -Item Short Form Health Survey (SF-12) as well as independently obtain ed diagnoses of depression for 716 patients. Follow-up information, on e year after baseline, was available for 166 of these patients. Method ology. We use k-means cluster analysis to group the patients according to appropriate dimensions of health derived from the SF-12 scores. Ch i-squared and exact permutation tests are used to validate the health states thus obtained, by checking for baseline and longitudinal correl ation of cluster membership and clinical diagnosis. Principal Findings . We find, on the basis of a combination of statistical and clinical c riteria, that six states are optimal for summarizing the range of heal th experienced by depressed patients. Each state is described in terms of a subject who is typical in a sense that is articulated with our c luster-analytic approach. In all of our models, the relationship betwe en health state membership and clinical diagnosis is highly statistica lly significant. The models are also sensitive to changes in patients' clinical status over time. Conclusions. Cluster analysis is demonstra bly a powerful methodology for forming clinically valid health states from health status data. The states produced are suitable for the expe rimental elicitation of preference and analyses of costs and utilities .