Classifying medication use in clinical research.

Abstract

BACKGROUND: Medication use data are usually collected in clinical research. Yet no standardized method for categorizing these exists, either for sample description or for the study of medication use as a variable. OBJECTIVE: The present investigation was designed to develop a simple, empirically based classification scheme for medication use categorization. METHOD: The authors used factor analysis to reduce the number of possible medication groupings. This permitted a pattern of medication usage to emerge that appeared to characterize specific clinical constellations. To illustrate the technique's potential, the authors applied this classification system to samples where sleep disorders are prominent: chronic fatigue syndrome and sleep apnea. RESULTS: The authors' classification approach resulted in 5 factors that appear to cohere in a logical fashion. These were labeled Cardiovascular or Metabolic Syndrome Medication, Symptom Relief Medication, Psychotropic Medication, Preventative Medication, and Hormonal Medication. CONCLUSIONS: The findings show that medication profile varies according to clinical sample. The medication profile for participants with sleep apnea reflects known comorbid conditions; the medication profile associated with chronic fatigue syndrome appears to reflect the common perception of this condition as a psychogenic disorder.