PAR7: VALIDATION OF A MODEL OF SEVERITY OF ILLNESS IN CHRONIC RESPIRATORY DISEASE

Abstract

OBJECTIVES: The purpose of this study is to adapt a previously validated questionnaire to a pharmacy claims database and examine its construct validity in measuring severity of illness in chronic respiratory disease (CRD). METHODS: The authors modified an asthma severity of illness questionnaire (13 items, total score range 0?28) based upon symptoms, medication use, hospitalization information and intubation history to a scale that is more conducive to retrospective data analysis. The adapted CRD scale (CRDS) was based on pharmacy claims data and hospitalization history (11 items, total score range 0?18). The CRDS was compared to utility as measured by a general health visual analogue scale and quality of life (QoL) as measured by the Physical Component Scale (PCS), Physical Function (PF) and General Health (GH) domains of the SF-36. Panel data analysis was performed on pharmacy claims and survey data from the Kaiser Permanente/USC Consultation Study. QoL and utility were regressed on the CRDS, along with covariates. A non-respiratory chronic disease score was used to control for chronic disease while avoiding significant multicollinearity. The analysis was limited to 126 patients with CRD followed over 3 years. The Hausman specification test was used to determine the appropriateness of the random-effects model formulation. RESULTS: The Hausman specification test suggested the use of the fixed-effects formulation for utility (m = 8.2, p> m = 0.0420). The CRDS was negative and significant (?1.79, p < 0.0286). The Hausman test suggested a fixed-effects formulation for PCS (p> m = 0.0333) and random-effects for GH (p> m = 0.0628) and PF (p> m = 0.1495). The CRDS was significant and negative for all three QoL domains: (PCS: ?0.68, p < 0.0085; PF: ?0.97, p<0.0130; GH: ?0.065, p < 0.0077). CONCLUSION: The adaptation of the asthma severity of illness questionnaire appears to be a valid measure of chronic respiratory disease in a pharmacy claims database.