Co-calibrating quality-of-life scores from three pulmonary disorders: implications for comparative-effectiveness research. (2nd June 2016)

• Record Type: Journal Article
• Authors: Rouse, M.; Twiss, J.; McKenna, S. P.
• Is Part Of: Journal of medical economics. Volume 19:Number 6(2016)
• Page Start: 596
• Page End: 603
• Publication Date: 2016-06-02
• Subjects: Asthma -- Co-calibration -- Chronic obstructive pulmonary disease -- Comparative effectiveness research -- Item response theory -- Pulmonary hypertension -- Rasch analysis -- γ scores; Medical care -- Cost control -- Periodicals; Medical economics -- Periodicals; 362.10941
• DOI: 10.3111/13696998.2016.1148700
• Languages: English
• ISSNs: 1369-6998

Abstract

Abstract: Background Efficient use of health resources requires accurate outcome assessment. Disease-specific patient-reported outcome (PRO) measures are designed to be highly relevant to patients with a specific disease. They have advantages over generic PROs that lack relevance to patient groups and miss crucial impacts of illness. It is thought that disease-specific measurement cannot be used in comparative effectiveness research (CER). The present study provides further evidence of the value of disease-specific measures in making valid comparisons across diseases. Methods The Asthma Life Impact Scale (ALIS, 22 items), Living with Chronic Obstructive Pulmonary Disease (LCOPD, 22 items) scale, and Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR, 25 items) were completed by 140, 162, and 91 patients, respectively. The three samples were analyzed for fit to the Rasch model, then combined into a scale consisting of 58 unique items and re-analyzed. Raw scores on the three measures were co-calibrated and a transformation table produced. Results The scales fit the Rasch model individually (ALIS Chi 2 probability value ( p -Chi 2 ) = 0.05; LCOPD p -Chi 2 = 0.38; CAMPHOR p -Chi 2 = 0.92). The combined data also fit the Rasch model ( p -Chi 2 = 0.22). There was no differential item functioning related to age, gender, or disease. The co-calibrated scales successfully distinguished between perceived severity groups ( p < 0.001). Limitations The samples were drawn from different sources. For scales to be co-calibrated using a common item design, they must be based on the same theoretical construct, be unidimensional, and have overlapping items. Conclusions The results showed that it is possible to co-calibrate scores from disease-specific PRO measures. This will permit more accurate and sensitive outcome measurement to be incorporated into CER. The co-calibration of needs-based disease-specific measures allows the calculation of γ scores that can be used to compare directly the impact of any type of interventions on any diseases included in the co-calibration.