Abstract 1367: Item response theory analysis of the patient satisfaction with cancer-related care: psychometric validation in a multicultural sample of 1,296 participants.
Authors: Pascal Jean-Pierre, Ying Cheng, Steven Patierno, Peter Raich, Richard Roetzheim, Steven Rosen, Donald Dudley, Karen Freund, Victoria Warren-Mears, Electra Paskett, Kevin Fiscella
Journal: Cancer Research (2013)

Abstract BACKGROUND: Patient satisfaction (PS) is an important outcome measure of quality of cancer-related care. PS was one of the four core study outcomes of the National Cancer Institute and American Cancer Society funded $25 million multicenter Patient Navigation Research Program (PNRP) to reduce disparities in cancer care. A Patient Satisfaction with Cancer Care (PSCC) measure was developed and validated for the PNRP using classical test theory and principal components analysis (PCA). OBJECTIVE: To calibrate items of the PSCC to facilitate the development of a computerized adaptive testing (CAT) system, which can be used to tailor the PSCC to patients’ satisfaction level based on properties of the items. METHODS: The PCA revealed a unidimensional PSCC measure. Thus, we applied unidimensional item response theory (IRT) models to the 18-item PSCC data from 1,296 participants (73% female; age 18 to 86 years). We fitted two IRT models to the data: An unconstrained graded response model (GRM) and a constrained GRM (i.e., Rasch Model) where all discrimination parameters across items were fixed to be equal. We obtained model fit indices (log-likelihood, AIC &amp; BIC) and performed model comparison through likelihood ratio (LR) test between the unconstrained GRM and the Rasch model. We obtained item and latent trait (i.e., patient satisfaction) parameter estimates, category characteristic curves, operating characteristic curves, and test information curves for the better fitting model. RESULTS: The unconstrained GRM fitted the data significantly better (LR = 828, df = 17, p &amp;lt; 0.001). Item parameter estimates showed strong items discriminating power (α = 0.94 to 2.18). Standard errors (SE) of the item parameter estimates were also small (i.e., mostly around 0.1 for the threshold parameters, and between 0.1 to 0.2 for the discrimination parameters), confirming the precision of the item parameter estimates obtained. CONCLUSIONS: The PSCC is suitable to be delivered through a CAT system where patients will receive tailored optimally selected items to measure their satisfaction levels, and scores will be equated across different subsets of items (i.e., test forms). An IRT-based PSCC CAT system will provide key patient reported outcome data to help improve patient-centered cancer care and satisfaction for medically underserved populations. Citation Format: Pascal Jean-Pierre, Ying Cheng, Steven Patierno, Peter Raich, Richard Roetzheim, Steven Rosen, Donald Dudley, Karen Freund, Victoria Warren-Mears, Electra Paskett, Kevin Fiscella. Item response theory analysis of the patient satisfaction with cancer-related care: psychometric validation in a multicultural sample of 1,296 participants. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1367. doi:10.1158/1538-7445.AM2013-1367