DEVELOPMENT AND INITIAL PSYCHOMETRIC VALIDATION OF A REAL-TIME PATIENT REPORTED EXPERIENCE MEASURE
Autor: | Lesley Moody, Sarah Benn, Luciano Ieraci, Esther Green, Saurabh Ingale, Gillian Hurwitz, Nancy M Kraetschmer, Erica Bridge, Simron Singh |
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Rok vydání: | 2022 |
Zdroj: | International Journal of Person Centered Medicine. 10:27-46 |
ISSN: | 2043-7749 2043-7730 |
Popis: | Patient-reported experience measures (PREMs) capture the patient’s view about his or her experience while receiving care across the continuum of care. Your Voice Matters (YVM), a real-time electronic PREM tool, was developed to measure the patient experience in the outpatient cancer setting and to drive quality improvements in the cancer system. This study describes the development and validation of YVM, a real-time electronic PREM tool in cancer services. Cognitive interviewing was conducted with patient and family advisors for both the French (n = 3) and English (n = 5) versions of the YVM tool. YVM was administered through five Regional Cancer Centers (RCCs) between April and August 2015. Shapley value regression used overall experience-dependent variables to determine core items and items eligible for removal from YVM. Exploratory factor analysis was used to determine the underlying factor structure.Internal consistency reliabilities were calculated using Cronbach’s alpha. A total of 557 YVM tools were completed by cancer patients in the treatment phase. Shapley value regression identified five lower scoring items for removal. Exploratory factor analysis showed that a 27-item, five-factor structure reflected the underlying patient experience dimensions in the cancer treatment visit. Cronbach’s alpha of 0.827 for all items suggested good internal consistency. YVM is a validated tool for measuring the experience of cancer patients during the treatment phase through the visit trajectory in real time. YVM will help drive improvements based on patients’ preferences and needs, and will provide robust patient experience data for cancer care delivery. |
Databáze: | OpenAIRE |
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