B0536
Title: Using optimal test assembly to shorten patient reported outcome measures
Authors: Daphna Harel - New York University (United States) [presenting]
Abstract: Patient-reported outcome measures are widely used to assess respondent experiences, well-being, and treatment response in clinical trials and cohort-based observational studies in both medicine and psychological studies. However, respondents may be asked to respond to many different scales in order to provide researchers and clinicians with a wide array of information regarding their experiences. Therefore, collecting such long and cumbersome patient-reported outcome measures may burden respondents and increase research costs. However, little research has been conducted on optimal, replicable, and reproducible methods to shorten these instruments. We propose the use of mixed-integer programming through Optimal Test Assembly as a method to shorten patient-reported outcome measures. We will provide several examples as well as a comparison to existing methods in the field.
