Dr. Daphna Harel
Department of Applied Statistics, Social Science, and Humanities
New York University
"Using Optimal Test Assembly Methods to Shorten Patient Reported Outcome Measures"
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. This manuscript proposes the use of mixed integer programming through Optimal Test Assembly as a method to shorten patient-reported outcome measures. This method is compared to the existing standard in the field, selecting items based on having high discrimination parameters from an item response theory model. The method is then illustrated in an application to a fatigue scale for patients with Systemic Sclerosis.