Administration of patient-reported outcome measures (PROs), using multidimensional computer adaptive tests (MCATs) has the potential to reduce patient burden, but the efficiency of MCAT depends on the degree to which an individual's responses fit the psychometric properties of the assessment. Assessing patients' symptom burden through the administration of MCATs is gaining popularity in clinical settings, especially in orthopeadics where patients reporting low physical functioning and high pain interference may not always report high levels of depression. Are MCATs more efficient and precise than unidimensional CATs in a patient profile where the person-item fit varies between symptoms? Results depend on the item selection algorithm used in the assessments. Constraining item selection algorithm can substantially reduce test lengths where person-item fit is poor. This study demonstrates how MCAT can reduce patient burden in settings where collecting PROs is becoming part of routine care.