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Choosing and Using Patient-Reported Outcome Measures in Clinical Practice

Published:March 09, 2021DOI:https://doi.org/10.1016/j.apmr.2020.12.033

      Abstract

      The increasing use of patient-reported outcome (PRO) measures is forcing clinicians and health care systems to decide which to select and how to incorporate them into their records and clinical workflows. This overview addresses 3 topics related to these concerns. First, a literature review summarizes key psychometric and practical factors (such as reliability, responsiveness, computer adaptive testing, and interpretability) in choosing PROs for clinical practice. Second, 3 clinical decision support issues are highlighted: gathering PROs, electronic health record effect on providers, and incorporating PROs into clinical decision support design and implementation. Lastly, the salience of crosscutting domains as well as 9 key pragmatic decisions are reviewed. Crosscutting domains are those that are relevant across most medical and mental health conditions, such as the SPADE symptom pentad (sleep problems, pain, anxiety, depression, low energy/fatigue) and physical functioning. The 9 pragmatic decisions include (1) generic vs disease-specific scales; (2) single- vs multidomain scales; (3) universal scales vs user-choice selection; (4) number of domains to measure; (5) prioritization of domains when multiple domains are assessed; (6) action thresholds; (7) clinical purpose (screening vs monitoring); as well as the (8) frequency and (9) logistical aspects of PRO administration.

      Keywords

      List of abbreviations:

      CAT (computer adaptive testing), EHR (electronic health record), IRT (item response theory), MCAT (multidimensional computer adaptive testing), MID (minimally important difference), PHQ (Patient Health Questionnaire), PRO (patient-reported outcome), PROMIS (Patient-Reported Outcome Measurement Information System), SPADE (sleep problems, pain, anxiety, depression, and low energy/fatigue), UCAT (unidimensional computer adaptive testing)
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