What Does Your PROMIS Score Mean? Improving the Utility of Patient-Reported Outcomes at the Point of Care
Authors: Shaw Jeremy D. , McEntarfer Ross , Ferrel Jason , Greene Natasha , Presson Angela P. , Zhang Chong , Lawrence Brandon D. , Spiker William R. , Spina Nicholas , Brodke Darrel S. 
Published: October 2020

Study Design: Prospective cohort. Objectives: Patient-Reported Outcome Measurement Information System (PROMIS) has been validated for lumbar spine. Use of patient-reported outcome (PRO) measures can improve clinical decision making and health literacy at the point of care. Use of PROMIS, however, has been limited in part because clinicians and patients lack plain language understanding of the meaning of scores and it remains unclear how best to use them at the point of care. The purpose was to develop plain language descriptions to apply to PROMIS Physical Function (PF) and Pain Interference (PI) scores and to assess patient understanding and preferences in presentation of their individualized PRO information. Methods: Retrospective analysis of prospectively collected PROMIS PF v1.2 and PI v1.1 for patients presenting to a tertiary spine center for back/lower extremity complaints was performed. Patients with missing scores, standard error >0.32, and assessments with <4 or >12 questions were excluded. Scores were categorized into score groups, specifically PROMIS PF groups were: <18, 20 ± 2, 25 ± 2, 30 ± 2, 35 ± 2, 40 ± 2, 45 ± 2, 50 ± 2, 55 ± 2, 60 ± 2, and >62; and PROMIS PI groups were: <48, 50 ± 2, 55 ± 2, 60 ± 2, 65 ± 2, 70 ± 2, 75 ± 2, 80 ± 2, and >82. Representative questions and answers from the PROMIS PI and PROMIS PF were selected for each score group, where questions with <25 assessments or representing <15% of assessments were excluded. Two fellowship-trained spine surgeons further trimmed the questions to create a streamlined clinical tool using a consensus process. Plain language descriptions for PROMIS PF were then used in a prospective assessment of 100 consecutive patients. Patient preference for consuming the score data was recorded and analyzed. Results: In total, 12 712 assessments/5524 unique patients were included for PF and 14 823 assessments/6582 unique patients for PI. More than 90% of assessments were completed in 4 questions. The number of assessments and patients per scoring group were normally distributed. The mean PF score was 37.2 ± 8.2 and the mean PI was 63.3 ± 7.4. Plain language descriptions and compact clinical tool was were generated. Prospectively 100 consecutive patients were surveyed for their preference in receiving their T-score versus plain language description versus graphical presentation. A total of 78% of patients found receiving personalized PRO data helpful, while only 1% found this specifically not helpful. Overall, 80% of patients found either graphical or plain language more helpful than T-score alone, and half of these preferred plain language and graphical descriptions together. In total, 89% of patients found the plain language descriptions to be accurate. Conclusions: Patients at the point of care are interested in receiving the results of their PRO measures. Plain language descriptions of PROMIS scores enhance patient understanding of PROMIS numerical scores. Patients preferred plain language and/or graphical representation rather than a numerical score alone. While PROs are commonly used for assessing outcomes in research, use at point of care is a growing interest and this study clarifies how they might be utilized in physician-patient communication.