Estimation of a Preference-Based Summary Score for the Patient-Reported Outcomes Measurement Information System: The PROMIS®-Preference (PROPr) Scoring System Journal Articles uri icon

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  • Background. Health-related quality of life (HRQL) preference-based scores are used to assess the health of populations and patients and for cost-effectiveness analyses. The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS®) consists of patient-reported outcome measures developed using item response theory. PROMIS is in need of a direct preference-based scoring system for assigning values to health states. Objective. To produce societal preference-based scores for 7 PROMIS domains: Cognitive Function–Abilities, Depression, Fatigue, Pain Interference, Physical Function, Sleep Disturbance, and Ability to Participate in Social Roles and Activities. Setting. Online survey of a US nationally representative sample ( n = 983). Methods. Preferences for PROMIS health states were elicited with the standard gamble to obtain both single-attribute scoring functions for each of the 7 PROMIS domains and a multiplicative multiattribute utility (scoring) function. Results. The 7 single-attribute scoring functions were fit using isotonic regression with linear interpolation. The multiplicative multiattribute summary function estimates utilities for PROMIS multiattribute health states on a scale where 0 is the utility of being dead and 1 the utility of “full health.” The lowest possible score is –0.022 (for a state viewed as worse than dead), and the highest possible score is 1. Limitations. The online survey systematically excludes some subgroups, such as the visually impaired and illiterate. Conclusions. A generic societal preference-based scoring system is now available for all studies using these 7 PROMIS health domains.


  • Dewitt, Barry
  • Feeny, David
  • Fischhoff, Baruch
  • Cella, David
  • Hays, Ron D
  • Hess, Rachel
  • Pilkonis, Paul A
  • Revicki, Dennis A
  • Roberts, Mark S
  • Tsevat, Joel
  • Yu, Lan
  • Hanmer, Janel

publication date

  • August 2018

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