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

Barry Dewitt, David Feeny, Baruch Fischhoff, David Cella, Ron D. Hays, Rachel Hess, Paul A. Pilkonis, Dennis A. Revicki, Mark S. Roberts, Joel Tsevat, Lan Yu and Janel Hanmer
Additional contact information
Barry Dewitt: Carnegie Mellon University, Department of Engineering and Public Policy, Pittsburgh, PA, USA
Baruch Fischhoff: Carnegie Mellon University, Department of Engineering and Public Policy, Pittsburgh, PA, USA
David Cella: Northwestern University Feinberg School of Medicine, Chicago, IL, USA
Ron D. Hays: University of California Los Angeles David Geffen School of Medicine, Los Angeles, CA, USA
Rachel Hess: University of Utah, Salt Lake City, UT, USA
Paul A. Pilkonis: University of Pittsburgh Medical Center, Pittsburgh, PA, USA
Dennis A. Revicki: Evidera Inc, Bethesda, MD, USA
Mark S. Roberts: University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA
Joel Tsevat: University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
Lan Yu: University of Pittsburgh Medical Center, Pittsburgh, PA, USA
Janel Hanmer: University of Pittsburgh Medical Center, Pittsburgh, PA, USA

Medical Decision Making, 2018, vol. 38, issue 6, 683-698

Abstract: 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.

Keywords: health-related quality of life; health utility; PROMIS; US general population (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:38:y:2018:i:6:p:683-698

DOI: 10.1177/0272989X18776637

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