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12-04-2018 | Uitgave 7/2018

Quality of Life Research 7/2018

Evaluation of options for presenting health-states from PROMIS® item banks for valuation exercises

Quality of Life Research > Uitgave 7/2018
Janel Hanmer, David Cella, David Feeny, Baruch Fischhoff, Ron D. Hays, Rachel Hess, Paul A. Pilkonis, Dennis Revicki, Mark Roberts, Joel Tsevat, Lan Yu
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Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s11136-018-1852-1) contains supplementary material, which is available to authorized users.



Health status descriptive systems based on item response theory (IRT), such as the Patient-Reported Outcomes Measurement Information System (PROMIS®), have item banks to measure domains of health. We developed a method to present such banks for health-state valuation.


We evaluated four different presentation approaches: a single item (1S), 2 items presented separately (2S), 2 items presented together (2T), or 5 items presented together (5T). We evaluated these four approaches in three PROMIS item banks (depression, physical function, and sleep disturbance). Adult community members valued health-state descriptions using the visual analog scale and standard gamble methods. We compared the approaches by the range of item bank theta scores captured, participants’ assessments of difficulty (1 = very easy to 7 = very hard), and exit interviews.


Participants (n = 118) ranged in age from 18 to 71; 63% were female and 54% were white. The 1S approach captured the smallest range of theta scores. A monotonic relationship between theta score and mean standard gamble estimate was found with all approaches except 2S. Across all 3 item banks, mean difficulty assessments were 2.35 (1S), 2.69 (2T), 2.78 (5T), and 2.80 (2S). In exit interviews, participants generally found all four approaches similarly meaningful and realistic.


Creating health descriptions by presenting 2 items maximized the range of theta while minimizing difficulty and maintaining a monotonic relationship with utility estimates. We recommend this approach for valuation of IRT-based descriptive systems such as PROMIS.

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