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A new method for valuing health: directly eliciting personal utility functions

Overview of attention for article published in The European Journal of Health Economics, July 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#30 of 796)
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
1 blog
twitter
13 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
8 Mendeley
Title
A new method for valuing health: directly eliciting personal utility functions
Published in
The European Journal of Health Economics, July 2018
DOI 10.1007/s10198-018-0993-z
Pubmed ID
Authors

Nancy J. Devlin, Koonal K. Shah, Brendan J. Mulhern, Krystallia Pantiri, Ben van Hout

Abstract

Standard methods for eliciting the preference data upon which 'value sets' are based generally have in common an aim to 'uncover' people's preferences by asking them to evaluate a subset of health states, then using their responses to infer their preferences over all dimensions and levels. An alternative approach is to ask people directly about the relative importance to them of the dimensions, levels and interactions between them. This paper describes a new stated preference approach for directly eliciting personal utility functions (PUFs), and reports a pilot study to test its feasibility for valuing the EQ-5D. A questionnaire was developed, designed to directly elicit PUFs from general public respondents via computer-assisted personal interviews, with a focus on helping respondents to reflect and deliberate on their preferences. The questionnaire was piloted in England. Seventy-six interviews were conducted in December 2015. Overall, pain/discomfort and mobility were found to be the most important of the EQ-5D dimensions. The ratings for intermediate improvements in each dimension show heterogeneity, both within and between respondents. Almost a quarter of respondents indicated that no EQ-5D health states are worse than dead. The PUF approach appears to be feasible, and has the potential to yield meaningful, well-informed preference data from respondents that can be aggregated to yield a value set for the EQ-5D. A deliberative approach to health state valuation also has the potential to complement and develop existing valuation methods. Further refinement of some elements of the approach is required.

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 25%
Other 1 13%
Student > Postgraduate 1 13%
Student > Master 1 13%
Librarian 1 13%
Other 2 25%
Readers by discipline Count As %
Medicine and Dentistry 3 38%
Economics, Econometrics and Finance 2 25%
Social Sciences 2 25%
Unspecified 1 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 August 2018.
All research outputs
#898,374
of 13,333,056 outputs
Outputs from The European Journal of Health Economics
#30
of 796 outputs
Outputs of similar age
#32,170
of 267,627 outputs
Outputs of similar age from The European Journal of Health Economics
#3
of 26 outputs
Altmetric has tracked 13,333,056 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 796 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,627 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.