| Title |
Does the use of the proportional shortfall help align the prioritisation of health services with public preferences?
|
|---|---|
| Published in |
HEPAC Health Economics in Prevention and Care, August 2017
|
| DOI | 10.1007/s10198-017-0923-5 |
| Pubmed ID | |
| Authors |
Jeff Richardson, Angelo Iezzi, Aimee Maxwell, Gang Chen |
| Abstract |
It has been proposed that equity may be included in the economic evaluation of health services using the 'proportional shortfall' (PS)-the proportion of a person's QALY expectation that they would lose because of an illness. The present paper reports the results of a population survey designed to test whether PS helped to explain people's preferences for health services and whether it did this better than the absolute shortfall or the equity related variables that PS seeks to replace. Survey respondents were asked to allocate 100 votes between 13 scenarios and a standard scenario. Variation in the allocation of votes was explained by health gain and different combinations of the equity variables. Differences in votes for the comparisons were significantly related to differences in PS but the relationship was weaker than between votes and the age related variables. Cases were identified where PS suggested a priority ordering of services which was strongly rejected by respondents. It is concluded that the use of PS is unlikely to improve the alignment of priorities with public preferences. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 14% |
| Researcher | 3 | 14% |
| Student > Bachelor | 2 | 10% |
| Other | 2 | 10% |
| Student > Master | 2 | 10% |
| Other | 4 | 19% |
| Unknown | 5 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 9 | 43% |
| Social Sciences | 2 | 10% |
| Sports and Recreations | 1 | 5% |
| Decision Sciences | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 7 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 11 August 2017.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from HEPAC Health Economics in Prevention and Care
#1,039
of 1,303 outputs
Outputs of similar age
#253,797
of 328,185 outputs
Outputs of similar age from HEPAC Health Economics in Prevention and Care
#11
of 15 outputs
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