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Estimating cost-effectiveness in public health: a summary of modelling and valuation methods

Overview of attention for article published in Health Economics Review, September 2012
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Title
Estimating cost-effectiveness in public health: a summary of modelling and valuation methods
Published in
Health Economics Review, September 2012
DOI 10.1186/2191-1991-2-17
Pubmed ID
Authors

Kevin Marsh, Ceri J Phillips, Richard Fordham, Evelina Bertranou, Janine Hale

Abstract

It is acknowledged that economic evaluation methods as they have been developed for Health Technology Assessment do not capture all the costs and benefits relevant to the assessment of public health interventions. This paper reviews methods that could be employed to measure and value the broader set of benefits generated by public health interventions. It is proposed that two key developments are required if this vision is to be achieved. First, there is a trend to modelling approaches that better capture the effects of public health interventions. This trend needs to continue, and economists need to consider a broader range of modelling techniques than are currently employed to assess public health interventions. The selection and implementation of alternative modelling techniques should be facilitated by the production of better data on the behavioural outcomes generated by public health interventions. Second, economists are currently exploring a number of valuation paradigms that hold the promise of more appropriate valuation of public health interventions outcomes. These include the capabilities approach and the subjective well-being approach, both of which offer the possibility of broader measures of value than the approaches currently employed by health economists. These developments should not, however, be made by economists alone. These questions, in particular what method should be used to value public health outcomes, require social value judgements that are beyond the capacity of economists. This choice will require consultation with policy makers, and perhaps even the general public. Such collaboration would have the benefit of ensuring that the methods developed are useful for decision makers.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 161 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 8 5%
Spain 2 1%
Netherlands 1 <1%
Chile 1 <1%
Canada 1 <1%
Germany 1 <1%
New Zealand 1 <1%
United States 1 <1%
Unknown 145 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 17%
Researcher 27 17%
Student > Master 24 15%
Other 17 11%
Student > Postgraduate 12 7%
Other 25 16%
Unknown 29 18%
Readers by discipline Count As %
Medicine and Dentistry 47 29%
Economics, Econometrics and Finance 23 14%
Social Sciences 10 6%
Nursing and Health Professions 7 4%
Psychology 7 4%
Other 30 19%
Unknown 37 23%
Attention Score in Context

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 07 September 2019.
All research outputs
#15,251,053
of 22,678,224 outputs
Outputs from Health Economics Review
#262
of 421 outputs
Outputs of similar age
#106,835
of 169,044 outputs
Outputs of similar age from Health Economics Review
#4
of 6 outputs
Altmetric has tracked 22,678,224 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 421 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 169,044 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
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