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Developing Guidance for Budget Impact Analysis

Overview of attention for article published in PharmacoEconomics, September 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

policy
4 policy sources

Citations

dimensions_citation
173 Dimensions

Readers on

mendeley
129 Mendeley
Title
Developing Guidance for Budget Impact Analysis
Published in
PharmacoEconomics, September 2012
DOI 10.2165/00019053-200119060-00001
Pubmed ID
Authors

Paul Trueman, Michael Drummond, John Hutton

Abstract

The role of economic evaluation in the efficient allocation of healthcare resources has been widely debated. Whilst economic evidence is undoubtedly useful to purchasers, it does not address the issue of affordability which is an increasing concern. Healthcare purchasers are concerned not just with maximising efficiency but also with the more simplistic goal of remaining within their annual budgets. These two objectives are not necessarily consistent. This paper examines the issue of affordability, the relationship between affordability and efficiency and builds the case for why there is a growing need for budget impact models to complement economic evaluation. Guidance currently available for such models is also examined and it is concluded that this guidance is currently insufficient. Some of these insufficiencies are addressed and some thoughts on what constitutes best practice in budget impact modelling are suggested. These suggestions include consideration of transparency, clarity of perspective, reliability of data sources, the relationship between intermediate and final end-points and rates of adoption of new therapies. They also include the impact of intervention by population subgroups or indications, reporting of results, probability of re-deploying resources, the time horizon, exploring uncertainty and sensitivity analysis, and decision-maker access to the model. Due to the nature of budget impact models, the paper does not deliver stringent methodological guidance on modelling. The intention was to provide some suggestions of best practice in addition to some foundations upon which future research can build.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 3 2%
United Kingdom 2 2%
Canada 1 <1%
Germany 1 <1%
Denmark 1 <1%
United States 1 <1%
Unknown 120 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 20%
Researcher 25 19%
Student > Ph. D. Student 18 14%
Student > Doctoral Student 8 6%
Student > Postgraduate 6 5%
Other 24 19%
Unknown 22 17%
Readers by discipline Count As %
Medicine and Dentistry 31 24%
Economics, Econometrics and Finance 31 24%
Pharmacology, Toxicology and Pharmaceutical Science 8 6%
Social Sciences 7 5%
Nursing and Health Professions 6 5%
Other 18 14%
Unknown 28 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 27 December 2022.
All research outputs
#2,863,993
of 25,374,917 outputs
Outputs from PharmacoEconomics
#247
of 1,992 outputs
Outputs of similar age
#20,025
of 189,948 outputs
Outputs of similar age from PharmacoEconomics
#32
of 550 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,992 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 86% 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 189,948 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 89% of its contemporaries.
We're also able to compare this research output to 550 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.