Ranking Vaccines A Prioritization Software Tool: Phase II: Prototype of a Decision-Support System (2013) / Chapter Skim
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2 Refinements to the SMART Vaccines Model
2 Refinements to the SMART Vaccines Model
Pages 25-32
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From page 25... ...
A Brief Review of the Modeling Framework The multi-attribute utility model underpinning SMART Vaccines is able to blend quantitative and user-based qualitative attributes. Priorities for vaccine candidates are then set according to a weighted average of the attributes chosen by the user (Keeney and Raiffa, 1976)
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From page 26... ...
In SMART Vaccines this resulting score is labeled the "SMART Score." Vaccines are ranked in priority according to the rank order of their SMART Scores. Figure 2-1 shows a diagram of the SMART Vaccines framework, slightly revised from the 2012 IOM report.
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From page 27... ...
To reflect this multiplicative impact of the licensure attribute, this value is now elicited from the user after the SMART Scores are produced for the vaccines being compared. Thus, if the resulting SMART Score for a specific vaccine candidate is calculated as 70, but the user-defined likelihood of successful licensure of that vaccine over a 10-year period is 50 percent, then the SMART Score is set to 35 to reflect the product of the original score and the probability of licensure.
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From page 28... ...
The reference points described next are a first attempt, which was based on an appraisal of the relevant literature but not on an actual application of SMART Vaccines to the six test vaccine candidates used to assure its current functionality. Future users of SMART Vaccines may wish to revisit the setting of these reference points following cumulative experiences with the software.
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From page 29... ...
This low-achieving vaccine defines zero on the SMART Score scale. Its opposite, with all four attributes at level x1 -- that is, a vaccine that has the potential to avert 14,000 premature deaths per year, has net incremental costs of $0 per QALY gained, is targeted to the primary benefit of infants and children, and is thermostable -- would achieve a SMART score of 100 and defines the highest value possible on the SMART Score.
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From page 30... ...
Now suppose that having obtained the rank order centroid outputs, the user chooses to alter the weights using slider bars for the specific attributes under consideration to 60 percent (premature deaths averted per year) , 18 percent (benefits infants and children)
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From page 31... ...
, then the weights they have placed on these attributes lead to predictable changes in each user's SMART Scores. If they have no common attributes in their respective value models, then it is not possible to compare one user's SMART Scores (and hence rankings)
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From page 32... ...
Quite to the contrary, SMART Vaccines makes clear what assumptions users have made about vaccine attributes and how they value each candidate vaccine's attributes. In the following chapter, the approaches taken to expand the test vaccine candidates and evaluate them using SMART Vaccines 1.0 are discussed.
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