Evidence map›Paper›PMID 27484123›Full record

ArticleBMC public health2016

What criteria do decision makers in Thailand use to set priorities for vaccine introduction?

Siriporn Pooripussarakul, Arthorn Riewpaiboon, David Bishai, Charung Muangchana, Sripen Tantivess

Abstract read
In one paragraph

Article in BMC public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. A decision-making framework for COVID-19 infodemic management strategies evaluation in spherical fuzzy environment.Stochastic environmental research and risk assessment : research journal · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Siriporn PooripussarakulDepartment of Pharmacy, Faculty of Pharmacy, Mahidol University, Bangkok, 10400, Thailand.
Arthorn RiewpaiboonDepartment of Pharmacy, Faculty of Pharmacy, Mahidol University, Bangkok, 10400, Thailand. arthorn.rie@mahidol.ac.th.ORCID 0000-0003-2959-3244
David BishaiDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
Charung MuangchanaNational Vaccine Institute, Ministry of Public Health, Nonthaburi, 11000, Thailand.
Sripen TantivessHealth Intervention and Technology Assessment Program (HITAP), Ministry of Public Health, Nonthaburi, 11000, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is a need to identify rational criteria and set priorities for vaccines. In Thailand, many licensed vaccines are being considering for introduction into the Expanded Program on Immunization; thus, the government has to make decisions about which vaccines should be adopted. This study aimed to set priorities for new vaccines and to facilitate decision analysis.

methodsWe used a best-worst scaling study for rank-ordering of vaccines. The candidate vaccines were determined by a set of criteria, including burden of disease, target age group, budget impact, side effect, effectiveness, severity of disease, and cost of vaccine. The criteria were identified from a literature review and by in-depth, open-ended interviews with experts. The priority-setting model was conducted among three groups of stakeholders, including policy makers, healthcare professionals and healthcare administrators. The vaccine data were mapped and then calculated for the probability of selection.

resultsFrom the candidate vaccines, the probability of hepatitis B vaccine being selected by all respondents (96.67 %) was ranked first. This was followed, respectively, by pneumococcal conjugate vaccine-13 (95.09 %) and Haemophilus influenzae type b vaccine (90.87 %). The three groups of stakeholders (policy makers, healthcare professionals and healthcare administrators) showed the same ranking trends. Most severe disease, high fever rate and high disease burden showed the highest coefficients for criterion levels being selected by all respondents. This result can be implied that a vaccine which can prevent most severe disease with high disease burden and has low safety has a greater chance of being selected by respondents in this study.

conclusionsThe priority setting of vaccines through a multiple-criteria approach could contribute to transparency and accountability in the decision-making process. This is a step forward in the development of an evidence-based approach that meets the need of developing country. The methodology is generalizable but its application to another country would require the criteria as relevant to that country.

Indexed as

Communicable Disease ControlDecision MakingHealth PrioritiesImmunization ProgramsPatient SelectionVaccinesBacterial CapsulesCost of IllnessDecision Support TechniquesDeveloping CountriesFeverHaemophilus InfectionsHaemophilus VaccinesHepatitis BHepatitis B VaccinesHumansHaemophilus influenzae type b polysaccharide vaccineHaemophilus VaccinesHepatitis B VaccinesPneumococcal VaccinesVaccinesVaccines, ConjugateDecision-makingPriority-settingVaccine

Identifiers

PMID27484123
PMCPMC4970258

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.