Evidence map›Paper›PMID 28849538›Full record

ArticlePharmacoEconomics2017

The HTA Risk Analysis Chart: Visualising the Need for and Potential Value of Managed Entry Agreements in Health Technology Assessment.

Sabine Elisabeth Grimm, Mark Strong, Alan Brennan, Allan J Wailoo

Abstract read
In one paragraph

Article in PharmacoEconomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  14. An Efficient Method for Computing Expected Value of Sample Information for Survival Data from an Ongoing Trial.Medical decision making : an international journal of the Society for Medical Decision Making · 2022
    Article
  15. Article
  16. Simulating Study Data to Support Expected Value of Sample Information Calculations: A Tutorial.Medical decision making : an international journal of the Society for Medical Decision Making · 2022
    Article
  17. Prioritisation and design of clinical trials.European journal of epidemiology · 2021
    Article
  18. A Review of Web-Based Tools for Value-of-Information Analysis.Applied health economics and health policy · 2021
    Review
  19. How Managed Entry Agreements can improve allocation in the public health system: a mechanism design approach.The European journal of health economics : HEPAC : health economics in prevention and care · 2021
    Article
  20. Article
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

4 authors.

Sabine Elisabeth GrimmMaastricht University Medical Center, Maastricht, The Netherlands. sabine.grimm@mumc.nl.
Mark StrongSchool of Health And Related Research, University of Sheffield, Sheffield, UK.
Alan BrennanSchool of Health And Related Research, University of Sheffield, Sheffield, UK.
Allan J WailooSchool of Health And Related Research, University of Sheffield, Sheffield, UK.

Funding

Department of Health PDF-2012-05-258Medical Research Council G0601721Medical Research Council MR/J000434/1
6 · The paper itself

Abstract

backgroundRecent changes to the regulatory landscape of pharmaceuticals may sometimes require reimbursement authorities to issue guidance on technologies that have a less mature evidence base. Decision makers need to be aware of risks associated with such health technology assessment (HTA) decisions and the potential to manage this risk through managed entry agreements (MEAs).

objectiveThis work develops methods for quantifying risk associated with specific MEAs and for clearly communicating this to decision makers.

methodsWe develop the 'HTA risk analysis chart', in which we present the payer strategy and uncertainty burden (P-SUB) as a measure of overall risk. The P-SUB consists of the payer uncertainty burden (PUB), the risk stemming from decision uncertainty as to which is the truly optimal technology from the relevant set of technologies, and the payer strategy burden (PSB), the additional risk of approving a technology that is not expected to be optimal. We demonstrate the approach using three recent technology appraisals from the UK National Institute for Health and Clinical Excellence (NICE), each of which considered a price-based MEA.

resultsThe HTA risk analysis chart was calculated using results from standard probabilistic sensitivity analyses. In all three HTAs, the new interventions were associated with substantial risk as measured by the P-SUB. For one of these technologies, the P-SUB was reduced to zero with the proposed price reduction, making this intervention cost effective with near complete certainty. For the other two, the risk reduced substantially with a much reduced PSB and a slightly increased PUB.

conclusionsThe HTA risk analysis chart shows the risk that the healthcare payer incurs under unresolved decision uncertainty and when considering recommending a technology that is not expected to be optimal given current evidence. This allows the simultaneous consideration of financial and data-collection MEA schemes in an easily understood format. The use of HTA risk analysis charts will help to ensure that MEAs are considered within a standard utility-maximising health economic decision-making framework.

Indexed as

Decision MakingDrug and Narcotic ControlCost-Benefit AnalysisData CollectionHumansPharmaceutical PreparationsReimbursement MechanismsTechnology Assessment, BiomedicalUncertaintyUnited KingdomPharmaceutical Preparations

Identifiers

PMID28849538
PMCPMC5684269

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.