Evidence map›Paper›PMID 31591672›Full record

ArticlePharmacoEconomics2019

Transparency in Health Economic Modeling: Options, Issues and Potential Solutions.

Eric Q Wu, Zheng-Yi Zhou, Jipan Xie, Cinzia Metallo, Praveen Thokala

Abstract read
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In one paragraph

Article in PharmacoEconomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 3 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

6 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. 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

5 authors.

Eric Q WuAnalysis Group, 111 Huntington Avenue, 14th Floor, Boston, MA, 02199, USA. eric.wu@analysisgroup.com.
Zheng-Yi ZhouAnalysis Group, Angel Court, London, England, EC2R 7HJ, UK.
Jipan XieAnalysis Group, 333 South Hope Street, Los Angeles, CA, 90071, USA.
Cinzia MetalloAnalysis Group, 111 Huntington Avenue, 14th Floor, Boston, MA, 02199, USA.
Praveen ThokalaUniversity of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Economic models are increasingly being used by health economists to assess the value of health technologies and inform healthcare decision making. However, most published economic models represent a kind of black box, with known inputs and outputs but undisclosed internal calculations and assumptions. This lack of transparency makes the evaluation of the model results challenging, complicates comparisons between models, and limits the reproducibility of the models. Here, we aim to provide an overview of the possible steps that could be undertaken to make economic models more transparent and encourage model developers to share more detailed calculations and assumptions with their peers. Scenarios with different levels of transparency (i.e., how much information is disclosed) and reach of transparency (i.e., who has access to the disclosed information) are discussed, and five key concerns (copyrights, model misuse, confidential data, software, and time/resources) pertaining to model transparency are presented, along with possible solutions. While a shift toward open-source models is underway in health economics, as has happened before in other research fields, the challenges ahead should not be underestimated. Importantly, there is a pressing need to find an acceptable trade-off between the added value of model transparency and the time and resources needed to achieve such transparency. To this end, it will be crucial to set incentives at different stakeholder levels. Despite the many challenges, the many benefits of publicly sharing economic models make increased transparency a goal worth pursuing.

Indexed as

Models, EconomicBiomedical TechnologyDecision MakingDelivery of Health CareEconomics, MedicalHumansReproducibility of ResultsSoftwareTechnology Assessment, Biomedical

Identifiers

What OpenQuestion holds

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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.