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

Eric Q. Wu (), Zheng-Yi Zhou, Jipan Xie, Cinzia Metallo and Praveen Thokala
Additional contact information
Eric Q. Wu: Analysis Group
Zheng-Yi Zhou: Analysis Group
Jipan Xie: Analysis Group
Cinzia Metallo: Analysis Group
Praveen Thokala: University of Sheffield

PharmacoEconomics, 2019, vol. 37, issue 11, No 7, 1349-1354

Abstract: 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.

Date: 2019
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DOI: 10.1007/s40273-019-00842-0

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