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      Can we Make Health Economic Decision Models as Simple as Possible, but Not Simpler? Introducing the SMART tool

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            Abstract

            Background: Developing health economic decision-analytic models (DAMs) requires making modelling choices to simplify reality while addressing the decision context. Finding the right balance between a DAM’s simplicity and its adequacy is important but can be challenging.

            Objective: To develop a tool that supports the systematic reporting and justification of modelling choices in a DAM, ensuring it is adequate and only as complex as necessary for addressing the decision context.

            Methods: We identified DAM features from key literature and our expertise. For each feature, we defined both simple and complex modelling choices that could be selected, and the consequences of simplifying a feature contrary to requirements of the decision context. Next, we designed the tool and assessed its clarity and completeness through interviews and expert workshops. To ensure consistency of use, we developed a glossary sheet and applied the tool in an illustrative case: a DAM on a repurposed drug for treatment-resistant hypertension.

            Results: We conducted five interviews and two workshops with 18 DAM experts. The developed SMART tool (Systematic Model adequacy Assessment and Reporting Tool) consists of a framework of 28 model features, allowing users to select modelling choices per feature, then assessing the consequences of their choices for validity and transparency. SMART also includes a glossary sheet. The treatment resistant hypertension case example is provided separately.

            Conclusions: The SMART tool supports DAM development and assessment, by promoting clear reporting and justification of modelling choices, and highlighting their consequences for model validity and transparency. Thoughtful and well-justified modelling choices can help optimize the use of resources and time for model development, while ensuring the model is adequate to support decision-making.

            Content

            Author and article information

            Journal
            DrugRxiv
            REPO4EU
            30 May 2025
            Affiliations
            [1 ] Maastricht University Medical Centre ( https://ror.org/02d9ce178)
            [2 ] Maastricht University, Maastricht, The Netherlands ( https://ror.org/02jz4aj89)
            [3 ] Maastricht University Medical Centre, Maastricht, The Netherlands ( https://ror.org/02d9ce178)
            [4 ] Radboud UMC ( https://ror.org/05wg1m734)
            [5 ] Maastricht University ( https://ror.org/02jz4aj89)
            Author notes
            Author information
            https://orcid.org/0000-0002-1090-1721
            Article
            10.58647/DRUGARXIV.PR000029.v1
            c7d956f7-af33-457e-b3f1-6e5624a44bc9

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            History
            : 30 May 2025
            Funding
            Funded by: funder-id https://doi.org/10.13039/100018693, HORIZON EUROPE Framework Programme;
            Categories

            All data generated or analysed during this study are included in this published article (and its supplementary information files).
            Economics of health & social care,Health & Social care
            Health Technology Assessment ,Health economics decision-analytic models,SMART tool

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