Teebah Abu-Zahra, Sabine E Grimm, Mirre Scholte, Manuela Joore
{"title":"我们能使健康经济决策模型尽可能简单，但不能更简单吗？介绍SMART工具。","authors":"Teebah Abu-Zahra, Sabine E Grimm, Mirre Scholte, Manuela Joore","doi":"10.1007/s40273-025-01515-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Developing health economic decision-analytic models requires making modelling choices to simplify reality while addressing the decision context. Finding the right balance between a decision-analytic model's simplicity and its adequacy is important but can be challenging.</p><p><strong>Objective: </strong>We aimed to develop a tool that supports the systematic reporting and justification of modelling choices in a decision-analytic model, ensuring it is adequate and only as complex as necessary for addressing the decision context.</p><p><strong>Methods: </strong>We identified decision-analytic model features from the 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 decision-analytic model on a repurposed drug for treatment-resistant hypertension.</p><p><strong>Results: </strong>We conducted five interviews and two workshops with 18 decision-analytic model experts. The developed SMART (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.</p><p><strong>Conclusions: </strong>SMART supports decision-analytic model 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 optimise the use of resources and time for model development, while ensuring the model is adequate to support decision making.</p>","PeriodicalId":19807,"journal":{"name":"PharmacoEconomics","volume":" ","pages":"1235-1250"},"PeriodicalIF":4.6000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12450218/pdf/","citationCount":"0","resultStr":"{\"title\":\"Can We Make Health Economic Decision Models as Simple as Possible, But Not Simpler? Introducing SMART tool.\",\"authors\":\"Teebah Abu-Zahra, Sabine E Grimm, Mirre Scholte, Manuela Joore\",\"doi\":\"10.1007/s40273-025-01515-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Developing health economic decision-analytic models requires making modelling choices to simplify reality while addressing the decision context. Finding the right balance between a decision-analytic model's simplicity and its adequacy is important but can be challenging.</p><p><strong>Objective: </strong>We aimed to develop a tool that supports the systematic reporting and justification of modelling choices in a decision-analytic model, ensuring it is adequate and only as complex as necessary for addressing the decision context.</p><p><strong>Methods: </strong>We identified decision-analytic model features from the 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 decision-analytic model on a repurposed drug for treatment-resistant hypertension.</p><p><strong>Results: </strong>We conducted five interviews and two workshops with 18 decision-analytic model experts. The developed SMART (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.</p><p><strong>Conclusions: </strong>SMART supports decision-analytic model 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 optimise the use of resources and time for model development, while ensuring the model is adequate to support decision making.</p>\",\"PeriodicalId\":19807,\"journal\":{\"name\":\"PharmacoEconomics\",\"volume\":\" \",\"pages\":\"1235-1250\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12450218/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PharmacoEconomics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s40273-025-01515-x\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/26 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PharmacoEconomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s40273-025-01515-x","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/26 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Can We Make Health Economic Decision Models as Simple as Possible, But Not Simpler? Introducing SMART tool.
Background: Developing health economic decision-analytic models requires making modelling choices to simplify reality while addressing the decision context. Finding the right balance between a decision-analytic model's simplicity and its adequacy is important but can be challenging.
Objective: We aimed to develop a tool that supports the systematic reporting and justification of modelling choices in a decision-analytic model, ensuring it is adequate and only as complex as necessary for addressing the decision context.
Methods: We identified decision-analytic model features from the 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 decision-analytic model on a repurposed drug for treatment-resistant hypertension.
Results: We conducted five interviews and two workshops with 18 decision-analytic model experts. The developed SMART (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: SMART supports decision-analytic model 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 optimise the use of resources and time for model development, while ensuring the model is adequate to support decision making.
期刊介绍：
PharmacoEconomics is the benchmark journal for peer-reviewed, authoritative and practical articles on the application of pharmacoeconomics and quality-of-life assessment to optimum drug therapy and health outcomes. An invaluable source of applied pharmacoeconomic original research and educational material for the healthcare decision maker.
PharmacoEconomics is dedicated to the clear communication of complex pharmacoeconomic issues related to patient care and drug utilization.
PharmacoEconomics offers a range of additional features designed to increase the visibility, readership and educational value of the journal’s content. Each article is accompanied by a Key Points summary, giving a time-efficient overview of the content to a wide readership. Articles may be accompanied by plain language summaries to assist readers who have some knowledge of, but not in-depth expertise in, the area to understand the scientific content and overall implications of the article.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
