Can We Make Health Economic Decision Models as Simple as Possible, But Not Simpler? Introducing SMART tool

Area of Science:

• Health economics
• Decision science
• Mathematical modeling

Background:

• Health economic decision-analytic models necessitate careful selection of modeling choices to simplify reality while remaining relevant to the decision context.
• Achieving an appropriate balance between model simplicity and adequacy is crucial yet challenging in model development.

Purpose of the Study:

• To create a tool that facilitates systematic reporting and justification of modeling choices in decision-analytic models.
• To ensure models are adequate and appropriately complex for their intended decision context.

Main Methods:

• Identified key decision-analytic model features from literature and expert input.
• Defined simple and complex choices for each feature, detailing consequences of inappropriate simplification.
• Designed and refined the Systematic Model Adequacy and Reporting Tool (SMART) through expert interviews and workshops, including a case study.

Main Results:

• Developed SMART, a tool featuring a framework of 28 model features for selecting and assessing modeling choices.
• SMART evaluates the consequences of user-selected choices on model validity and transparency.
• Included a glossary sheet for consistent application, demonstrated with a treatment-resistant hypertension model.

Conclusions:

• SMART enhances decision-analytic model development and assessment by promoting clear reporting and justification of modeling choices.
• The tool highlights the impact of choices on model validity and transparency.
• Well-justified modeling choices optimize resource use and ensure model adequacy for decision-making.