ISPOR Task Force Report: Good Practice for Decision Analytic Modeling in Health-Care
2003
This report describes the consensus of a task force convened to provide modelers with guidelines for conducting and reporting modeling studies. While published more than a decade ago, it remains a clearly written resource for thinking about how to accurately describe the components of models and their quality.
Criteria for assessing the quality of models fell into three areas: model structure, data used as inputs to models, and model validation. Several major themes cut across these areas. Models and their results should be represented as aids to decision making, not as statements of scientific fact; therefore, it is inappropriate to demand that models be validated prospectively before use.
However, model assumptions regarding causal structure and parameter estimates should be continually assessed against data, and models should be revised accordingly. Structural assumptions and parameter estimates should be reported clearly and explicitly, and opportunities for users to appreciate the conditional relationship between inputs and outputs should be provided through sensitivity analyses.
ISPOR Task Force Report: Good Practice for Decision Analytic Modeling in Health-Care
Source:
Weinstein MC, O’Brien B, Hornberger J et al. Principles of Good Practice for Decision Analytic Modeling in Health-Care Evaluation: Report of the ISPOR Task Force on Good Research Practices--Modeling Studies. Value in Health 2003; 6 (1): 9-17. https://doi.org/10.1046/j.1524-4733.2003.00234.x