Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR Task Force on Good Research Practices--Modeling Studies
- PMID: 12535234
- DOI: 10.1046/j.1524-4733.2003.00234.x
Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR Task Force on Good Research Practices--Modeling Studies
Abstract
Objectives: Mathematical modeling is used widely in economic evaluations of pharmaceuticals and other health-care technologies. Users of models in government and the private sector need to be able to evaluate the quality of models according to scientific criteria of good practice. This report describes the consensus of a task force convened to provide modelers with guidelines for conducting and reporting modeling studies.
Methods: The task force was appointed with the advice and consent of the Board of Directors of ISPOR. Members were experienced developers or users of models, worked in academia and industry, and came from several countries in North America and Europe. The task force met on three occasions, conducted frequent correspondence and exchanges of drafts by electronic mail, and solicited comments on three drafts from a core group of external reviewers and more broadly from the membership of ISPOR.
Results: 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.
Conclusions: Model-based evaluations are a valuable resource for health-care decision makers. It is the responsibility of model developers to conduct modeling studies according to the best practicable standards of quality and to communicate results with adequate disclosure of assumptions and with the caveat that conclusions are conditional upon the assumptions and data on which the model is built.
Comment in
-
Making decisions on technology availability in the British National Health Service--why we need reliable models.Value Health. 2003 Jan-Feb;6(1):3-5. doi: 10.1046/j.1524-4733.2003.00002.x. Value Health. 2003. PMID: 12535232 No abstract available.
-
The ISPOR Good Practice Modeling Principles--a sensible approach: be transparent, be reasonable.Value Health. 2003 Jan-Feb;6(1):6-8. doi: 10.1046/j.1524-4733.2003.00003.x. Value Health. 2003. PMID: 12535233 No abstract available.
Similar articles
-
Principles of good practice for budget impact analysis: report of the ISPOR Task Force on good research practices--budget impact analysis.Value Health. 2007 Sep-Oct;10(5):336-47. doi: 10.1111/j.1524-4733.2007.00187.x. Value Health. 2007. PMID: 17888098
-
Good research practices for measuring drug costs in cost effectiveness analyses: issues and recommendations: the ISPOR Drug Cost Task Force report--Part I.Value Health. 2010 Jan-Feb;13(1):3-7. doi: 10.1111/j.1524-4733.2009.00663.x. Epub 2009 Oct 28. Value Health. 2010. PMID: 19874571
-
The ISPOR Good Practices for Quality Improvement of Cost-Effectiveness Research Task Force Report.Value Health. 2009 Nov-Dec;12(8):1086-99. doi: 10.1111/j.1524-4733.2009.00605.x. Epub 2009 Sep 10. Value Health. 2009. PMID: 19744291
-
Budget impact analysis-principles of good practice: report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force.Value Health. 2014 Jan-Feb;17(1):5-14. doi: 10.1016/j.jval.2013.08.2291. Epub 2013 Dec 13. Value Health. 2014. PMID: 24438712
-
Using real-world data for coverage and payment decisions: the ISPOR Real-World Data Task Force report.Value Health. 2007 Sep-Oct;10(5):326-35. doi: 10.1111/j.1524-4733.2007.00186.x. Value Health. 2007. PMID: 17888097
Cited by
-
Clinical and cost-effectiveness of pessary self-management versus clinic-based care for pelvic organ prolapse in women: the TOPSY RCT with process evaluation.Health Technol Assess. 2024 May;28(23):1-121. doi: 10.3310/NWTB5403. Health Technol Assess. 2024. PMID: 38767959 Free PMC article. Clinical Trial.
-
Barriers and Facilitators of Using R for Decision Analytic Modeling in Health Technology Assessment: Focus Group Results.Pharmacoeconomics. 2024 Jul;42(7):783-795. doi: 10.1007/s40273-024-01374-y. Epub 2024 Apr 12. Pharmacoeconomics. 2024. PMID: 38607519
-
Decision analysis in cardiac surgery: a scoping review and methodological primer.Eur J Cardiothorac Surg. 2024 Mar 29;65(4):ezae123. doi: 10.1093/ejcts/ezae123. Eur J Cardiothorac Surg. 2024. PMID: 38539047 Free PMC article. Review.
-
Digital variance angiography in patients undergoing lower limb arterial recanalization: cost-effectiveness analysis within the English healthcare setting.J Comp Eff Res. 2024 Mar 22;13(4):e230068. doi: 10.57264/cer-2023-0068. Online ahead of print. J Comp Eff Res. 2024. PMID: 38517149 Free PMC article.
-
Evaluating the Validation Process: Embracing Complexity and Transparency in Health Economic Modelling.Pharmacoeconomics. 2024 Jul;42(7):715-719. doi: 10.1007/s40273-024-01364-0. Epub 2024 Mar 18. Pharmacoeconomics. 2024. PMID: 38498106 Free PMC article. No abstract available.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Miscellaneous