Principles of Good Practice for Decision Analytic Modeling in Health-Care Evaluation: Report of the ISPOR Task Force on Good Research Practices—Modeling Studies

The citation for this report is:
Weinstein MC, O'Brien B, Hornberger J, et al. Principles of good practice of decision analytic modeling in health care evaluation: Report of the ISPOR Task Force on Good Research Practices-Modeling Studies. Value Health 2003; 6:9-17

Task Force Chair
Milton C. Weinstein PhD, Center for Risk Analysis, Harvard School of Public Health, Boston, Massachusetts, and Innovus Research, Inc., Medford, Massachusetts, USA.

Leadership Group
Chris McCabe MSc, Senior Lecturer in Health Economics, Trent Institute for Health Services Research, University of Sheffield, Sheffield, UK.
John Hornberger MD, MS, Acumen, LLC, and Stanford University School of Medicine, Stanford, California, USA.
Joseph Jackson PhD, Group Director, Pharmaceutical Research Institute, Bristol-Myers Squibb, Princeton, New Jersey, USA.
Magnus Johannesson PhD, Associate Professor, Centre for Health Economics, Stockholm School of Economics, Stockholm, Sweden.
Bryan R. Luce PhD, Senior Research Leader and CEO, MEDTAP International, Bethesda, Maryland
Bernie O’Brien PhD, Professor, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada

Reviewer Group
Andrea K. Biddle MPH, PhD, Associate Professor, Department of Health Policy and Administration, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Donald Chafin MD, MS, Director, SICU/Associate Professor of Medicine & Epidemiology, Beth Israel Medical Center/Albert Einstein College of Medicine, New York, NY, USA.
Daniel Halberg PhD, Assistant Professor, University of Arkansas for Medical Sciences, Little Rock, Matthew Rousculp MPH, The University of Alabama at Birmingham, Birmingham, AL, USA.
Phantipa Sathkong MS, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Pathumwan, Bangkok, Thailand.
Daniel Sarpong PhD, Associate Professor of Biostatistics, College of Pharmacy, Xavier University of Louisiana, New Orleans, LA, USA.
Hemal Shah PharmD, Director, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CN, USA.
Mendel Singer PhD, Assistant Professor, Case Western Reserve University, Cleveland, OH, USA.
Dong-Churl Suh PhD, Assistant Professor, Rutgers University, College of Pharmacy, Piscataway, NJ
John Walt MBA, Manager, Global Pharmacoeconomic Strategy & Research, Allergan, Irvine, CA, USA.
Leslie Wilson PhD, MS Adjunct Assistant Professor, University of California San Francisco, San Francisco, California, CA, USA.

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 prior to use. However, model assumptions regarding causal structure and parameter estimates should be continually assessed against data, and models 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 upon which the model is built.

Contact ISPOR @ info@ispor.org  |  View Legal Disclaimer
©2010 International Society for Pharmacoeconomics and Outcomes Research. All rights reserved under International and Pan-American Copyright Conventions. 
Website design by Eagle Systems USA, Inc.