Literature DB >> 22990083

Conceptualizing a model: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-2.

Mark Roberts1, Louise B Russell2, A David Paltiel3, Michael Chambers4, Phil McEwan5, Murray Krahn6.   

Abstract

The appropriate development of a model begins with understanding the problem that is being represented. The aim of this article is to provide a series of consensus-based best practices regarding the process of model conceptualization. For the purpose of this series of papers, the authors consider the development of models whose purpose is to inform medical decisions and health-related resource allocation questions. They specifically divide the conceptualization process into two distinct components: the conceptualization of the problem, which converts knowledge of the health care process or decision into a representation of the problem, followed by the conceptualization of the model itself, which matches the attributes and characteristics of a particular modeling type to the needs of the problem being represented. Recommendations are made regarding the structure of the modeling team, agreement on the statement of the problem, the structure, perspective and target population of the model, and the interventions and outcomes represented. Best practices relating to the specific characteristics of model structure, and which characteristics of the problem might be most easily represented in a specific modeling method, are presented. Each section contains a number of recommendations that were iterated among the authors, as well as the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.

Mesh:

Year:  2012        PMID: 22990083     DOI: 10.1177/0272989X12454941

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  61 in total

Review 1.  Current challenges in health economic modeling of cancer therapies: a research inquiry.

Authors:  Jeffrey D Miller; Kathleen A Foley; Mason W Russell
Journal:  Am Health Drug Benefits       Date:  2014-05

2.  Economic evaluations with agent-based modelling: an introduction.

Authors:  Jagpreet Chhatwal; Tianhua He
Journal:  Pharmacoeconomics       Date:  2015-05       Impact factor: 4.981

3.  Climate influences on the cost-effectiveness of vector-based interventions against malaria in elimination scenarios.

Authors:  Paul E Parham; Dyfrig A Hughes
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2015-04-05       Impact factor: 6.237

Review 4.  Verification of Decision-Analytic Models for Health Economic Evaluations: An Overview.

Authors:  Erik J Dasbach; Elamin H Elbasha
Journal:  Pharmacoeconomics       Date:  2017-07       Impact factor: 4.981

5.  Modeling Treatment Sequences in Pharmacoeconomic Models.

Authors:  Ying Zheng; Feng Pan; Sonja Sorensen
Journal:  Pharmacoeconomics       Date:  2017-01       Impact factor: 4.981

Review 6.  Model Structuring for Economic Evaluations of New Health Technologies.

Authors:  Hossein Haji Ali Afzali; Laura Bojke; Jonathan Karnon
Journal:  Pharmacoeconomics       Date:  2018-11       Impact factor: 4.981

7.  Understanding and Identifying Key Issues with the Involvement of Clinicians in the Development of Decision-Analytic Model Structures: A Qualitative Study.

Authors:  Samantha Husbands; Susan Jowett; Pelham Barton; Joanna Coast
Journal:  Pharmacoeconomics       Date:  2018-12       Impact factor: 4.981

8.  Building better models: if we build them, will policy makers use them? Toward integrating modeling into health care decisions.

Authors:  Jeanne Mandelblatt; Clyde Schechter; David Levy; Ann Zauber; Yaojen Chang; Ruth Etzioni
Journal:  Med Decis Making       Date:  2012 Sep-Oct       Impact factor: 2.583

Review 9.  A systematic review of the quality of economic models comparing thrombosis inhibitors in patients with acute coronary syndrome undergoing percutaneous coronary intervention.

Authors:  Maximilian H M Hatz; Reiner Leidl; Nichola A Yates; Björn Stollenwerk
Journal:  Pharmacoeconomics       Date:  2014-04       Impact factor: 4.981

10.  Trends in Characteristics of Patients Listed for Liver Transplantation Will Lead to Higher Rates of Waitlist Removal Due to Clinical Deterioration.

Authors:  Zinan Yi; Maria E Mayorga; Eric S Orman; Stephanie B Wheeler; Paul H Hayashi; A Sidney Barritt
Journal:  Transplantation       Date:  2017-10       Impact factor: 4.939

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