The Challenge of Transparency and Validation in Health Economic Decision Modelling: A View from Mount Hood

Transparency in health economic decision modelling is important for engendering confidence in the models and in the reliability of model-based cost-effectiveness analyses. The Mount Hood Diabetes Challenge Network has taken a lead in promoting transparency through validation with biennial conferences in which diabetes modelling groups meet to compare simulated outcomes of pre-specified scenarios often based on the results of pivotal clinical trials. Model registration is a potential method for promoting transparency, while also reducing the duplication of effort. An important network initiative is the ongoing construction of a diabetes model registry (https://www.mthooddiabeteschallenge.com). Following the 2012 International Society for Pharmacoeconomics and Outcomes Research and the Society of Medical Decision Making (ISPOR-SMDM) guidelines, we recommend that modelling groups provide technical and non-technical documentation sufficient to enable model reproduction, but not necessarily provide the model code. We also request that modelling groups upload documentation on the methods and outcomes of validation efforts, and run reference case simulations so that model outcomes can be compared. In this paper, we discuss conflicting definitions of transparency in health economic modelling, and describe the ongoing development of a registry of economic models for diabetes through the Mount Hood Diabetes Challenge Network, its objectives and potential further developments, and highlight the challenges in its construction and maintenance. The support of key stakeholders such as decision-making bodies and journals is key to ensuring the success of this and other registries. In the absence of public funding, the development of a network of modellers is of huge value in enhancing transparency, whether through registries or other means.

[1]  William Herrington,et al.  A policy model of cardiovascular disease in moderate-to-advanced chronic kidney disease , 2017, Heart.

[2]  Ping Zhang,et al.  Computer modeling of diabetes and its complications: a report on the Fifth Mount Hood challenge meeting. , 2007, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[3]  Douglas K Owens,et al.  Future Directions for Cost-effectiveness Analyses in Health and Medicine , 2018, Medical decision making : an international journal of the Society for Medical Decision Making.

[4]  John Brazier,et al.  Development of the Scharr HUD (Health Utilities Database) , 2013 .

[5]  R. R. Holman,et al.  UKPDS Outcomes Model 2: a new version of a model to simulate lifetime health outcomes of patients with type 2 diabetes mellitus using data from the 30 year United Kingdom Prospective Diabetes Study: UKPDS 82 , 2013, Diabetologia.

[6]  John Hornberger Computer modeling of diabetes and its complications: a report on the fifth mount hood challenge meeting. , 2013, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[7]  A J Palmer,et al.  The Mt. Hood challenge: cross-testing two diabetes simulation models. , 2000, Diabetes research and clinical practice.

[8]  Joshua T. Cohen,et al.  30 Years of Pharmaceutical Cost-Utility Analyses , 2012, PharmacoEconomics.

[9]  Helen Dakin,et al.  Review of studies mapping from quality of life or clinical measures to EQ-5D: an online database , 2013, Health and Quality of Life Outcomes.

[10]  Alan Brennan,et al.  Computer Modeling of Diabetes and Its Transparency: A Report on the Eighth Mount Hood Challenge , 2018, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[11]  Christopher James Sampson,et al.  Model Registration: A Call to Action , 2017, PharmacoEconomics - Open.

[12]  Joshua T. Cohen,et al.  Can Economic Model Transparency Improve Provider Interpretation of Cost-Effectiveness Analysis? A Response. , 2017, Medical care.

[13]  Ben Goldacre The WHO joint statement from funders on trials transparency , 2017, British Medical Journal.

[14]  Dr David M. Eddy Accuracy versus Transparency in Pharmacoeconomic Modelling , 2012, PharmacoEconomics.

[15]  Kay Dickersin,et al.  The evolution of trial registries and their use to assess the clinical trial enterprise. , 2012, JAMA.

[16]  P. Easterbrook,et al.  Publication bias in clinical research , 1991, The Lancet.

[17]  Mick Watson When will ‘open science’ become simply ‘science’? , 2015, Genome Biology.

[18]  Julia Earnshaw,et al.  NICE Guide to the Methods of Technology Appraisal , 2012, PharmacoEconomics.

[19]  J. Caro,et al.  Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--7. , 2012, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[20]  M J Buxton,et al.  Modelling in economic evaluation: an unavoidable fact of life. , 1997, Health economics.

[21]  Sean Ekins,et al.  Ahead of Our Time: Collaboration in Modeling Then and Now , 2017, PharmacoEconomics.

[22]  S. Goodacre,et al.  Being economical with the truth: how to make your idea appear cost effective , 2002, Emergency medicine journal : EMJ.

[23]  John P. A. Ioannidis,et al.  Why Most Clinical Research Is Not Useful , 2016, PLoS medicine.

[24]  P. Vemer,et al.  AdViSHE: A Validation-Assessment Tool of Health-Economic Models for Decision Makers and Model Users , 2015, PharmacoEconomics.

[25]  David M Eddy,et al.  Accuracy versus transparency in pharmacoeconomic modelling: finding the right balance. , 2006, PharmacoEconomics.

[26]  Fiona Godlee,et al.  All trials must be registered and the results published , 2013, BMJ.

[27]  Dyfrig A Hughes,et al.  Development of a database of instruments for resource-use measurement: purpose, feasibility, and design. , 2012, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[28]  Maiwenn J Al,et al.  Improving model validation in health technology assessment: comments on guidelines of the ISPOR-SMDM modeling good research practices task force. , 2013, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[29]  Reiner Leidl,et al.  External Validation of Health Economic Decision Models for Chronic Obstructive Pulmonary Disease (COPD): Report of the Third COPD Modeling Meeting. , 2017, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[30]  Nicholas C. Ide,et al.  Trial Registration at ClinicalTrials.gov between May and October 2005. , 2005, The New England journal of medicine.

[31]  David Moher,et al.  Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement , 2013, International Journal of Technology Assessment in Health Care.

[32]  John Hornberger,et al.  Computer Modeling of Diabetes and Its Complications , 2007, Diabetes Care.

[33]  Iris Lansdorp-Vogelaar,et al.  A Systematic Comparison of Microsimulation Models of Colorectal Cancer , 2011, Medical decision making : an international journal of the Society for Medical Decision Making.

[34]  Yaling Yang,et al.  Review and critical appraisal of studies mapping from quality of life or clinical measures to EQ-5D: an online database and application of the MAPS statement , 2018, Health and Quality of Life Outcomes.

[35]  Alan Brennan,et al.  Computer Modeling of Diabetes and Its Complications , 2007, Diabetes Care.

[36]  Sean Ekins,et al.  Time for Cooperation in Health Economics among the Modelling Community , 2012, PharmacoEconomics.

[37]  Philip M Clarke,et al.  Development of life-expectancy tables for people with type 2 diabetes. , 2009, European heart journal.