Literature DB >> 23529209

Optimal global value of information trials: better aligning manufacturer and decision maker interests and enabling feasible risk sharing.

Simon Eckermann1, Andrew R Willan.   

Abstract

Risk sharing arrangements relate to adjusting payments for new health technologies given evidence of their performance over time. Such arrangements rely on prospective information regarding the incremental net benefit of the new technology, and its use in practice. However, once the new technology has been adopted in a particular jurisdiction, randomized clinical trials within that jurisdiction are likely to be infeasible and unethical in the cases where they would be most helpful, i.e. with current evidence of positive while uncertain incremental health and net monetary benefit. Informed patients in these cases would likely be reluctant to participate in a trial, preferring instead to receive the new technology with certainty. Consequently, informing risk sharing arrangements within a jurisdiction is problematic given the infeasibility of collecting prospective trial data. To overcome such problems, we demonstrate that global trials facilitate trialling post adoption, leading to more complete and robust risk sharing arrangements that mitigate the impact of costs of reversal on expected value of information in jurisdictions who adopt while a global trial is undertaken. More generally, optimally designed global trials offer distinct advantages over locally optimal solutions for decision makers and manufacturers alike: avoiding opportunity costs of delay in jurisdictions that adopt; overcoming barriers to evidence collection; and improving levels of expected implementation. Further, the greater strength and translatability of evidence across jurisdictions inherent in optimal global trial design reduces barriers to translation across jurisdictions characteristic of local trials. Consequently, efficiently designed global trials better align the interests of decision makers and manufacturers, increasing the feasibility of risk sharing and the expected strength of evidence over local trials, up until the point that current evidence is globally sufficient.

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Year:  2013        PMID: 23529209     DOI: 10.1007/s40273-013-0038-5

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


  19 in total

1.  Coverage options for promising technologies: Medicare's 'coverage with evidence development'.

Authors:  Sean R Tunis; Steven D Pearson
Journal:  Health Aff (Millwood)       Date:  2006 Sep-Oct       Impact factor: 6.301

2.  Expected value of information and decision making in HTA.

Authors:  Simon Eckermann; Andrew R Willan
Journal:  Health Econ       Date:  2007-02       Impact factor: 3.046

3.  Coverage with evidence development: an examination of conceptual and policy issues.

Authors:  John Hutton; Paul Trueman; Christopher Henshall
Journal:  Int J Technol Assess Health Care       Date:  2007       Impact factor: 2.188

4.  Optimal clinical trial design using value of information methods with imperfect implementation.

Authors:  Andrew R Willan; Simon Eckermann
Journal:  Health Econ       Date:  2010-05       Impact factor: 3.046

5.  Value of information and pricing new healthcare interventions.

Authors:  Andrew R Willan; Simon Eckermann
Journal:  Pharmacoeconomics       Date:  2012-06-01       Impact factor: 4.981

6.  Can't get no satisfaction? Will pay for performance help?: toward an economic framework for understanding performance-based risk-sharing agreements for innovative medical products.

Authors:  Adrian Towse; Louis P Garrison
Journal:  Pharmacoeconomics       Date:  2010       Impact factor: 4.981

7.  The option value of delay in health technology assessment.

Authors:  Simon Eckermann; Andrew R Willan
Journal:  Med Decis Making       Date:  2008-05-13       Impact factor: 2.583

8.  Presenting evidence and summary measures to best inform societal decisions when comparing multiple strategies.

Authors:  Simon Eckermann; Andrew R Willan
Journal:  Pharmacoeconomics       Date:  2011-07       Impact factor: 4.981

Review 9.  Economic evaluation of pharmaceuticals. Frankenstein's monster or vampire of trials?

Authors:  B O'Brien
Journal:  Med Care       Date:  1996-12       Impact factor: 2.983

10.  Time and expected value of sample information wait for no patient.

Authors:  Simon Eckermann; Andrew R Willan
Journal:  Value Health       Date:  2007-12-17       Impact factor: 5.725

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  3 in total

1.  Can the real opportunity cost stand up: displaced services, the straw man outside the room.

Authors:  Simon Eckermann; Brita Pekarsky
Journal:  Pharmacoeconomics       Date:  2014-04       Impact factor: 4.981

2.  Estimating the Expected Value of Sample Information Using the Probabilistic Sensitivity Analysis Sample: A Fast, Nonparametric Regression-Based Method.

Authors:  Mark Strong; Jeremy E Oakley; Alan Brennan; Penny Breeze
Journal:  Med Decis Making       Date:  2015-03-25       Impact factor: 2.583

3.  An Efficient Method for Computing Expected Value of Sample Information for Survival Data from an Ongoing Trial.

Authors:  Mathyn Vervaart; Mark Strong; Karl P Claxton; Nicky J Welton; Torbjørn Wisløff; Eline Aas
Journal:  Med Decis Making       Date:  2021-12-30       Impact factor: 2.749

  3 in total

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