Literature DB >> 17640110

A stated preference binary choice experiment to explore NICE decision making.

Paul Tappenden1, John Brazier, Julie Ratcliffe, James Chilcott.   

Abstract

OBJECTIVE: To explore whether the National Institute for Health and Clinical Excellence (NICE) takes account of concerns other than just incremental cost effectiveness in commissioning healthcare services.
METHOD: A stated preference binary choice experiment was used to explore the preferences of members of NICE's Appraisal Committees for incremental cost effectiveness, the degree of uncertainty surrounding incremental costs and health outcomes, the age of beneficiaries, baseline health-related quality of life (HR-QOL) and the availability of alternative therapies when considering whether to recommend health technologies.
RESULTS: A logit modelling analysis of Committee members' stated preferences suggested that increases in the incremental cost-effectiveness ratio and economic uncertainty, and the availability of other therapies was associated with statistically significant reductions in the odds of a positive recommendation (p < 0.01). The transition from a very low to a comparatively high level of baseline HR-QOL was also associated with a statistically significant reduction in the odds of a positive recommendation (p = 0.003). The age of beneficiaries did not significantly affect decisions concerning whether to recommend technologies.
CONCLUSION: The results of the choice experiment support the notion of a probabilistic adoption/rejection approach rather than the operation of a single cost-effectiveness threshold.

Entities:  

Mesh:

Year:  2007        PMID: 17640110     DOI: 10.2165/00019053-200725080-00006

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


  9 in total

1.  Using discrete choice modelling in priority setting: an application to clinical service developments.

Authors:  S Farrar; M Ryan; D Ross; A Ludbrook
Journal:  Soc Sci Med       Date:  2000-01       Impact factor: 4.634

2.  The failings of NICE.

Authors:  R Smith
Journal:  BMJ       Date:  2000-12-02

3.  WHO evaluates NICE.

Authors:  Nancy Devlin; David Parkin; Marthe Gold
Journal:  BMJ       Date:  2003-11-08

4.  Does NICE have a cost-effectiveness threshold and what other factors influence its decisions? A binary choice analysis.

Authors:  Nancy Devlin; David Parkin
Journal:  Health Econ       Date:  2004-05       Impact factor: 3.046

5.  National Institute for Clinical Excellence and its value judgments.

Authors:  Michael D Rawlins; Anthony J Culyer
Journal:  BMJ       Date:  2004-07-24

6.  Seeing the NICE side of cost-effectiveness analysis: a qualitative investigation of the use of CEA in NICE technology appraisals.

Authors:  Stirling Bryan; Iestyn Williams; Shirley McIver
Journal:  Health Econ       Date:  2007-02       Impact factor: 3.046

7.  A rational framework for decision making by the National Institute For Clinical Excellence (NICE).

Authors:  Karl Claxton; Mark Sculpher; Michael Drummond
Journal:  Lancet       Date:  2002-08-31       Impact factor: 79.321

8.  Bentham in a box: technology assessment and health care allocation.

Authors:  A R Jonsen
Journal:  Law Med Health Care       Date:  1986-09

9.  Eliciting stated preferences for health-technology adoption criteria using paired comparisons and recommendation judgments.

Authors:  F Reed Johnson; Martin Backhouse
Journal:  Value Health       Date:  2006 Sep-Oct       Impact factor: 5.725

  9 in total
  11 in total

1.  Reimbursement decisions of the All Wales Medicines Strategy Group: influence of policy and clinical and economic factors.

Authors:  Warren G Linley; Dyfrig A Hughes
Journal:  Pharmacoeconomics       Date:  2012-09-01       Impact factor: 4.981

2.  What Can We Expect from Value-Based Funding of Medicines? A Retrospective Study.

Authors:  Anthony Harris; Jing Jing Li; Karen Yong
Journal:  Pharmacoeconomics       Date:  2016-04       Impact factor: 4.981

3.  Revealed and Stated Preferences of Decision Makers for Priority Setting in Health Technology Assessment: A Systematic Review.

Authors:  Peter Ghijben; Yuanyuan Gu; Emily Lancsar; Silva Zavarsek
Journal:  Pharmacoeconomics       Date:  2018-03       Impact factor: 4.981

4.  Combining multicriteria decision analysis, ethics and health technology assessment: applying the EVIDEM decision-making framework to growth hormone for Turner syndrome patients.

Authors:  Mireille M Goetghebeur; Monika Wagner; Hanane Khoury; Donna Rindress; Jean-Pierre Grégoire; Cheri Deal
Journal:  Cost Eff Resour Alloc       Date:  2010-04-08

5.  Decision-makers' preferences for approving new medicines in Wales: a discrete-choice experiment with assessment of external validity.

Authors:  Warren G Linley; Dyfrig A Hughes
Journal:  Pharmacoeconomics       Date:  2013-04       Impact factor: 4.981

6.  Using a discrete choice experiment to elicit time trade-off and willingness-to-pay amounts for influenza health-related quality of life at different ages.

Authors:  Lisa A Prosser; Katherine Payne; Donna Rusinak; Ping Shi; Mark Messonnier
Journal:  Pharmacoeconomics       Date:  2013-04       Impact factor: 4.981

7.  A think aloud study comparing the validity and acceptability of discrete choice and best worst scaling methods.

Authors:  Jennifer A Whitty; Ruth Walker; Xanthe Golenko; Julie Ratcliffe
Journal:  PLoS One       Date:  2014-04-23       Impact factor: 3.240

8.  Do different clinical evidence bases lead to discordant health-technology assessment decisions? An in-depth case series across three jurisdictions.

Authors:  Daryl S Spinner; Julie Birt; Jeffrey W Walter; Lee Bowman; Josephine Mauskopf; Michael F Drummond; Catherine Copley-Merriman
Journal:  Clinicoecon Outcomes Res       Date:  2013-01-30

Review 9.  Evidence and Value: Impact on DEcisionMaking--the EVIDEM framework and potential applications.

Authors:  Mireille M Goetghebeur; Monika Wagner; Hanane Khoury; Randy J Levitt; Lonny J Erickson; Donna Rindress
Journal:  BMC Health Serv Res       Date:  2008-12-22       Impact factor: 2.655

10.  Prioritising health service innovation investments using public preferences: a discrete choice experiment.

Authors:  Seda Erdem; Carl Thompson
Journal:  BMC Health Serv Res       Date:  2014-08-28       Impact factor: 2.655

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.