Literature DB >> 23877738

Navigating time and uncertainty in health technology appraisal: would a map help?

Christopher McCabe1, Richard Edlin, Peter Hall.   

Abstract

Healthcare systems are increasingly under pressure to provide funding for innovative technologies. These technologies tend to be characterized by their potential to make valued contributions to patient health in areas of relative unmet need, and have high acquisition costs and uncertainty within the evidence base on their actual impact on health. Decision makers are increasingly interested in linking reimbursement strategies to the degree of uncertainty in the evidence base and, as a result, reimbursement for innovative technologies is frequently linked to some form of patient access or risk-sharing scheme. As the dominant methods of economic evaluation report final outcomes only at the time horizon of the analysis, they present only aggregated information. This omits much of the information available on how net benefit is distributed within the time horizon. In this article, we introduce the Net Benefit Probability Map (NBPM), which maps net health benefit versus time to identify how certain decision makers can be about the benefit of technologies at multiple time points. Using an illustrative example, we show how the NBPM can inform decision makers about how long it will take for innovative technologies to 'pay off', how methodological choices on discount rates affect results and how alternative payment mechanisms can reduce the risk for decision makers facing innovative technologies.

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Year:  2013        PMID: 23877738     DOI: 10.1007/s40273-013-0077-y

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


  15 in total

1.  Analysis of uncertainty in health care cost-effectiveness studies: an introduction to statistical issues and methods.

Authors:  B J O'Brien; A H Briggs
Journal:  Stat Methods Med Res       Date:  2002-12       Impact factor: 3.021

2.  Expected net present value of sample information: from burden to investment.

Authors:  Peter S Hall; Richard Edlin; Samer Kharroubi; Walter Gregory; Christopher McCabe
Journal:  Med Decis Making       Date:  2012-04-30       Impact factor: 2.583

3.  Discounting and decision making in the economic evaluation of health-care technologies.

Authors:  Karl Claxton; Mike Paulden; Hugh Gravelle; Werner Brouwer; Anthony J Culyer
Journal:  Health Econ       Date:  2010-05-12       Impact factor: 3.046

4.  Need for differential discounting of costs and health effects in cost effectiveness analyses.

Authors:  Werner B F Brouwer; Louis W Niessen; Maarten J Postma; Frans F H Rutten
Journal:  BMJ       Date:  2005-08-20

5.  Value based pricing for NHS drugs: an opportunity not to be missed?

Authors:  Karl Claxton; Andrew Briggs; Martin J Buxton; Anthony J Culyer; Christopher McCabe; Simon Walker; Mark J Sculpher
Journal:  BMJ       Date:  2008-02-02

6.  Access with evidence development schemes: a framework for description and evaluation.

Authors:  Christopher J McCabe; Tania Stafinski; Richard Edlin; Devidas Menon
Journal:  Pharmacoeconomics       Date:  2010       Impact factor: 4.981

7.  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

8.  Net health benefits: a new framework for the analysis of uncertainty in cost-effectiveness analysis.

Authors:  A A Stinnett; J Mullahy
Journal:  Med Decis Making       Date:  1998 Apr-Jun       Impact factor: 2.583

9.  Costs, effects and C/E-ratios alongside a clinical trial.

Authors:  B A van Hout; M J Al; G S Gordon; F F Rutten
Journal:  Health Econ       Date:  1994 Sep-Oct       Impact factor: 3.046

10.  Updated cost-effectiveness analysis of trastuzumab for early breast cancer: a UK perspective considering duration of benefit, long-term toxicity and pattern of recurrence.

Authors:  Peter S Hall; Claire Hulme; Christopher McCabe; Yemi Oluboyede; Jeff Round; David A Cameron
Journal:  Pharmacoeconomics       Date:  2011-05       Impact factor: 4.981

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  6 in total

1.  Bayesian Hierarchical Models for Meta-Analysis of Quality-of-Life Outcomes: An Application in Multimorbidity.

Authors:  Susanne Schmitz; Tatjana T Makovski; Roisin Adams; Marjan van den Akker; Saverio Stranges; Maurice P Zeegers
Journal:  Pharmacoeconomics       Date:  2020-01       Impact factor: 4.981

2.  The 'Switch' study protocol: a randomised-controlled trial of switching to an alternative tumour-necrosis factor (TNF)-inhibitor drug or abatacept or rituximab in patients with rheumatoid arthritis who have failed an initial TNF-inhibitor drug.

Authors:  Nuria C Navarro Coy; Sarah Brown; Ailsa Bosworth; Claire T Davies; Paul Emery; Colin C Everett; Catherine Fernandez; Janine C Gray; Suzanne Hartley; Claire Hulme; Anne-Maree Keenan; Christopher McCabe; Anthony Redmond; Catherine Reynolds; David Scott; Linda D Sharples; Sue Pavitt; Maya H Buch
Journal:  BMC Musculoskelet Disord       Date:  2014-12-23       Impact factor: 2.362

3.  Dealing with Time in Health Economic Evaluation: Methodological Issues and Recommendations for Practice.

Authors:  James F O'Mahony; Anthony T Newall; Joost van Rosmalen
Journal:  Pharmacoeconomics       Date:  2015-12       Impact factor: 4.981

4.  Using the Payoff Time in Decision-Analytic Models: A Case Study for Using Statins in Primary Prevention.

Authors:  Alexander Thompson; Bruce Guthrie; Katherine Payne
Journal:  Med Decis Making       Date:  2017-04-25       Impact factor: 2.583

5.  The value of innovation under value-based pricing.

Authors:  Santiago G Moreno; Joshua A Ray
Journal:  J Mark Access Health Policy       Date:  2016-04-07

6.  Cost effectiveness and value of information analyses of islet cell transplantation in the management of 'unstable' type 1 diabetes mellitus.

Authors:  Klemens Wallner; A M James Shapiro; Peter A Senior; Christopher McCabe
Journal:  BMC Endocr Disord       Date:  2016-04-09       Impact factor: 2.763

  6 in total

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