Literature DB >> 19014201

Modelling downstream effects in the presence of technological change.

Duncan Mortimer1.   

Abstract

Downstream effects are typically evaluated given current technology and current practice patterns rather than for technology and practice patterns that will be available at the time when downstream effects accrue. Where a relatively short time horizon can be expected to capture all relevant costs and effects, the current approach is unlikely to introduce substantial error into estimates of the costs and benefits attributed to an intervention; the estimates will remain valid so long as the context to which estimates relate remains unchanged. However, for longer time horizons, the magnitude of error associated with the current approach might be substantial. This paper describes three strategies for incorporating uncertainty associated with technological change into modeled economic evaluations: (i) discounting; (ii) within-trial analysis; and (iii) threshold/sensitivity analysis with horizon scanning. The appropriateness of each strategy for handling uncertainty associated with technological change is then considered under various possible situations defined over the characteristics of technological change (pace and whether technological change produces interventions that are dominant, cost increasing or cost saving) and the characteristics of downstream effects (proximity and the sensitivity of policy recommendations to their inclusion/exclusion). Selecting the appropriate strategy (or strategies) for the situation should permit estimation of more realistic upper and lower bounds around base-case estimates.

Mesh:

Year:  2008        PMID: 19014201     DOI: 10.2165/0019053-200826120-00003

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


  15 in total

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Journal:  J Public Health Med       Date:  1992-09

Review 2.  Taking account of future technology in cost effectiveness analysis.

Authors:  Joshua A Salomon; Milton C Weinstein; Sue J Goldie
Journal:  BMJ       Date:  2004-09-25

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Authors:  M C Weinstein
Journal:  Int J Technol Assess Health Care       Date:  1990       Impact factor: 2.188

4.  The value of medical spending in the United States, 1960-2000.

Authors:  David M Cutler; Allison B Rosen; Sandeep Vijan
Journal:  N Engl J Med       Date:  2006-08-31       Impact factor: 91.245

5.  Discounting costs and effects: a reconsideration.

Authors:  B A van Hout
Journal:  Health Econ       Date:  1998-11       Impact factor: 3.046

6.  Modelling in economic evaluation: an unavoidable fact of life.

Authors:  M J Buxton; M F Drummond; B A Van Hout; R L Prince; T A Sheldon; T Szucs; M Vray
Journal:  Health Econ       Date:  1997 May-Jun       Impact factor: 3.046

7.  Cost-effectiveness of cardiac resynchronization therapy: results from the CARE-HF trial.

Authors:  Melanie J Calvert; Nick Freemantle; Guiqing Yao; John G F Cleland; Lucinda Billingham; Jean-Claude Daubert; Stirling Bryan
Journal:  Eur Heart J       Date:  2005-11-11       Impact factor: 29.983

8.  Cost effectiveness of thrombolytic therapy with tissue plasminogen activator as compared with streptokinase for acute myocardial infarction.

Authors:  D B Mark; M A Hlatky; R M Califf; C D Naylor; K L Lee; P W Armstrong; G Barbash; H White; M L Simoons; C L Nelson
Journal:  N Engl J Med       Date:  1995-05-25       Impact factor: 91.245

9.  Whither trial-based economic evaluation for health care decision making?

Authors:  Mark J Sculpher; Karl Claxton; Mike Drummond; Chris McCabe
Journal:  Health Econ       Date:  2006-07       Impact factor: 3.046

10.  Generalized cost-effectiveness analysis for national-level priority-setting in the health sector.

Authors:  Raymond Hutubessy; Dan Chisholm; Tessa Tan-Torres Edejer
Journal:  Cost Eff Resour Alloc       Date:  2003-12-19
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