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Modelling Downstream Effects in the Presence of Technological Change

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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.

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Notes

  1. A DMUC implies that increments in the consumption of our relatively wealthy future selves have a lower value than increments in present consumption. Where economic growth is a function of technological advance, the hypothesized decline in the marginal utility of future consumption will also vary in line with technological advance. However, there are many who have questioned the existence of a diminishing marginal utility for future lives or life-years.[10,20]

  2. Where funds available for current programmes might instead be invested to obtain increased funding for future programmes, an argument can be made for ‘induced’ discounting at the MIRR in the next best alternative programme.[19,21] Because the MIRR is a function of the production technology available, the appropriate discount rate will vary in line with technological advance. However, a number of counter arguments have been forwarded in the literature against this type of ‘induced’ discounting.[9,18]

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Acknowledgements

The research reported in this paper was supported by the Centre for Health Economics at Monash University. Funding for this paper was not contingent on approval of the final manuscript. The author had sole discretion over the design and conduct of the research. The views expressed herein are the sole responsibility of the author. The author has no conflicts of interest that are directly relevant to the content of this article.

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  1. Centre for Health Economics, Faculty of Business & Economics, Monash University, Melbourne, Victoria, Australia

    Duncan Mortimer

  2. Division of Health Sciences, University of South Australia, Adelaide, South Australia, Australia

    Duncan Mortimer

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Correspondence to Duncan Mortimer.

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Mortimer, D. Modelling Downstream Effects in the Presence of Technological Change. Pharmacoeconomics 26, 991–1003 (2008). https://doi.org/10.2165/0019053-200826120-00003

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