Evidence map›Paper›PMID 19014201›Full record

ArticlePharmacoEconomics2008

Modelling downstream effects in the presence of technological change.

Duncan Mortimer

Abstract read
PubMed Publisher
In one paragraph

Article in PharmacoEconomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Duncan MortimerCentre for Health Economics, Faculty of Business & Economics, Monash University, Melbourne, Victoria, Australia. duncan.mortimer@unisa.edu.au

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Models, EconomicCost-Benefit AnalysisTechnologyUncertainty

Identifiers

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.