Evidence map›Paper›PMID 10977387›Full record

ReviewPharmacoEconomics2000

Modelling in health economic evaluation. What is its place? What is its value?

A Brennan, R Akehurst

Abstract readReview
PubMed Publisher
In one paragraph

Review in PharmacoEconomics, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 5 pooled it
–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

57 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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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

2 authors.

A BrennanSchool of Health and Related Research (ScHARR), University of Sheffield, England. a.brennan@sheffield.ac.uk
R Akehurst

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper itemizes the current and developing roles of modelling in health economic evaluation and discusses its value in each role. We begin by noting the emptiness of the dichotomy that some commentators have sought to create between modelling and controlled trials as mechanisms for informing decisions. Both are necessary parts of the armoury. Recent literature discussions are examined and the accelerating prevalence of modelling is reported. The identified roles include: extrapolating outcomes to the longer term; adjusting for prognostic factors in trials; translating from intermediate to final outcomes; extending analysis to the relevant comparators; generalizing from specific trial populations to the full target group for an intervention and to other settings and countries; systematic sensitivity analyses; and the use of modelling for the design and prioritization of future trials. Roles are illustrated with 20 recent examples, mostly from within our own work analysing new or contentious interventions for the Trent Development and Evaluation Committee, which is planned to be incorporated into the UK National Institute for Clinical Excellence (NICE). Each role discussed has been essential at some point in this policy-making forum. Finally, the importance of quality assurance, critical review and validity testing is reiterated and there are some observations on processes to ensure probity and quality.

Indexed as

Biomedical TechnologyModels, EconomicHumans

Identifiers

PMID10977387

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.