Evidence map›Paper›PMID 10178653›Full record

ArticlePharmacoEconomics1998

The role of cost-consequence analysis in healthcare decision-making.

J A Mauskopf, J E Paul, D M Grant, A Stergachis

Abstract read
PubMed Publisher
In one paragraph

Article in PharmacoEconomics, 1998. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 2 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

88 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  17. A cost consequence study of the impact of a dermatology-trained practice nurse on the quality of life of primary care patients with eczema and psoriasis.The British journal of general practice : the journal of the Royal College of General Practitioners · 2000
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28 more citing papers are in PubMed but not listed here.

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

4 authors.

J A MauskopfResearch Triangle Institute, Research Triangle Park, North Carolina, USA. JOM@RTI.ORG
J E Paul
D M Grant
A Stergachis

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A greater understanding of value associated with new pharmaceutical products should lead to better decision-making. Most commonly cost-effectiveness ratios (CERs) are used to indicate value; however, researchers have recently shown that CER estimates are rarely used by decision-makers in making formulary decisions. In this article, a cost-consequence approach to estimating the value for money of a new treatment for a specific disease is described. Using a cost-consequence approach, the impact of the new treatment on lifetime resource use and costs (including specific healthcare service use and costs, and productivity losses) and health outcomes (including disease symptoms, life expectancy and quality of life) for an individual or group of individuals is estimated and presented in a tabular format. The cost-consequence format is more likely to be approachable, readily understandable and applied by healthcare decision-makers than a simple CER. The decision-maker may use selected items from the cost-consequence analysis to compute composite measures of drug value, such as cost per life-year gained or cost per quality-adjusted life-year (QALY) gained. In general, the cost-consequence approach, by making the impact of the new treatment as comprehensive and transparent as possible, will enable decision-makers to select the components most relevant to their perspective and will also give them confidence that the data are credible to use as the basis for resource allocation decisions.

Indexed as

Cost-Benefit AnalysisDecision MakingDelivery of Health CareHumans

Identifiers

PMID10178653

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.