Evidence map›Paper›PMID 16942120›Full record

ArticlePharmacoEconomics2006

The value of thinly spread QALYs.

Duncan Mortimer

Abstract read
PubMed Publisher
In one paragraph

Article in PharmacoEconomics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Willingness to pay for a quality-adjusted life year: a systematic review with meta-regression.The European journal of health economics : HEPAC : health economics in prevention and care · 2022
    Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
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, Clayton, Victoria, Australia. duncan.mortimer@buseco.monash.edu.au

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A number of recent findings from the literature imply that the value of a QALY varies depending on the concentration or dispersion of that QALY over treated individuals. Given that funding decisions are currently made under either the assumption of distributive-neutrality or some combination of explicit decision criteria and implicit adjustment for distributional concerns, it is likely that substantial social welfare gains are available if distributional objectives could be more accurately reflected in funding decisions. This paper considers three alternative approaches to explicitly adjust for distributional concerns with regard to the concentration or dispersion of individual health gains. Including non-health arguments in the objective function by 'weighting' QALYs for distributional effects or imposing differential funding thresholds for interventions with different distributional effects might be considered first- and second-best solutions, and would likely deliver the greatest social welfare gains. However, there is some doubt that first- or second-best solutions would be: (i) feasible given current data gaps; and (ii) politically acceptable. Rather, a simple and transparent approach is suggested wherein the sponsors of interventions that deliver health gains that are of questionable 'welfare-significance' for the treated individual would be required to provide decision-makers with an estimate of willingness to pay for the QALYs in question and would only be eligible for funding in the event that the positive net present value criterion is met.

Indexed as

Economics, PharmaceuticalQuality-Adjusted Life YearsHealth Care RationingHealth PolicyHumansSocial Welfare

Identifiers

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.