Evidence map›Paper›PMID 36937042›Full record

ArticleFrontiers in global women's health2023

Does

Elena Keller, Willings Botha, Georgina M Chambers

Full text read
In one paragraph

Article in Frontiers in global women's health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Is next generation sequencing for the diagnosis of rare diseases worth its cost? A user-based approach to valuation.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. 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

3 authors.

Elena KellerCentre for Big Data Research in Health & National Perinatal Epidemiology and Statistics Unit, UNSW Sydney, Sydney, NSW, Australia.
Willings BothaCentre for Big Data Research in Health & National Perinatal Epidemiology and Statistics Unit, UNSW Sydney, Sydney, NSW, Australia.
Georgina M ChambersCentre for Big Data Research in Health & National Perinatal Epidemiology and Statistics Unit, UNSW Sydney, Sydney, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Using traditional health technology assessment (HTA) outcome metrics, such as quality-adjusted life-years, to assess fertility treatments raises considerable methodological challenges because the objective of fertility treatments is to create new life rather than extend, save, or improve health-related quality of life. Objective: The aim of this study was to develop a novel cost-benefit framework to assess value for money of publicly funded IVF treatment; to determine the number of cost-beneficial treatment cycles for women of different ages; and to perform an incremental cost-benefit analysis from a taxpayer perspective. Methods: We developed a Markov model to determine the net monetary benefit (NMB) of IVF treatment by female age and number of cycles performed. IVF treatment outcomes were monetized using taxpayers' willingness-to-pay values derived from a discrete choice experiment (DCE). Using the current funding environment as the comparator, we performed an incremental analysis of only funding cost-beneficial cycles. Similar outputs to cost-effectiveness analyses were generated, including net-benefit acceptability curves and cost-benefit planes. We created an interactive online app to provide a detailed and transparent presentation of the results. Results: The results suggest that at least five publicly funded IVF cycles are cost-beneficial in women aged <42 years. Cost-benefit planes suggest a strong taxpayer preference for restricting funding to cost-beneficial cycles over current funding arrangements in Australia from an economic perspective. Conclusions: The provision of fertility treatment is valued highly by taxpayers. This novel cost-benefit method overcomes several challenges of conventional cost-effectiveness methods and provides an exemplar for incorporating DCE results into HTA. The results offer new evidence to inform discussions about treatment funding arrangements.

Indexed as

cost-benefit analysis (CBA)discrete choice experiment (DCE)health technology assessment (HTA)IVF treatmentMarkov modelvalue of a statistical baby (VSB)willingness-to-pay (WTP)

Identifiers

PMID36937042
PMCPMC10014591

What OpenQuestion holds

Textfull text, public
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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.