Evidence map›Paper›PMID 39268199›Full record

ArticleArchives of pediatrics (Lisle, IL)2024

The "Other E" in ELSI: The Use of Economic Evaluation to Inform the Expansion of Newborn Screening.

Kee Chan, Amy Brower, Theodore G Ganiats

Abstract read
In one paragraph

Article in Archives of pediatrics (Lisle, IL), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Kee ChanValueMinded LLC, Milwaukee, Wisconsin, USA.
Amy BrowerAmerican College of Medical Genetics and Genomics, Bethesda, Maryland, USA.
Theodore G GaniatsUniversity of California, San Diego, La Jolla, California, USA.

Funding

NICHD NIH HHS HHSN275201800005C
6 · The paper itself

Abstract

The utilization and application of genomic information generated from precision medicine continues to increase with the goal of improving health outcomes. Increasingly researchers, health care professionals, and public health teams include an examination of the ethical, legal, and social issues (ELSI) in their consideration of the use of precision medicine for newborn and pediatric health. In addition to ELSI considerations, stakeholders could benefit from an understanding of economics, the other "E" in ELSI. The use of an economic evaluation could aid decision-making on whether to screen newborns who may be at risk for disease, to diagnose newborns and children who present with symptoms, to inform the treatment and management of diagnosed individuals. In this manuscript we review the core concepts of economic evaluation, the framework of decision-analysis, and key parameters for consideration in assessing the economics of NBS program(s). We describe the common language used in the economic evaluation and provide a practical overview of health economic evaluations including 1) their purpose, 2) different types and components, 3) evaluation of the different types and components of economic evaluations (i.e., cost-effectiveness vs. cost-benefit analysis), 4) impact of societal or healthcare perspectives on the analysis, 5) health outcomes, 6) time horizon for the analysis, 7) identification of appropriate comparators, and 8) resources for economic data. We conclude with a use case to demonstrate the application and understanding of economic considerations for in the advancement and expansion of NBS.

Indexed as

Cost-benefit AnalysisCost-effectivenessCost-utility AnalysisEconomic EvaluationGenomicsNewborn Screening (NBS)Public Health EconomicsSequencing

Identifiers

PMID39268199
PMCPMC11392499

What OpenQuestion holds

Textmetadata
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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.