Evidence map›Paper›PMID 40854612›Full record

ArticleInternational journal of technology assessment in health care2025

IOATLAS: scanning across the medical horizon.

Hannah O'Keefe, Elizabeth Green, Anjum Jahan, Imogen Forsythe, Jane Nesworthy, Sonia Garcia Gonzalez-Moral

Abstract read
In one paragraph

Article in International journal of technology assessment in health care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Hannah O'KeefeNIHR Innovation Observatory, https://ror.org/01kj2bm70Newcastle University, Newcastle-upon-Tyne, UK.ORCID https://orcid.org/0000-0002-0107-711X
Elizabeth GreenNIHR Innovation Observatory, https://ror.org/01kj2bm70Newcastle University, Newcastle-upon-Tyne, UK.ORCID https://orcid.org/0009-0006-1092-6458
Anjum JahanNIHR Innovation Observatory, https://ror.org/01kj2bm70Newcastle University, Newcastle-upon-Tyne, UK.ORCID https://orcid.org/0009-0000-1718-7674
Imogen ForsytheNIHR Innovation Observatory, https://ror.org/01kj2bm70Newcastle University, Newcastle-upon-Tyne, UK.ORCID https://orcid.org/0009-0003-5607-2177
Jane NesworthyNIHR Innovation Observatory, https://ror.org/01kj2bm70Newcastle University, Newcastle-upon-Tyne, UK.ORCID https://orcid.org/0009-0008-8525-1357
Sonia Garcia Gonzalez-MoralNIHR Innovation Observatory, https://ror.org/01kj2bm70Newcastle University, Newcastle-upon-Tyne, UK.ORCID https://orcid.org/0000-0003-0431-4771

Funding

National Institute for Health and Care Research HSRIC-2016-10009/Innovation Observatory
6 · The paper itself

Abstract

introductionHorizon scanning (HS) is a methodology that aims to capture signals and trends that highlight future opportunities and challenges. The National Institute for Health and Care Research (NIHR) Innovation Observatory routinely scans for medical technologies and therapeutics to inform policy and practice for healthcare in the United Kingdom (UK). To date, there is no standardized terminology for horizon scanning in healthcare. Here, we discuss the development of a data glossary and the IOAtlas web app.

methodsWe extracted data points from 4 years' worth of NIHR Innovation Observatory HS projects and collated them by technology type and descriptive family. A source repository was established by extracting a list of all sources used in NIHR Innovation Observatory briefing notes between 2017 and 2021. The repository was validated by external HS organizations and experts, and sources were then mapped to the appropriate time horizons. The glossary and repository were converted to an SQLite database format and connected to a free web app, IOAtlas.

resultsAfter de-duplication and consolidation, a total of 148 data points were included in the glossary. The source repository consists of 149 sources, with 99 percent being compliant with searching for two or more technology types. The final SQLite database contained 35 tables with 36 relationships.

conclusionsWe present a data glossary to provide globalized standardization for the terminology used in HS projects. The glossary can be accessed through the IOAtlas web app. Furthermore, we provide users with an interface to generate downloadable data extraction templates within IOAtlas.

Indexed as

Technology Assessment, BiomedicalDatabases, FactualHumansTerminology as TopicUnited Kingdomforecastingforesight analysisglossaryhorizon scanningMedTechsoftwarestandardizationtherapeutics

Identifiers

PMID40854612
PMCPMC12450546

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.