Evidence map›Paper›PMID 39075459›Full record

ArticleBMC medical informatics and decision making2024

Creating a health informatics data resource for hearing health research.

Nishchay Mehta, Baptiste Briot Ribeyre, Lilia Dimitrov, Louise J English, Colleen Ewart, Antje Heinrich, Nikhil Joshi, Kevin J Munro, Gail Roadknight, Luis Romao and 5 more

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Article in BMC medical informatics and decision making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Nishchay MehtaNIHR University College London Hospitals Biomedical Research Centre, London, UK.
Baptiste Briot RibeyreNIHR University College London Hospitals Biomedical Research Centre, London, UK.
Lilia DimitrovNIHR University College London Hospitals Biomedical Research Centre, London, UK.
Louise J EnglishNIHR University College London Hospitals Biomedical Research Centre, London, UK.
Colleen EwartNIHR Health Informatics Collaborative Hearing Health, Patient and Public Engagement Group, London, UK.
Antje HeinrichNIHR Manchester Biomedical Research Centre, Manchester, UK.
Nikhil JoshiNIHR University College London Hospitals Biomedical Research Centre, London, UK.
Kevin J MunroNIHR Manchester Biomedical Research Centre, Manchester, UK.
Gail RoadknightOxford University Hospitals NHS Foundation Trust: Oxford, Oxfordshire, UK.
Luis RomaoNIHR University College London Hospitals Biomedical Research Centre, London, UK.
Anne Gm SchilderNIHR University College London Hospitals Biomedical Research Centre, London, UK.
Ruth V SpriggsNIHR Biomedical Research Centre, School of Medicine, University of Nottingham, Nottingham, UK.
Ruth NorrisNIHR Manchester Biomedical Research Centre, Manchester, UK.
Talisa RossNIHR University College London Hospitals Biomedical Research Centre, London, UK. Talisaross@doctors.org.uk.
George TilstonNIHR Manchester Biomedical Research Centre, Manchester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe National Institute of Health and Social Care Research (NIHR) Health Informatics Collaborative (HIC) for Hearing Health has been established in the UK to curate routinely collected hearing health data to address research questions. This study defines priority research areas, outlines its aims, governance structure and demonstrates how hearing health data have been integrated into a common data model using pure tone audiometry (PTA) as a case study.

methodsAfter identifying key research aims in hearing health, the governance structure for the NIHR HIC for Hearing Health is described. The Observational Medical Outcomes Partnership (OMOP) was chosen as our common data model to provide a case study example.

resultsThe NIHR HIC Hearing Health theme have developed a data architecture outlying the flow of data from all of the various siloed electronic patient record systems to allow the effective linkage of data from electronic patient record systems to research systems. Using PTAs as an example, OMOPification of hearing health data successfully collated a rich breadth of datapoints across multiple centres.

conclusionThis study identified priority research areas where routinely collected hearing health data could be useful. It demonstrates integration and standardisation of such data into a common data model from multiple centres. By describing the process of data sharing across the HIC, we hope to invite more centres to contribute and utilise data to address research questions in hearing health. This national initiative has the power to transform UK hearing research and hearing care using routinely collected clinical data.

Indexed as

Medical InformaticsAudiometry, Pure-ToneBiomedical ResearchElectronic Health RecordsHumansUnited KingdomDatabaseData sharingHearing health

Identifiers

PMID39075459
PMCPMC11285202

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LicenceCC BY-NC-ND
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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.