Evidence map›Paper›PMID 30832727›Full record

ArticleJournal of biomedical semantics2019

Seeing the whole picture: integrated pre-surgery reports with PreOptique.

Guillermo Vega-Gorgojo, Laura Slaughter, Martin Giese

Abstract read
In one paragraph

Article in Journal of biomedical semantics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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.

Guillermo Vega-GorgojoDepartment of Informatics, University of Oslo, Oslo, Norway.
Laura SlaughterDepartment of Informatics, University of Oslo, Oslo, Norway.
Martin GieseDepartment of Informatics, University of Oslo, Oslo, Norway. martingi@ifi.uio.no.ORCID 0000-0002-2058-2728

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInformation technology has transformed the way healthcare is conducted. There is a deluge of patient data dispersed in different systems that are commonly not interoperable. As a result, access to patient data has become a major bottleneck for healthcare professionals that struggle to find the relevant information in a timely way and without missing critical clinical information.

resultsWe implemented PreOptique, a novel hybrid semantic and text-based system that was commissioned by a large hospital in Norway for providing integrated access to patient health records scattered over several databases and document repositories. We use ontology-based data access (OBDA) for the seamless integration of the structured databases at the hospital through the Optique platform. We employ text analysis techniques to extract vital sign measures and clinical findings from patient documents. PreOptique was developed and deployed at the hospital. This solution demonstrates how OBDA technology can provide integrated data access to disparate structured sources in healthcare, without requiring the replacement of existing databases. Unstructured clinical texts are also mined to extract patient findings, while the graphical user interface (GUI) provides a single access point that hides the underlying complexity of the system. We ran a usability study with 5 target users, obtaining a system usability score (SUS) of 86.0. Further, participants in the study stressed the simplicity of the GUI and the integration of data sources enabled by the system.

conclusionsThis pilot study showcases the use of OBDA technology and text analysis to enable the integration of patient data for supporting clinical surgery operations. PreOptique is usable and can be easily employed by medical personnel to find patient data in a timely way.

Indexed as

SemanticsSurgical Procedures, OperativeElectronic Health RecordsHumansSoftwareBiological ontologiesElectronic health recordsOntology-based data accessSystems integrationText analysis

Identifiers

PMID30832727
PMCPMC6398264

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.