Evidence map›Paper›PMID 31146771›Full record

ArticleJournal of biomedical semantics2019

Ontology-based specification and generation of search queries for post-market surveillance.

Alexandr Uciteli, Stefan Kropf, Timo Weiland, Stefanie Meese, Klaus Graef, Sabrina Rohrer, Marc O Schurr, Wolfram Bartussek, Christoph Goller, Philipp Blohm and 8 more

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. 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

18 authors.

Alexandr UciteliInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany. auciteli@imise.uni-leipzig.de.
Stefan KropfInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany. stefan.kropf@imise.uni-leipzig.de.
Timo Weilandnovineon Healthcare Technology Partners GmbH, Tübingen, Germany.
Stefanie Meesenovineon Healthcare Technology Partners GmbH, Tübingen, Germany.
Klaus Graefnovineon Healthcare Technology Partners GmbH, Tübingen, Germany.
Sabrina Rohrernovineon Healthcare Technology Partners GmbH, Tübingen, Germany.
Marc O Schurrnovineon Healthcare Technology Partners GmbH, Tübingen, Germany.
Wolfram BartussekOntoPort UG, Sulzbach, Germany.
Christoph GollerIntraFind Software AG, München, Germany.
Philipp BlohmIntraFind Software AG, München, Germany.
Robin SeidelFederal Institute for Drugs and Medical Devices (BfArM), Bonn, Germany.
Christian BayerFederal Institute for Drugs and Medical Devices (BfArM), Bonn, Germany.
Manuel KernenbachFederal Institute for Drugs and Medical Devices (BfArM), Bonn, Germany.
Kathrin PfeifferFederal Institute for Drugs and Medical Devices (BfArM), Bonn, Germany.
Wolfgang LauerFederal Institute for Drugs and Medical Devices (BfArM), Bonn, Germany.
Jörg-Uwe MeyerMT2IT GmbH & Co. KG, Ratzeburg, Germany.
Michael WitteMT2IT GmbH & Co. KG, Ratzeburg, Germany.
Heinrich HerreInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany. heinrich.herre@imise.uni-leipzig.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe vigilant observation of medical devices during post-market surveillance (PMS) for identifying safety-relevant incidents is a non-trivial task. A wide range of sources has to be monitored in order to integrate all accessible data about the safety and performance of a medical device. PMS needs to be supported by an efficient search strategy and the possibility to create complex search queries by domain experts.

resultsWe use ontologies to support the specification of search queries and the preparation of the document corpus, which contains all relevant documents. In this paper, we present (1) the Search Ontology (SON) v2.0, (2) an Excel template for specifying search queries, and (3) the Search Ontology Generator (SONG), which generates complex queries out of the Excel template. Based on our approach, a service-oriented architecture was designed, which supports and assists domain experts during PMS. Comprehensive testing confirmed the correct execution of all SONG functions. The applicability of our method and of the developed tools was evaluated by domain experts. The test persons concordantly rated our solution after a short period of training as highly user-friendly, intuitive and well applicable for supporting PMS.

conclusionsThe Search Ontology is a promising domain-independent approach to specify complex search queries. Our solution allows advanced searches for relevant documents in different domains using suitable domain ontologies.

Indexed as

Biological OntologiesProduct Surveillance, PostmarketingData MiningEquipment and SuppliesSafetyInformation retrievalOntologyOntology generationPost-market surveillanceSearch queriesSpreadsheet-based ontology specification

Identifiers

PMID31146771
PMCPMC6543572

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.