Evidence map›Paper›PMID 24551324›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2013

Assessing the performance of LOINC® and RadLex for coverage of CT scans across three sites in a health information exchange.

Anton Oscar Beitia, Gilad Kuperman, Bradley N Delman, Jason S Shapiro

Abstract readEvaluation Study
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  9. Knowledge Translation and Barriers to Imaging Optimization in the Emergency Department: A Research Agenda.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2015
    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

4 authors.

Anton Oscar BeitiaDepartment of Radiology, Wyckoff Heights Medical Center, Brooklyn, NY.
Gilad KupermanDepartment of Biomedical Informatics, Columbia University, New York, NY. ; New York Presbyterian Hospital, New York, NY.
Bradley N DelmanDepartment of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY.
Jason S ShapiroDepartment of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We evaluated the performance of LOINC® and RadLex standard terminologies for covering CT test names from three sites in a health information exchange (HIE) with the eventual goal of building an HIE-based clinical decision support system to alert providers of prior duplicate CTs. Given the goal, the most important parameter to assess was coverage for high frequency exams that were most likely to be repeated. We showed that both LOINC® and RadLex provided sufficient coverage for our use case through calculations of (a) high coverage of 90% and 94%, respectively for the subset of CTs accounting for 99% of exams performed and (b) high concept token coverage (total percentage of exams performed that map to terminologies) of 92% and 95%, respectively. With trends toward greater interoperability, this work may provide a framework for those wishing to map radiology site codes to a standard nomenclature for purposes of tracking resource utilization.

Indexed as

Health Information SystemsLogical Observation Identifiers Names and CodesTomography, X-Ray ComputedVocabulary, ControlledClinical CodingElectronic Health RecordsHealth Information ManagementHumansInformation DisseminationMedical Record LinkageRadiology

Identifiers

PMID24551324
PMCPMC3900124

What OpenQuestion holds

Textmetadata
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.