Evidence map›Paper›PMID 11825289›Full record

ArticleProceedings. AMIA Symposium2001

Integrating existing drug formulation terminologies into an HL7 standard classification using OpenGALEN.

C J Wroe, J J Cimino, A L Rector

Abstract read
In one paragraph

Article in Proceedings. AMIA Symposium, 2001. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. NLP-based identification of pneumonia cases from free-text radiological reports.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2008
    Article
  5. 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.

C J WroeDepartment of Computer Science, University of Manchester, UK.
J J Cimino
A L Rector

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many terminologies exist for the form of drugs--i.e. tablets, capsules, sprays, suppositories, etc. However, they have surprisingly different content. To communicate medication messages effectively, a mechanism is needed to translate between these existing terminologies. An ontological approach, based on techniques developed by OpenGALEN, has been used to build a drug form terminology for HL7 version 3. It integrates existing terminologies from commercial drug information vendors and regulatory authorities, and provides a framework for translating between them. To date, term sets have been included from First DataBank, the FDA, Multum and Micromedex, to produce a terminology of 820 concepts. The approach is made practical by distributing the knowledge engineering effort to volunteers with experience of the domain, and then integrating the knowledge into a logically consistent classification.

Indexed as

Dosage FormsVocabulary, ControlledChemistry, PharmaceuticalTerminology as TopicDosage Forms

Identifiers

PMID11825289
PMCPMC2243292

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.