Evidence map›Paper›PMID 25954332›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2014

Analyzing U.S. prescription lists with RxNorm and the ATC/DDD Index.

Olivier Bodenreider, Laritza M Rodriguez

Abstract readEvaluation Study
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

2 authors.

Olivier BodenreiderLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD.
Laritza M RodriguezLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD.

Funding

National Biomedical Information ServicesZIHLM200888 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PALTOO, DINA · 2009 to 2025
$5200.7M
Using large Clinical Data bases to assess the association between patient factors, medication usage and patient outcomesZIALM008927 · NLM · NATIONAL LIBRARY OF MEDICINE · PI MCDONALD, CLEMENT · 2009 to 2015
$1.5M
Intramural NIH HHS
6 · The paper itself

Abstract

objectivesTo evaluate the suitability of the ATC/DDD Index (Anatomical Therapeutic Chemical (ATC) Classification System/Defined Daily Dose) for analyzing prescription lists in the U.S.

methodsWe mapped RxNorm clinical drugs to ATC. We used this mapping to classify a large set of prescription drugs with ATC and compared the prescribed daily dose to the defined daily dose (DDD) in ATC.

results64% of the 11,422 clinical drugs could be precisely mapped to ATC. 97% of the 87,001 RxNorm codes from the prescription dataset could be classified with ATC, and 97% of the prescribed daily doses could be assessed.

conclusionsAlthough the mapping of RxNorm ingredients to ATC appears to be largely incomplete, the most frequently prescribed drugs in the prescription dataset we analyzed were covered. This study demonstrates the feasibility of using ATC in conjunction with RxNorm for analyzing U.S. prescription datasets for drug classification and assessment of the prescribed daily doses.

Indexed as

RxNormTerminology as TopicClinical CodingPrescription DrugsUnited StatesPrescription Drugs

Identifiers

PMID25954332
PMCPMC4419961

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.