Evidence map›Paper›PMID 25954414›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2014

Analysis of medication and indication occurrences in clinical notes.

Sunghwan Sohn, Hongfang Liu

Abstract read
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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Generalized Extraction and Classification of Span-Level Clinical Phrases.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018
    Article
  4. 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.

Sunghwan SohnDepartment of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN.
Hongfang LiuDepartment of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN.

Funding

Methods for generalized ontology terms enrichment analysisR01LM011369 · NLM · STANFORD UNIVERSITY · PI SHAH, NIGAM H · 2013 to 2020
$5.0M
Natural language processing for clinical and translational researchR01GM102282 · NIGMS · MAYO CLINIC ROCHESTER · PI LIU, HONGFANG, PAKHOMOV, SERGUEI VS · 2013 to 2016
$2.5M
NIGMS NIH HHS R01 GM102282NIGMS NIH HHS R01GM102282A1NLM NIH HHS R01 LM011369NLM NIH HHS R01LM011369
6 · The paper itself

Abstract

A medication indication is a valid reason to use medication. Comprehensive information on medication and its intended indications has valuable potential applications for patient treatments, quality improvements, and clinical decision support. Though there are some publicly available medication resources, this medication and indication information is comprised primarily of labeled uses approved by the FDA. Additionally, linking those medications and the corresponding indications is not easy to accomplish. Furthermore, research that analyzes actual medication and indication occurrences used in real clinical practice is limited. In this study, we compiled clinician-asserted medication and indication pairs from a large cohort of Mayo Clinic electronic medical records (EMRs) and normalized them to the standard forms (ie, medication to the RxNorm ingredient and indication to SNOMED-CT). We then analyzed medication and indication occurrences and compared them with the public resource in various ways, including off-label statistics.

Indexed as

Drug Therapy, Computer-AssistedElectronic Health RecordsRxNormHumansSystematized Nomenclature of MedicineUnified Medical Language System

Identifiers

PMID25954414
PMCPMC4419933

What OpenQuestion holds

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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.