Evidence map›Paper›PMID 26335981›Full record

SynthesisJournal of the American Medical Informatics Association : JAMIA2015

Medication-indication knowledge bases: a systematic review and critical appraisal.

Hojjat Salmasian, Tran H Tran, Herbert S Chase, Carol Friedman

Abstract readComparative StudySystematic Review
In one paragraph

Synthesis in Journal of the American Medical Informatics Association : JAMIA, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Evaluating NLP Approaches to Extract Drug Indications.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026
    Article
  3. Article
  4. Review
  5. Hierarchical Concept Relations Improve Detection of Off-Label Drug Use in Electronic Health Records Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Developing a Data-driven Medication Indication Knowledge Base using a Large Scale Medical Claims Database.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019
    Article
  13. Article
  14. Article
  15. Disease-drug database for pharmacogenomic-based prescribing.Clinical pharmacology and therapeutics · 2016
    Article
  16. 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.

Hojjat SalmasianDepartment of Biomedical Informatics, Columbia University, New York, New York, USA hs2610@columbia.edu.
Tran H TranNew York Presbyterian Hospital, New York, New York, USA College of Pharmacy and Health Sciences, St. John's University.
Herbert S ChaseDepartment of Biomedical Informatics, Columbia University, New York, New York, USA.
Carol FriedmanDepartment of Biomedical Informatics, Columbia University, New York, New York, USA.

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
Pharmacovigilence using Natural Language Processing, Statistics, and the EHRR01LM010016 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FRIEDMAN, CAROL · 2009 to 2016
$3.4M
A Biomedical Natural Language Processing ResourceR01LM008635 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FRIEDMAN, CAROL · 2005 to 2008
$2.1M
NLM NIH HHS 5 T15 LM007079NLM NIH HHS R01 LM008635NLM NIH HHS R01 LM010016NLM NIH HHS R01 LM010016-0S1NLM NIH HHS R01 LM010016-0S2
6 · The paper itself

Abstract

objectiveMedication-indication information is a key part of the information needed for providing decision support for and promoting appropriate use of medications. However, this information is not readily available to end users, and a lot of the resources only contain this information in unstructured form (free text). A number of public knowledge bases (KBs) containing structured medication-indication information have been developed over the years, but a direct comparison of these resources has not yet been conducted. MATERIAL AND

methodsWe conducted a systematic review of the literature to identify all medication-indication KBs and critically appraised these resources in terms of their scope as well as their support for complex indication information.

resultsWe identified 7 KBs containing medication-indication data. They notably differed from each other in terms of their scope, coverage for on- or off-label indications, source of information, and choice of terminologies for representing the knowledge. The majority of KBs had issues with granularity of the indications as well as with representing duration of therapy, primary choice of treatment, and comedications or comorbidities. DISCUSSION AND

conclusionThis is the first study directly comparing public KBs of medication indications. We identified several gaps in the existing resources, which can motivate future research.

Indexed as

Drug Therapy, Computer-AssistedKnowledge BasesHumansOff-Label UseSystematized Nomenclature of Medicineappropriatenessdrug therapyelectronic health recordsindicationoff-label use

Identifiers

PMID26335981
PMCPMC5009909

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.