Evidence map›Paper›PMID 22019377›Full record

ArticleJournal of biomedical informatics2012

Development and evaluation of an ontology for guiding appropriate antibiotic prescribing.

Tiffani J Bright, E Yoko Furuya, Gilad J Kuperman, James J Cimino, Suzanne Bakken

Abstract readEvaluation Study
In one paragraph

Article in Journal of biomedical informatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
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  10. Article
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  13. Design and evaluation of a bacterial clinical infectious diseases ontology.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2013
    Article
  14. Ontological approach to reduce complexity in polypharmacy.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2013
    Article
  15. Article
  16. Deriving an abstraction network to support quality assurance in OCRe.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2012
    Article
  17. Ontological approach for safe and effective polypharmacy prescription.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2012
    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

5 authors.

Tiffani J BrightDuke University Medical Center, Division of Clinical Informatics, 2200 West Main St., Suite 600, Durham, NC 27710, USA. tiffani.bright@gmail.com
E Yoko Furuya
Gilad J Kuperman
James J Cimino
Suzanne Bakken

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
Training in Interdisciplinary Research to Reduce Antimicrobial Resistance (TIRAR)T90NR010824 · NINR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI LARSON, ELAINE LUCILLE · 2007 to 2011
$1.0M
Biomedical Translational Research Information System (BTRIS) Data Reuse ProtocolZIACL000904 · CLC · CLINICAL CENTER · PI CIMINO, JAMES · 2009 to 2014
$0k
NINR NIH HHS T90 NR010824NLM NIH HHS T15 LM007079PHS HHS D11 HP07346
6 · The paper itself

Abstract

objectivesTo develop and apply formal ontology creation methods to the domain of antimicrobial prescribing and to formally evaluate the resulting ontology through intrinsic and extrinsic evaluation studies.

methodsWe extended existing ontology development methods to create the ontology and implemented the ontology using Protégé-OWL. Correctness of the ontology was assessed using a set of ontology design principles and domain expert review via the laddering technique. We created three artifacts to support the extrinsic evaluation (set of prescribing rules, alerts and an ontology-driven alert module, and a patient database) and evaluated the usefulness of the ontology for performing knowledge management tasks to maintain the ontology and for generating alerts to guide antibiotic prescribing.

resultsThe ontology includes 199 classes, 10 properties, and 1636 description logic restrictions. Twenty-three Semantic Web Rule Language rules were written to generate three prescribing alerts: (1) antibiotic-microorganism mismatch alert; (2) medication-allergy alert; and (3) non-recommended empiric antibiotic therapy alert. The evaluation studies confirmed the correctness of the ontology, usefulness of the ontology for representing and maintaining antimicrobial treatment knowledge rules, and usefulness of the ontology for generating alerts to provide feedback to clinicians during antibiotic prescribing.

conclusionsThis study contributes to the understanding of ontology development and evaluation methods and addresses one knowledge gap related to using ontologies as a clinical decision support system component-a need for formal ontology evaluation methods to measure their quality from the perspective of their intrinsic characteristics and their usefulness for specific tasks.

Indexed as

Anti-Bacterial AgentsBacterial InfectionsDecision Support Systems, ClinicalDrug HypersensitivityDrug Therapy, Computer-AssistedElectronic PrescribingHumansMedication ErrorsAnti-Bacterial Agents

Identifiers

PMID22019377
PMCPMC3272092

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Registered trials

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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.