Evidence map›Paper›PMID 36088328›Full record

ArticleBMC medical informatics and decision making2022

OntoPharma: ontology based clinical decision support system to reduce medication prescribing errors.

Elena Calvo-Cidoncha, Concepción Camacho-Hernando, Faust Feu, Xavier Pastor-Duran, Carles Codina-Jané, Raimundo Lozano-Rubí

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 4% of its field
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Elena Calvo-CidonchaPharmacy Service, Division of Medicines, Hospital Clínic of Barcelona, 170 Villarroel Street, 08036, Barcelona, Spain. elcalvo@clinic.cat.
Concepción Camacho-HernandoDivision of Medicines, Hospital Clínic of Barcelona, 170 Villarroel Street, 08036, Barcelona, Spain.
Faust FeuManagement Team, Hospital Clínic of Barcelona, 170 Villarroel Street, 08036, Barcelona, Spain.
Xavier Pastor-DuranUnit of Medical Informatics, Hospital Clínic of Barcelona, 170 Villarroel Street, 08036, Barcelona, Spain.
Carles Codina-JanéPharmacy Service, Division of Medicines, Hospital Clínic of Barcelona, 170 Villarroel Street, 08036, Barcelona, Spain.
Raimundo Lozano-RubíUnit of Medical Informatics, Hospital Clínic of Barcelona, 170 Villarroel Street, 08036, Barcelona, Spain.
Hospital Clínic de Barcelona · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical decision support systems (CDSS) have been shown to reduce medication errors. However, they are underused because of different challenges. One approach to improve CDSS is to use ontologies instead of relational databases. The primary aim was to design and develop OntoPharma, an ontology based CDSS to reduce medication prescribing errors. Secondary aim was to implement OntoPharma in a hospital setting.

methodsA four-step process was proposed. (1) Defining the ontology domain. The ontology scope was the medication domain. An advisory board selected four use cases: maximum dosage alert, drug-drug interaction checker, renal failure adjustment, and drug allergy checker. (2) Implementing the ontology in a formal representation. The implementation was conducted by Medical Informatics specialists and Clinical Pharmacists using Protégé-OWL. (3) Developing an ontology-driven alert module. Computerised Physician Order Entry (CPOE) integration was performed through a REST API. SPARQL was used to query ontologies. (4) Implementing OntoPharma in a hospital setting. Alerts generated between July 2020/ November 2021 were analysed.

resultsThe three ontologies developed included 34,938 classes, 16,672 individuals and 82 properties. The domains addressed by ontologies were identification data of medicinal products, appropriateness drug data, and local concepts from CPOE. When a medication prescribing error is identified an alert is shown. OntoPharma generated 823 alerts in 1046 patients. 401 (48.7%) of them were accepted.

conclusionsOntoPharma is an ontology based CDSS implemented in clinical practice which generates alerts when a prescribing medication error is identified. To gain user acceptance OntoPharma has been designed and developed by a multidisciplinary team. Compared to CDSS based on relational databases, OntoPharma represents medication knowledge in a more intuitive, extensible and maintainable manner.

Indexed as

Decision Support Systems, ClinicalMedical Order Entry SystemsDrug InteractionsDrug PrescriptionsHumansMedication Errors“Biological ontologies” [Mesh]“Decision support systems clinical” [Mesh]“Drug prescriptions” [Mesh]“Medication errors” [Mesh]

Identifiers

PMID36088328
PMCPMC9463735
OpenAlexW4295445652

What OpenQuestion holds

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LicenceCC BY
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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.