Evidence map›Paper›PMID 39232813›Full record

ArticleArchives of public health = Archives belges de sante publique2024

Recognizing and preventing unacknowledged prescribing errors associated with polypharmacy.

Giovanna Gentile, Antonio Del Casale, Ottavia De Luca, Gerardo Salerno, Sara Spirito, Martina Regiani, Matteo Regiani, Saskia Preissner, Monica Rocco, Robert Preissner and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Archives of public health = Archives belges de sante publique, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

12 authors.

Giovanna Gentile, Via di Grottarossa 1035/1039, Rome, 00189, Italy.
Antonio Del CasaleDepartment of Dynamic and Clinical Psychology and Health Studies, Faculty of Medicine and Psychology, Sapienza University of Rome, Roma, 00189, Italy.
Ottavia De LucaLaboratory of Clinical Biochemistry, Advanced Molecular Diagnostic Unit, Sant'Andrea University Hospital, Via di Grottarossa 1035/1039, Rome, 00189, Italy.
Gerardo Salerno, Via di Grottarossa 1035/1039, Rome, 00189, Italy.
Sara Spirito, Via di Grottarossa 1035/1039, Rome, 00189, Italy.
Martina RegianiFaculty of Medicine and Psychology, Sapienza University of Rome, Roma, 00189, Italy.
Matteo RegianiFaculty of Medicine and Psychology, Sapienza University of Rome, Roma, 00189, Italy.
Saskia PreissnerDepartment Oral and Maxillofacial Surgery, Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
Monica RoccoDepartment of Medical-Surgical Sciences and Translational Medicine, Sapienza University of Rome, Rome, 00189, Italy.
Robert PreissnerStructural Bioinformatics Group, Institute for Physiology, Charité-University Medicine Berlin, 10117, Berlin, Germany.
Maurizio Simmaco, Via di Grottarossa 1035/1039, Rome, 00189, Italy.
Marina Borro, Via di Grottarossa 1035/1039, Rome, 00189, Italy. marina.borro@uniroma1.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrescribing errors put an enormous burden on health and the economy, claiming implementation of effective methods to prevent/reduce them. Polypharmacy regimens (five or more drugs) are highly prone to unacknowledged prescribing errors, since the complex network of drug-drug interactions, guidelines and contraindications is challenging to be adequately evaluated in the prescription phase, especially if different doctors are involved. Clinical decision support systems aimed at polypharmacy evaluation may be crucial to recognize and correct prescribing errors.

methodsA commercial clinical decision support system (Drug-PIN

resultsPolypharmacy was present in 205 patients, and moderate to high risk for medication harm was predicted by Drug-PIN

conclusionsResults suggest that computer-aided evaluation of medication-associated harm could be a valuable and actionable tool to identify and prevent prescribing errors in polypharmacy. We conducted the study in a Hospital pre-admission setting, which is not representative of the general population but represents a hotspot to intercept fragile population, where a consistent fraction of potentially harmful polypharmacy regimens could be promptly identified and corrected by systematic use of adequate clinical decision support tools.

Indexed as

Drug-drug interactionsDrug-PIN®Medication errorsPolypharmacyPrescribing errors

Identifiers

PMID39232813
PMCPMC11373128

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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.