Evidence map›Paper›PMID 38551750›Full record

ArticleInternational journal of clinical pharmacy2024

Clinical risk assessment of modelled situations in a pharmaceutical decision support system: a modified e-Delphi exploratory study.

Juline Bouet, Arnaud Potier, Bruno Michel, Céline Mongaret, Mathias Ade, Alexandre Dony, Anne-Sophie Larock, Édith Dufay

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In one paragraph

Article in International journal of clinical pharmacy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 27% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

8 authors at 5 institutions in 2 countries.

Juline BouetPharmacy Department, CHU Nîmes, 4 Rue du Professeur Robert Debré, 30000, Nîmes, France. juline.bouet@gmail.com.ORCID http://orcid.org/0000-0001-7571-8437
Arnaud PotierPharmacy Department, CH Lunéville, 54300, 6 Rue Jean Girardet, Lunéville, France.
Bruno MichelPharmacy Department, HU Strasbourg, 1 Place de l'Hopital, 67000, Strasbourg, France.
Céline MongaretPharmacy Department, CHU Clermont-Ferrand, 58 Rue Montalembert, 63000, Clermont-Ferrand, France.
Mathias AdePharmacy Department, CP Nancy, 1 Rue Dr Archambault, 54000, Laxou, France.
Alexandre DonyPharmacy Department, CH Lunéville, 54300, 6 Rue Jean Girardet, Lunéville, France.
Anne-Sophie LarockPharmacy Department, CHU UCL Namur, Place Louise Godin 15, 5330, Yvoir, Belgium.
Édith DufayPharmacy Department, CH Lunéville, 54300, 6 Rue Jean Girardet, Lunéville, France.
Schneider Electric (France) · FRCentre d’Investigation Clinique Innovation Technologique de Nancy · FRCentre Hospitalier Universitaire de Clermont-Ferrand · FRCHU Dinant Godinne UCL Namur · BEHôpital Civil, Strasbourg · FR

Funding

Grand-Est Regional Health Agency 202104614
6 · The paper itself

Abstract

backgroundPharmaceutical decision support systems (PDSSs) use reasoning software to match patient data to modelled situations likely to cause drug-related problems (DRPs) or adverse drug events. To aid decision-making, modelled situations must be linked to well-defined systemic clinical risks.

aimTo obtain expert consensus on the level of clinical risk for patients associated with each modelled situation that could be addressed using a PDSS.

methodA two-round e-Delphi survey was conducted from February to April 2022, involving 20 experts from four French-speaking countries. Participants had to rate modelled situations on two five-point Likert scales, assessing the likelihood of clinical consequences and their severity. The degree of consensus was determined as the proportion of participants providing risk scores in line with the median. The combined median scores for likelihood and severity provided the level of risk according to the Clinical Risk Situation for Patients (CRiSP) scale, formalized via validated tools.

resultsThe expert panel achieved consensus (≥ 75% agreement) on 48 out of 52 modelled clinical situations. Among these, 45 were categorized as high or extreme risk. The most common DRP identified was overdosing, accounting for 22% of cases. Furthermore, DRPs involving cardiovascular, psychiatric, and endocrinological drug classes were prevalent, constituting 45, 13, and 9% of cases, respectively.

conclusionThrough consensus, our study identified 45 modelled clinical situations associated with high or extreme risks. This study highlights the interest of using PDSSs to prevent harm in patients and, on a large scale, document the impact of the pharmacist in preventing, intercepting and managing iatrogenic drug risk.

Indexed as

Decision Support Systems, ClinicalDelphi TechniqueDrug-Related Side Effects and Adverse ReactionsAdultConsensusFemaleHumansMaleMiddle AgedRisk AssessmentClinical decision support systemDrug-related problemsMedication errorsMedication review

Identifiers

PMID38551750
OpenAlexW4393310053

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.