Evidence map›Paper›PMID 28760793›Full record

ArticleBMJ open2017

PIM-Check: development of an international prescription-screening checklist designed by a Delphi method for internal medicine patients.

Aude Desnoyer, Anne-Laure Blanc, Valérie Pourcher, Marie Besson, Caroline Fonzo-Christe, Jules Desmeules, Arnaud Perrier, Pascal Bonnabry, Caroline Samer, Bertrand Guignard

Abstract read
In one paragraph

Article in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

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

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  9. Development and Delphi validation of a Best Possible Medication History form.European journal of hospital pharmacy : science and practice · 2023
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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

10 authors.

Aude DesnoyerDepartment of Pharmacy, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Anne-Laure BlancDepartment of Pharmacy, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Valérie PourcherDepartment of Infectious and Tropical Diseases, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière, Paris, France.
Marie BessonDepartment of Clinical Pharmacology and Toxicology, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Caroline Fonzo-ChristeDepartment of Pharmacy, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Jules DesmeulesDepartment of Clinical Pharmacology and Toxicology, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Arnaud PerrierDepartment of General Internal Medicine, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Pascal BonnabryDepartment of Pharmacy, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Caroline SamerDepartment of Clinical Pharmacology and Toxicology, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Bertrand GuignardDepartment of Pharmacy, Hôpitaux Universitaires de Genève, Geneva, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPotentially inappropriate medication (PIM) occurs frequently and is a well-known risk factor for adverse drug events, but its incidence is underestimated in internal medicine. The objective of this study was to develop an electronic prescription-screening checklist to assist residents and young healthcare professionals in PIM detection.

designFive-step study involving selection of medical domains, literature review and 17 semistructured interviews, a two-round Delphi survey, a forward/back-translation process and an electronic tool development.

setting22 University and general hospitals from Canada, Belgium, France and Switzerland.

participants40 physicians and 25 clinical pharmacists were involved in the study.Agreement with the checklist statements and their usefulness for healthcare professional training were evaluated using two 6-point Likert scales (ranging from 0 to 5). PRIMARY AND SECONDARY OUTCOME MEASURES: Agreement and usefulness ratings were defined as: >65% of the experts giving the statement a rating of 4 or 5, during the first Delphi-round and >75% during the second.

results166 statements were generated during the first two steps. Mean agreement and usefulness ratings were 4.32/5 (95% CI 4.28 to 4.36) and 4.11/5 (4.07 to 4.15), respectively, during the first Delphi-round and 4.53/5 (4.51 to 4.56) and 4.36/5 (4.33 to 4.39) during the second (p<0.001). The final checklist includes 160 statements in 17 medical domains and 56 pathologies. An algorithm of approximately 31 000 lines was developed including comorbidities and medications variables to create the electronic tool.

conclusionPIM-Check is the first electronic prescription-screening checklist designed to detect PIM in internal medicine. It is intended to help young healthcare professionals in their clinical practice to detect PIM, to reduce medication errors and to improve patient safety.

Indexed as

Potentially Inappropriate Medication ListAdultAttitude of Health PersonnelChecklistDelphi TechniqueFemaleHumansInappropriate PrescribingInternal MedicineMaleMedication ErrorsMiddle AgedClinical Practice GuidelinesEvidence-based MedicineInternal MedicineMedical EducationPharmacology and Toxicology

Identifiers

PMID28760793
PMCPMC5642656

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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.