Evidence map›Paper›PMID 28717929›Full record

Trial reportEuropean journal of clinical pharmacology2017

Reduction in targeted potentially inappropriate medication use in elderly inpatients: a pragmatic randomized controlled trial.

Benoit Cossette, Jean-François Éthier, Thomas Joly-Mischlich, Josée Bergeron, Geneviève Ricard, Serge Brazeau, Mathieu Caron, Olivier Germain, Hélène Payette, Janusz Kaczorowski and 1 more

Abstract readRandomized Controlled TrialPragmatic Clinical Trial
PubMed Publisher
In one paragraph

Trial report in European journal of clinical pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 9 pooled it
2.2field-weighted citation impact, top 14% 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

26 citing papers in PubMed, 9 syntheses or guidelines pooled it, 51 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

11 authors at 4 institutions in 1 country.

Benoit CossetteFaculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada. benoit.cossette@usherbrooke.ca.
Jean-François ÉthierFaculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada.
Thomas Joly-MischlichFaculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada.
Josée BergeronDepartment of Pharmacy, Centre Intégré Universitaire de Santé et de Services Sociaux de l'Estrie - Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada.
Geneviève RicardFaculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada.
Serge BrazeauDepartment of Medicine, Centre Intégré Universitaire de Santé et de Services Sociaux de l'Estrie - Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada.
Mathieu CaronDepartment of Information Technology, Centre Intégré Universitaire de Santé et de Services Sociaux de l'Estrie - Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada.
Olivier GermainDepartment of Mathematics, Université de Sherbrooke, Sherbrooke, QC, Canada.
Hélène PayetteFaculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada.
Janusz KaczorowskiDepartment of Family and Emergency Medicine, Université de Montréal, Montréal, QC, Canada.
Mitchell LevineDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Université de Sherbrooke · CACentre Hospitalier Universitaire de Sherbrooke · CACentre Hospitalier de l’Université de Montréal · CAMcMaster University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe use of potentially inappropriate medications (PIMs) in hospitalized older adults is a complex problem, but the use of computerized alert systems (CAS) has shown some potential. The study's objective is to assess the change in PIM use with a CAS-based pharmacist-physician intervention model compared to usual clinical care.

methodsPragmatic single-site randomized controlled trial was conducted at a university teaching hospital. Hospitalizations identified with selected Beers or STOPP criteria were randomized to usual clinical care or to the CAS-based pharmacist-physician intervention. The primary outcome was PIM drug cessation or dosage decrease. Clinical relevance of the CAS alerts was assessed.

resultsAnalyses included 231 patients who had 128 and 126 hospitalizations in the control and intervention groups, respectively. Patients had a mean age of 81, and 60% were female. In the intervention compared to the control group, drug cessation or dosage decrease were more frequent at 48 h post-alert (45.8 vs 15.9%; absolute difference 30.0%; 95%CI 13.8 to 46.1%) and at discharge from the hospital (48.1 vs 27.3%; absolute difference 20.8%; 95%CI 4.6 to 37.0%). In a post hoc analysis of all alerts, regardless of their clinical relevance, the absolute difference in drug cessation or dosage decrease between the intervention and control groups was 16.2% (95%CI 2.9 to 29.6%) at 48 h and 8.0% (95%CI -4.0 to 20.0%) at discharge from the hospital.

conclusionsIn hospitalized older adults, a CAS-based pharmacist-physician intervention, compared to usual clinical care, resulted in significant higher number of drug cessation and dosage reductions for targeted PIMs.

Indexed as

Drug-Related Side Effects and Adverse ReactionsPotentially Inappropriate Medication ListAgedAged, 80 and overFemaleHealth Services for the AgedHospitals, UniversityHumansInappropriate PrescribingInpatientsMaleMedical Order Entry SystemsComputerized alert systemHospitalKnowledge translationOlder adultsPotentially inappropriate medications

Identifiers

PMID28717929
OpenAlexW2734786126

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.