Evidence map›Paper›PMID 31133583›Full record

ArticleBMJ open2019

Prevalence, clinical relevance and predictive factors of medication discrepancies revealed by medication reconciliation at hospital admission: prospective study in a Swiss internal medicine ward.

Olivier Giannini, Nicole Rizza, Michela Pironi, Saida Parlato, Brigitte Waldispühl Suter, Paola Borella, Alberto Pagnamenta, Liat Fishman, Alessandro Ceschi

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.2field-weighted citation impact, top 5% 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

22 citing papers in PubMed, 50 citations in OpenAlex.

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  4. Medication discrepancies and medication-related problems in psychiatric patients: A medication reconciliation study.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026
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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

9 authors at 6 institutions in 5 countries.

Olivier Giannini *Department of Internal Medicine, Ospedale Regionale di Mendrisio, Ente Ospedaliero Cantonale, Mendrisio, Ticino, Switzerland.
Nicole Rizza *Hospital Pharmacy Service, Institute of Pharmacological Sciences of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.
Michela PironiHospital Pharmacy Service, Institute of Pharmacological Sciences of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.
Saida ParlatoHospital Pharmacy Service, Institute of Pharmacological Sciences of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.
Brigitte Waldispühl SuterDivision of Clinical Informatics, Ente Ospedaliero Cantonale, Bellinzona, Switzerland.
Paola BorellaDepartment of Internal Medicine, Ospedale Regionale di Mendrisio, Ente Ospedaliero Cantonale, Mendrisio, Ticino, Switzerland.
Alberto PagnamentaUnit of Clinical Epidemiology, Ente Ospedaliero Cantonale, Bellinzona, Switzerland.
Liat FishmanPatient Safety Foundation, Zurich, Switzerland.
Alessandro CeschiDivision of Clinical Pharmacology and Toxicology, Institute of Pharmacological Sciences of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.
Ente Ospedaliero Cantonale · CHServices Hospital · PKMRC Epidemiology Unit · GBNational Patient Safety Foundation · USOspedale Regionale di Mendrisio · CHUniversity Hospital of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveMedication reconciliation (MedRec) is a relevant safety procedure in medication management at transitions of care. The aim of this study was to evaluate the impact of MedRec, including a

designProspective interventional study. Data were analysed using descriptive statistics followed by univariate and multivariate Poisson regression models and a zero-inflated Poisson regression model.

settingInternal medicine ward in a secondary care hospital in Southern Switzerland.

participantsThe first 100 consecutive patients admitted in an internal medicine ward. PRIMARY AND SECONDARY OUTCOME MEASURES: Medication discrepancies between the medication list obtained by the physician and that obtained by a pharmacist according to a systematic approach (BPMH) were collected, quantified and assessed by an expert panel that assigned a severity score. The same procedure was applied to discrepancies regarding allergies. Predicting factors for medication discrepancies were identified.

resultsThe median of medications per patient was 8 after standard medication history and 11 after BPMH. Total admission discrepancies were 524 (5.24 discrepancies per patient) with at least 1 discrepancy per patient. For 47 patients, at least one discrepancy was classified as clinically relevant. Discrepancies were classified as significant and serious in 19% and 2% of cases, respectively. Furthermore, 67% of the discrepancies were detected during the interview conducted by the pharmacist with the patients and/or their caregivers. The number of drugs used and the autonomous management of home therapy were associated with an increased number of clinically relevant discrepancies in a multivariable Poisson regression model.

conclusionEven in an advanced healthcare system, a standardised MedRec process including a BPMH represents an important strategy that may contribute to avoid a notable number of clinically relevant discrepancies and potential adverse drug events.

Indexed as

AdultAgedAged, 80 and overFemaleHospitalizationHumansMaleMedication ErrorsMedication ReconciliationMiddle AgedPatient TransferProspective StudiesSwitzerlandclinical pharmacologyinternal medicinemedical historyrisk management

Identifiers

PMID31133583
PMCPMC6538074
OpenAlexW2947301038

What OpenQuestion holds

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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.