Evidence map›Paper›PMID 28744584›Full record

SynthesisEuropean journal of clinical pharmacology2017

Predictors for unintentional medication reconciliation discrepancies in preadmission medication: a systematic review.

Julie Hias, Lorenz Van der Linden, Isabel Spriet, Peter Vanbrabant, Ludo Willems, Jos Tournoy, Sabrina De Winter

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis 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 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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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

7 authors.

Julie HiasPharmacy Department, University Hospitals Leuven, Leuven, Belgium. julie.1.hias@uzleuven.be.ORCID http://orcid.org/0000-0002-7269-2515
Lorenz Van der LindenPharmacy Department, University Hospitals Leuven, Leuven, Belgium.
Isabel SprietPharmacy Department, University Hospitals Leuven, Leuven, Belgium.
Peter VanbrabantDepartment of General Internal Medicine, University of Leuven, University Hospitals Leuven, Leuven, Belgium.
Ludo WillemsPharmacy Department, University Hospitals Leuven, Leuven, Belgium.
Jos TournoyDepartment of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium.
Sabrina De WinterPharmacy Department, University Hospitals Leuven, Leuven, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDiscrepancies in preadmission medication (PAM) are common and potentially harmful. Medication reconciliation is able to reduce the discrepancy rate, yet implementation is challenging. In order for reconciliation efforts to be more cost-effective, patients at high risk for reconciliation errors should be identified. The purpose of this systematic review is to identify predictors for unintentional discrepancies in PAM.

methodsMedline and Embase were searched systematically until June 2017. Only studies concerning adult subjects were retained. Quantitative studies were included if predictors for unintentional discrepancies in the PAM had been determined on hospital admission. Variables were divided into patient-, medication-, and setting-related predictors based on a thematic analysis. Studies on identification of predictors for discrepancies and potentially harmful discrepancies were handled separately.

resultsThirty-five studies were eligible, of which 5 studies focused on potentially harmful discrepancies. The following 16 significant variables were identified using multivariable prediction models: number of preadmission drugs, patient's age, availability of a drug list, patients' understanding of medication, usage of different outpatient pharmacies, number of high-risk drugs, discipline for which the patient is admitted, admitting physician's experience, number and type of consulted sources, patient's gender, type of care before admission, number of outpatient visits during the past year, class of medication, number of reimbursements, use of an electronic prescription system, and type of admission (elective vs emergency). The number of preadmission drugs was identified as a predictor in 20 studies. Potentially harmful discrepancies were ascertained in 5 studies with age found to have a predictive value in all 5 studies.

conclusionMultiple suitable predictors for PAM-related discrepancies were identified of which higher age and polypharmacy were reported most frequently.

Indexed as

Medication ReconciliationPatient AdmissionHumansHigh-risk patientsHospitalizationMedication reconciliationPredictorsReconciliation discrepanciesRisk stratification

Identifiers

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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.