Evidence map›Paper›PMID 32948574›Full record

Observational studyBMJ open2020

What do double-check routines actually detect? An observational assessment and qualitative analysis of identified inconsistencies.

Yvonne Pfeiffer, Chantal Zimmermann, David L B Schwappach

Abstract readObservational Study
In one paragraph

Observational study in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Yvonne PfeifferSwiss Patient Safety Foundation, Asylstr, Zurich, Switzerland pfeiffer@patientensicherheit.ch.ORCID 0000-0001-6226-5037
Chantal ZimmermannInstitute of Social and Preventive Medicine (ISPM), University of Bern, Zurich, Switzerland.
David L B SchwappachSwiss Patient Safety Foundation, Asylstr, Zurich, Switzerland.ORCID 0000-0001-8668-3065

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesDouble checking is used in oncology to detect medication errors before administering chemotherapy. The objectives of the study were to determine the frequency of detected potential medication errors, i.e., mismatching information, and to better understand the nature of these inconsistencies.

designIn observing checking procedures, field noteswere taken of all inconsistencies that nurses identified during double checking the order against the prepared chemotherapy.

settingOncological wards and ambulatory infusion centres of three Swiss hospitals.

participantsNurses' double checking was observed. OUTCOME MEASURES: In a qualitative analysis, (1) a category system for the inconsistencies was developed and (2) independently applied by two researchers.

resultsIn 22 (3.2%) of 690 observed double checks, 28 chemotherapy-related inconsistencies were detected. Half of them related to non-matching information between order and drug label, while the other half was identified because the nurses used their own knowledge. 75% of the inconsistencies could be traced back to inappropriate orders, and the inconsistencies led to 33 subsequent or corrective actions.

conclusionsIn double check situations, the plausibility of the medication is often reviewed. Additionally, they serve as a correction for errors and that are made much earlier in the medication process, during order. Both results open up new opportunities for improving the medication process.

Indexed as

Medical OncologyMedication ErrorsAmbulatory Care FacilitiesHumanschemotherapyorganisation of health servicesquality in health care

Identifiers

PMID32948574
PMCPMC7500291

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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.