Evidence map›Paper›PMID 31297019›Full record

ArticleSaudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society2019

Addressing medication errors in an adult oncology department in Saudi Arabia: A qualitative study.

Waleed Alharbi, Jennifer Cleland, Zoe Morrison

Abstract read
In one paragraph

Article in Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Observational
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.

Waleed AlharbiCentre for Healthcare Education Research and Innovation (CHERI), Institute of Education in Medical and Dental Sciences, University of Aberdeen, Aberdeen, United Kingdom.
Jennifer ClelandCentre for Healthcare Education Research and Innovation (CHERI), Institute of Education in Medical and Dental Sciences, University of Aberdeen, Aberdeen, United Kingdom.
Zoe MorrisonDepartment of Human Resources & Organisational Behaviour, University of Greenwich, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThere is a wide range of strategies that could help in minimizing medication errors during healthcare delivery. We undertook a qualitative study to identify recommended solutions to minimize medication errors in an adult oncology department in Saudi Arabia from the perspectives of healthcare professionals.

methodsThis was a qualitative study conducted in an adult oncology department in Saudi Arabia. After obtaining the required ethical approvals and written consents from the participants, seven focus group discussions were carried out for data collection. A stratified purposive sampling strategy was used to recruit medical doctors, pharmacists, and nurses. NVivo Pro version 11 was used for data analyses. Inductive content analysis was adopted in the coding of collected data.

resultOur study showed that improving organizational support, staff education, and communication could help in minimizing medication errors in the adult oncology department.

conclusionThe adoption of multiple strategies is required to improve the safety of the medication process in the adult oncology department. We argue that the availability of supportive leadership should be prioritized as it plays a crucial role in determining the effectiveness and efficiency of both staff education and communication.

Indexed as

Adult OncologyMedication errorsQualitative studySaudi ArabiaSolutions

Identifiers

PMID31297019
PMCPMC6598207

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.