Evidence map›Paper›PMID 31992634›Full record

ArticleBMJ health & care informatics2020

Optimising electronic prescribing in hospitals: a scoping review protocol.

Jac Williams, David W Bates, Aziz Sheikh

Open access · goldAbstract read
In one paragraph

Article in BMJ health & care informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 13 citations in OpenAlex.

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  6. Unveiling medication errors in liver transplant patients towards enhancing the imperative patient safety.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2023
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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

3 authors at 2 institutions in 2 countries.

Jac WilliamsThe University of Edinburgh Usher Institute, Edinburgh, UK.ORCID http://orcid.org/0000-0002-8486-3457
David W BatesDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0001-6268-1540
Aziz SheikhThe University of Edinburgh Usher Institute, Edinburgh, UK aziz.sheikh@ed.ac.uk.ORCID https://orcid.org/0000-0001-7022-3056
University of Edinburgh · GBBrigham and Women's Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionElectronic prescribing (ePrescribing) systems can improve the quality of prescribing decisions and substantially reduce the risk of serious medication errors in hospitals. However, realising these benefits depends on ensuring that relevant sociotechnical considerations are addressed. Optimising ePrescribing systems is essential to maximise the associated benefits and minimise the accompanying risks of these large-scale and expensive health informatics infrastructures.

methodsWe will undertake a systematic scoping review of the literature to identify strategies to achieve optimisation of ePrescribing systems. We will search Medline, Embase and CINAHL for the period 1 January 2010 to 1 June 2019 and the grey literature by using Google Scholar. Independent reviewers will screen the results using predefined inclusion and exclusion criteria and will extract data for narrative and thematic synthesis. DISCUSSION: This work will be published in a peer-reviewed journal and we will ensure that the findings are both accessible and interpretable to the public, academics, policymakers and National Health Service leaders.

Indexed as

Pharmacy Service, HospitalQuality ImprovementElectronic PrescribingScoping Reviews as Topichealth careinformation systemsmedical informaticspatient carerecord systems

Identifiers

PMID31992634
PMCPMC7062357
OpenAlexW3004283815

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.