Evidence map›Paper›PMID 35360263›Full record

ArticleContrast media & molecular imaging2022

Application of Intelligent Intravenous Drug Dispensing Robot in Clinical Nursing.

Lifen Zhang, Wei Liu, Yanhong Zhang

Abstract read
In one paragraph

Article in Contrast media & molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Hospital-Based Robotic Applications in Nursing Practice: A Scoping Review.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2026
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  3. Review
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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.

Lifen ZhangPharmacy Intravenous Admixture Service Center, Harbin Medical University Cancer Hospital, Heilongjiang, Haerbin 150000, China.ORCID 0000-0002-1418-1282
Wei LiuPET/CT-MR Center, Harbin Medical University Cancer Hospital, Heilongjiang, Haerbin 150000, China.ORCID 0000-0003-1064-5534
Yanhong ZhangICU Unit 1, Harbin Medical University Cancer Hospital, Heilongjiang, Haerbin 150000, China.ORCID 0000-0003-2535-668X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to explore the application of intelligent intravenous drug dispensing robot in clinical nursing, the efficiency, residual amount, needle pushing, and pulling times, the incidence of accidental hand stab injury and the accuracy of drug dispensing were compared and observed between intelligent intravenous drug dispensing robot and manual dispensing. The study found that the sterile powder residual amount of injection is pointed out in the standard, the drug label is not equipped with ≤50 mg, and the residual limit is ≤ 15%; the lamination is 50-150 mg, the residual amount is limited to ≤10%; the marking is 150-500 mg, the residual amount is ≤ 7%; the marking is 500 mg, the residual amount is limited to ≤5%; 6 months of artificial deployment accidental stab ergonomics occur; without this phenomenon when using the drug-like robot, 6 months internal use of the pharmaceutical robot, 4 times of error occurrence, and errors occurred 60 times. During the clinical intravenous infusion dispensing process, the use of intelligent vein is used to configure the robot, improve the efficiency of the drug, reduce the incidence of drug residual, reduce the incidence of dispensing, increase the accuracy and safety of venous liquidation, and decrease to some extent professional injury caused by drug formulation for liquid nurses.

Indexed as

Medication ErrorsRoboticsHumansInjections

Identifiers

PMID35360263
PMCPMC8960012

What OpenQuestion holds

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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.