Evidence map›Paper›PMID 32313713›Full record

ArticleInternational journal of nursing sciences2020

Optimization of the intravenous infusion workflow in the isolation ward for patients with coronavirus disease 2019.

Yan Song, Wenhui Wang, Lijun Zhang, Li Sha, Guilan Lu

Abstract read
In one paragraph

Article in International journal of nursing sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. The Impact of Pandemic-Driven Care Redesign on Hospital Efficiency.Risk management and healthcare policy · 2024
    Review
  3. Article
  4. Article
  5. 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

5 authors.

Yan SongNursing Department, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Jiangsu, China.
Wenhui WangDepartment of Gynaecology and Obsterics, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Jiangsu, China.
Lijun ZhangDepartment of Infectious Diseases, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Jiangsu, China.
Li ShaNursing Department, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Jiangsu, China.
Guilan LuNursing Department, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to evaluate the effect of optimization of the intravenous infusion workflow in isolation wards for patients with coronavirus disease 2019.

methodsThe infusion management group optimized the intravenous infusion workflow based on Hamer's Process Reengineering Theory and applied it to the treatment of patients with coronavirus disease 2019. The work efficiency, patients' satisfaction and economic indicators before and after optimization were compared.

resultsAfter the infusion workflow was optimized, average times for preparation drugs and intravenous admixture, and patients' waiting time decreased from 4.84 min, 4.03 min, and 34.33 min to 3.50 min, 2.60 min, and 30.87 min, respectively, patients' satisfaction increased from 66.7% to 93.3%, and the cost of personal protective equipment (PPE) decreased from 46.67 sets and 186.6 CNY per day to 36.17 sets and 144.6 CNY, with statistical significance.

conclusionThe optimization of the intravenous infusion workflow can effectively decrease the cost of PPE while improving the efficiency of infusion and patients' satisfaction.

Indexed as

COVID-19Drug compoundingIntravenous infusionsPatient satisfactionPersonal protective equipmentWorkflow

Identifiers

PMID32313713
PMCPMC7165242

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.