Evidence map›Paper›PMID 38395803›Full record

ArticleBMC infectious diseases2024

Identification of key potential infection processes and risk factors in the computed tomography examination process by FMEA method under COVID-19.

Lingzhi Jin, Meiting Ye, Wenhua Lin, Yong Ye, Yen-Ching Chuang, Jin-Yan Luo, Fuqin Tang

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2024. 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
2.5field-weighted citation impact, top 9% 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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
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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

7 authors at 3 institutions in 1 country.

Lingzhi Jin *Radiology department, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China.
Meiting Ye *Radiology department, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China.
Wenhua LinRadiology department, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China.
Yong YeInstitute of Public Health and Emergency Management, Taizhou University, Taizhou, Zhejiang, China.
Yen-Ching ChuangInstitute of Public Health and Emergency Management, Taizhou University, Taizhou, Zhejiang, China. yenching.chuang@gmail.com.
Jin-Yan LuoInstitute for Hospital Management, Tsing Hua University, Shenzhen, Guangdong, China. luojy22@mails.tsinghua.edu.cn.
Fuqin TangNursing Department, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China. fuqintang2022@yeah.net.
Taizhou University · CNTaizhou Central Hospital · CNTsinghua–Berkeley Shenzhen Institute · CN

Funding

The National Natural Science Foundation of China 72204183
6 · The paper itself

Abstract

purposeTo identify the key infection processes and risk factors in Computed Tomography (CT) examination process within the standard prevention and control measures for the COVID-19 epidemic, aiming to mitigate cross-infection occurrences in the hospital.

methodThe case hospital has assembled a team of 30 experts specialized in CT examination. Based on the CT examination process, the potential failure modes were assessed from the perspective of severity (S), occurrence probability (O), and detectability (D); they were then combined with corresponding risk prevention measures. Finally, key infection processes and risk factors were identified according to the risk priority number (RPN) and expert analysis.

resultsThrough the application of RPN and further analysis, four key potential infection processes were identified, including "CT request form (A

conclusionHospitals can publicize the precautions regarding CT examination through various channels, reducing the incidence of CT examination failure. Hospitals' cleaning services are usually outsourced, and the educational background of the staff employed in these services is generally not high. Therefore, during training and communication, it is more necessary to provide a series of scope and training programs that are aligned with their understanding level. The model developed in this study effectively identifies the key infection prevention process and critical risk factors, enhancing the safety of medical staff and patients. This has significant research implications for the potential epidemic of major infectious diseases.

Indexed as

COVID-19Cross InfectionHumansRisk FactorsTomographyTomography, X-Ray ComputedComputed tomographyFailure modes and effects AnalysisHealthcare workerRadiologyRisk analysis

Identifiers

PMID38395803
PMCPMC10893727
OpenAlexW4392094906

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.