Evidence map›Paper›PMID 38293376›Full record

ArticleHeliyon2024

Factors associated with cleaning quality of reusable medical devices at a single center in China.

Juanli Huang, Liangying Yi, Yanhua Chen, Juan Hu

Abstract read
In one paragraph

Article in Heliyon, 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
–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. 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

4 authors.

Juanli HuangDepartment of Sterile Processing Nursing, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Liangying YiDepartment of Sterile Processing Nursing, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Yanhua ChenDepartment of Sterile Processing Nursing, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Juan HuDepartment of Sterile Processing Nursing, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Improper cleaning is one of the main causes of sub-optimal levels of sterilization, and also a risk factor in terms of nosocomial infections. We aimed to investigate the factors associated with the cleaning quality of the reusable medical devices and prescribe improvement measures for ensuring the safe use of the devices and for iatrogenic infection control. Methods: An expert consultation was conducted to identify the factors associated with the cleaning quality of reusable medical devices. A self-designed quality inspection form for reusable medical device cleaning was used to collect the data concerning the factors associated with the cleaning quality of the reusable medical devices cleaned at our hospital's central sterile supply department (CSSD) during January to June 2022. We also investigated the cleaning personnel's perceptions and knowledge of medical devices cleaning by means of a self-designed questionnaire. Results: Statistically significant differences ( Conclusions: The quality of reusable medical device cleaning should be improved by: adherence to standard cleaning procedures, choosing the correct cleaning method and pre-treatment, improving cleaning personnel's knowledge and perceptions of medical device cleaning, and disassembling the medical devices with complex structures so as to reduce the quality defects of medical device cleaning.

Indexed as

Cleaning qualityFactorsImprovement measuresReusable medical devices

Identifiers

PMID38293376
PMCPMC10826661

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.