Evidence map›Paper›PMID 36821562›Full record

ArticlePloS one2023

Dynamic risk assessment of hospital oxygen supply system by HAZOP and intuitionistic fuzzy.

Yeganeh Yousofnejad, Fatemeh Afsari, Mahboubeh Es'haghi

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

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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 1 country.

Yeganeh YousofnejadStudent Research Committee, Faculty of Public Health, Kerman University of Medical Sciences, Kerman, Iran.ORCID 0000-0003-0722-0340
Fatemeh AfsariDepartment of Computer Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
Mahboubeh Es'haghiDepartment of Occupational Health Engineering and Safety at Work, Faculty of Public Health, Kerman University of Medical Sciences, Kerman, Iran.ORCID 0000-0003-1310-7360
Kerman University of Medical Sciences · IRShahid Bahonar University of Kerman · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Events such as oxygen leakage in the oxygen generation systems can have severe consequences, such as fire and explosion. In addition, the disruption in the oxygenation systems can lead to a threat to patients' lives. Thus, this study aimed to identify the significant deviations in the oxygen supply system as critical equipment at hospitals based on the Hazard and Operability (HAZOP) method. Despite the advantages of risk assessment techniques, hazard identification techniques are still being utilized with deterministic and unreliable values and have a completely static nature. Therefore, using dynamic techniques to overcome intrinsic ambiguity in the risk assessment process through fuzzy sets has been recommended. Additionally, we proposed the HAZOP methodology to integrate with the intuitionistic fuzzy system for assessing the medical oxygen supply system using Pressure Swing Absorbance technology as a proactive approach. The results showed that the intuitionistic fuzzy approach, combined with the risk assessment method, is a suitable tool to eliminate uncertainty, improve decision-making, and result in more detailed and accurate findings. The approach adopted in this study can be used as a needs assessment tool to optimize maintenance programs and provide the necessary training for the staff, maintenance operators, and medical equipment managers.

Indexed as

Fuzzy LogicHumansUncertainty

Identifiers

PMID36821562
PMCPMC9949673
OpenAlexW4321610095

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.