Evidence map›Paper›PMID 35399829›Full record

ArticleJournal of healthcare engineering2022

A PDCA Model for Disinfection Supply Rooms in the Context of Artificial Intelligence to Reduce the Incidence of Adverse Events and Improve the Disinfection Compliance Rate.

Yunxia Wang, Shuying Zhang, Mingmei Chi, Junmei Yu

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 31% 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, 5 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Yunxia WangThe Disinfection Supply Room of Changyi People's Hospital, Changyi, Shandong Province 261300, China.
Shuying ZhangHealth Examination Center of Changyi City People's Hospital, Changyi, Shandong Province,261300, China.
Mingmei ChiThe Second Ophthalmology Department of Changyi People's Hospital, Changyi, Shandong Province,261300, China.
Junmei YuDisinfection and Supply Department of Zibo Central Hospital of, Zibo, Shandong Province,255000, China.ORCID 0000-0002-1936-6198
Linyi People's Hospital · CNCentral Hospital of Zibo · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As an important section for controlling hospital infection, the main responsibility of the sterilization supply room is to clean, disinfect, sterilize, store, and distribute all medical devices that need to be reused in the hospital, and the quality of its work is closely related to the normal work of the hospital. Disinfection and supply department is the premise and foundation of the hospital department, mainly responsible for the recovery, cleaning, disinfection, sterilization, storage, and distribution of medical devices. The cleaning and disinfection work is characterized by strong technicality and high requirements, and the work effect is directly related to the safety of patients' lives and the occurrence of hospital infections. Therefore, there is an urgent need for a scientific and efficient management mode to be applied to the work of the supply room. The traditional management mode has some drawbacks, which affects the actual work of the hospital. Disinfection and supply rooms are an important part of hospital infection control and an important department to ensure the quality of health care. An effective management mode can not only improve the efficiency but also the overall quality of work, and PDCA (plan-do-check action cycle) as an advanced management mode can effectively improve the quality of management. This study investigates the effect of PDCA cycle management based on artificial intelligence algorithms in the nursing management of sterile supply rooms, and the experimental results show that the algorithm model can effectively reduce the incidence of adverse events and improve the rate of sterilization standards, which has certain practical significance.

Indexed as

Cross InfectionDisinfectionArtificial IntelligenceHospitalsHumansIncidence

Identifiers

PMID35399829
PMCPMC8986403
OpenAlexW4220740764

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.