Evidence map›Paper›PMID 37247215›Full record

SynthesisJournal of medical Internet research2023

Effects of the Implementation of Intelligent Technology for Hand Hygiene in Hospitals: Systematic Review and Meta-analysis.

Yi Zhang, Xiangping Chen, Yuewen Lao, Xiaobin Qiu, Kang Liu, Yiyu Zhuang, Xiaoyan Gong, Ping Wang

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 6% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Article
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  5. Article
  6. Review
  7. Article
  8. Observational
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  11. Review
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

8 authors at 1 institution in 1 country.

Yi Zhang *Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.ORCID 0000-0002-8612-8114
Xiangping ChenSir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.ORCID 0009-0006-5170-5002
Yuewen LaoSir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.ORCID 0000-0003-2320-1705
Xiaobin QiuSir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.ORCID 0009-0004-9578-9696
Kang LiuSir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.ORCID 0009-0004-0597-6253
Yiyu ZhuangSir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.ORCID 0000-0002-1416-1919
Xiaoyan GongSir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.ORCID 0009-0000-9246-8919
Ping WangSir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.ORCID 0009-0006-0493-7687
Sir Run Run Shaw Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe World Health Organization recommends regular hand hygiene monitoring and feedback to improve hand hygiene behaviors and health care-associated infection rates. Intelligent technologies for hand hygiene are increasingly being developed as alternative or supplemental monitoring approaches. However, there is insufficient evidence regarding the effect of this type of intervention, with conflicting results in the literature.

objectiveWe conduct a systematic review and meta-analysis to evaluate the effects of using intelligent technology for hand hygiene in hospitals.

methodsWe searched 7 databases from inception to December 31, 2022. Two reviewers independently and blindly selected studies, extracted data, and assessed the risk of bias. A meta-analysis was performed using the RevMan 5.3 and STATA 15.1 software. Sensitivity and subgroup analyses were also conducted. Overall certainty of evidence was appraised using the Grading of Recommendations Assessment, Development, and Evaluation approach. The systematic review protocol was registered.

resultsThe 36 studies comprised 2 randomized controlled trials and 34 quasi-experimental studies. The included intelligent technologies involved 5 functions: performance reminders,electronic counting and remote monitoring,data processing,feedback,and education. Compared with usual care, the intelligent technology intervention for hand hygiene improved health care workers' hand hygiene compliance (risk ratio 1.56, 95% CI 1.47-1.66; P<.001), reduced health care-associated infection rates (risk ratio 0.25, 95% CI 0.19-0.33; P<.001), and was not associated with multidrug-resistant organism detection rates (risk ratio 0.53, 95% CI 0.27-1.04; P=.07). Three covariates, including publication year, study design, and intervention, were not factors of hand hygiene compliance or hospital-acquired infection rates analyzed by meta-regression. Sensitivity analysis showed stable results except for the pooled outcome of multidrug-resistant organism detection rates. The caliber of 3 pieces of evidence suggested a dearth of high-caliber research.

conclusionsIntelligent technologies for hand hygiene play an integral role in hospital. However, low quality of evidence and important heterogeneity were observed. Larger clinical trials are required to evaluate the impact of intelligent technology on multidrug-resistant organism detection rates and other clinical outcomes.

Indexed as

Cross InfectionHand HygieneHealth PersonnelHospitalsHumanshand hygieneinfectionintelligent technologymeta-analysismultidrug resistancesystematic review

Identifiers

PMID37247215
PMCPMC10262028
OpenAlexW4327881697

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.