Evidence map›Paper›PMID 38028363›Full record

ArticleInfection prevention in practice2023

Effects of data-driven feedback on nurses' and physicians' hand hygiene in hospitals - a non-resource-intensive intervention in real-life clinical practice.

Anne-Mette Iversen, Marco Bo Hansen, Svend Ellermann-Eriksen

Open access · goldAbstract read
In one paragraph

Article in Infection prevention in practice, 2023. 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
0.6field-weighted citation impact, top 33% 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, 3 citations in OpenAlex.

  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

3 authors at 1 institution in 1 country.

Anne-Mette IversenDepartment of Oncology, Aarhus University Hospital and Aarhus University, Denmark.
Marco Bo HansenKonduto ApS, Sani Nudge, Copenhagen, Denmark.
Svend Ellermann-EriksenDepartment of Clinical Microbiology, Aarhus University Hospital and Aarhus University, Denmark.
Aarhus University Hospital · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hand hygiene (HH) by healthcare workers (HCWs) is one of the most important measures to prevent hospital-acquired infections. However, HCWs struggle to adhere to HH guidelines. We aimed to investigate the effect of a non-resource intensive intervention with group and individual feedback on HCWs HH in a real-life clinical practice during the COVID-19 pandemic. Methods: In 2021, an 11-month prospective, interventional study was conducted in two inpatient departments at a Danish university hospital. An automated hand hygiene monitoring system (Sani Nudge™) was used to collect data. HH opportunities and alcohol-based hand rub events were measured. Data were provided as HH compliance (HHC) rates. We compared HHC across 1) a baseline period, 2) an intervention period with weekly feedback in groups, followed by 3) an intervention period with weekly individual feedback on emails, and 4) a follow-up period. Results: We analyzed data from physicians ( Conclusions: The automated hand hygiene monitoring system enabled assessment of the interventions. We found no significant effect of group or individual feedback at the two departments. However, other factors may have influenced the results during the pandemic, such as time constraints, workplace culture, and the degree of leadership support.

Indexed as

Electronic monitoring systemsGroup feedbackHospital-acquired infectionIndividual feedbackInfection preventionNudging

Identifiers

PMID38028363
PMCPMC10679856
OpenAlexW4388036692

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.