Evidence map›Paper›PMID 31080588›Full record

ArticleAntimicrobial resistance and infection control2019

A national survey on the implementation of key infection prevention and control structures in German hospitals: results from 736 hospitals conducting the WHO Infection Prevention and Control Assessment Framework (IPCAF).

Seven Johannes Sam Aghdassi, Sonja Hansen, Peter Bischoff, Michael Behnke, Petra Gastmeier

Open access · goldAbstract read
In one paragraph

Article in Antimicrobial resistance and infection control, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
5.5field-weighted citation impact, top 3% 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

51 citing papers in PubMed, 105 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

5 authors at 1 institution in 1 country.

Seven Johannes Sam AghdassiCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Hygiene and Environmental Medicine, Berlin, Germany.ORCID 0000-0002-8263-3455
Sonja HansenCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Hygiene and Environmental Medicine, Berlin, Germany.
Peter BischoffCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Hygiene and Environmental Medicine, Berlin, Germany.
Michael BehnkeCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Hygiene and Environmental Medicine, Berlin, Germany.
Petra GastmeierCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Hygiene and Environmental Medicine, Berlin, Germany.
Humboldt-Universität zu Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Healthcare-associated infections (HAI) pose a burden on healthcare providers worldwide. To prevent HAI and strengthen infection prevention and control (IPC) structures, the WHO has developed a variety of tools and guidelines. Recently, the WHO released the Infection Prevention and Control Assessment Framework (IPCAF), a questionnaire-like tool designed for assessing IPC structures at the facility level. The IPCAF reflects the eight WHO core components of IPC. Data on the implementation of IPC measures in German hospitals are scarce. Therefore, it was our objective to utilize the IPCAF in order to gather information on the current state of IPC implementation in German hospitals, as well as to promote the IPCAF to a broad audience. Methods: The National Reference Center for Surveillance of Nosocomial Infections (NRZ) sent a translated version of the IPCAF to 1472 acute care hospitals in Germany. Data entry and transfer to the NRZ was done electronically between October and December 2018. The IPCAF was conceived in a way that depending on the selected answers a score was calculated, with 0 being the lowest possible and 800 the highest possible score. Depending on the overall score, the IPCAF allocated hospitals to four different "IPC levels": inadequate, basic, intermediate, and advanced. Results: A total of 736 hospitals provided a complete dataset and were included in the data analysis. The overall median score of all hospitals was 690, which corresponded to an advanced level of IPC. Only three hospitals (0.4%) fell into the category "basic", with 111 hospitals (15.1%) being "intermediate" and 622 hospitals (84.5%) being "advanced". In no case was the category "inadequate" allocated. More profound differences were found between the respective core components. Components on multimodal strategies and workload, staffing, ward design and bed occupancy revealed the lowest scores. Conclusions: IPC key aspects in general are well established in Germany. Potentials for improvement were identified particularly with regard to workload and staffing. Insufficient implementation of multimodal strategies was found to be another relevant deficit. Our survey represents a successful attempt at promoting the IPCAF and encouraging hospitals to utilize WHO tools for self-assessment.

Indexed as

Surveys and QuestionnairesCross InfectionGermanyHealth Plan ImplementationHospitalsHumansInfection ControlWorld Health OrganizationHealthcare-associated infectionImplementationInfection preventionSurveillanceSurvey

Identifiers

PMID31080588
PMCPMC6505265
OpenAlexW2944507841

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.