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The German Quality Network Sepsis: study protocol for the evaluation of a quality collaborative on decreasing sepsis-related mortality in a quasi-experimental difference-in-differences design

Overview of attention for article published in Implementation Science, January 2018
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  • Above-average Attention Score compared to outputs of the same age (52nd percentile)

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Title
The German Quality Network Sepsis: study protocol for the evaluation of a quality collaborative on decreasing sepsis-related mortality in a quasi-experimental difference-in-differences design
Published in
Implementation Science, January 2018
DOI 10.1186/s13012-017-0706-5
Pubmed ID
Authors

Daniel Schwarzkopf, Hendrik Rüddel, Matthias Gründling, Christian Putensen, Konrad Reinhart

Abstract

While sepsis-related mortality decreased substantially in other developed countries, mortality of severe sepsis remained as high as 44% in Germany. A recent German cluster randomized trial was not able to improve guideline adherence and decrease sepsis-related mortality within the participating hospitals, partly based on lacking support by hospital management and lacking resources for documentation of prospective data. Thus, more pragmatic approaches are needed to improve quality of sepsis care in Germany. The primary objective of the study is to decrease sepsis-related hospital mortality within a quality collaborative relying on claims data. The German Quality Network Sepsis (GQNS) is a quality collaborative involving 75 hospitals. This study protocol describes the conduction and evaluation of the start-up period of the GQNS running from March 2016 to August 2018. Democratic structures assure participatory action, a study coordination bureau provides central support and resources, and local interdisciplinary quality improvement teams implement changes within the participating hospitals. Quarterly quality reports focusing on risk-adjusted hospital mortality in cases with sepsis based on claims data are provided. Hospitals committed to publish their individual risk-adjusted mortality compared to the German average. A complex risk-model is used to control for differences in patient-related risk factors. Hospitals are encouraged to implement a bundle of interventions, e.g., interdisciplinary case analyses, external peer-reviews, hospital-wide staff education, and implementation of rapid response teams. The effectiveness of the GQNS is evaluated in a quasi-experimental difference-in-differences design by comparing the change of hospital mortality of cases with sepsis with organ dysfunction from a retrospective baseline period (January 2014 to December 2015) and the intervention period (April 2016 to March 2018) between the participating hospitals and all other German hospitals. Structural and process quality indicators of sepsis care as well as efforts for quality improvement are monitored regularly. The GQNS is a large-scale quality collaborative using a pragmatic approach based on claims data. A complex risk-adjustment model allows valid quality comparisons between hospitals and with the German average. If this study finds the approach to be useful for improving quality of sepsis care, it may also be applied to other diseases. ClinicalTrials.gov NCT02820675.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 13%
Student > Master 8 11%
Student > Bachelor 6 9%
Researcher 4 6%
Other 4 6%
Other 10 14%
Unknown 29 41%
Readers by discipline Count As %
Medicine and Dentistry 15 21%
Nursing and Health Professions 8 11%
Pharmacology, Toxicology and Pharmaceutical Science 4 6%
Economics, Econometrics and Finance 3 4%
Psychology 3 4%
Other 6 9%
Unknown 31 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 January 2018.
All research outputs
#13,063,214
of 23,016,919 outputs
Outputs from Implementation Science
#1,336
of 1,723 outputs
Outputs of similar age
#207,543
of 441,922 outputs
Outputs of similar age from Implementation Science
#43
of 46 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,723 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.8. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 441,922 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.