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Tailoring implementation strategies for evidence-based recommendations using computerised clinical decision support systems: protocol for the development of the GUIDES tools

Overview of attention for article published in Implementation Science, March 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Tailoring implementation strategies for evidence-based recommendations using computerised clinical decision support systems: protocol for the development of the GUIDES tools
Published in
Implementation Science, March 2016
DOI 10.1186/s13012-016-0393-7
Pubmed ID
Authors

Stijn Van de Velde, Pavel Roshanov, Tiina Kortteisto, Ilkka Kunnamo, Bert Aertgeerts, Per Olav Vandvik, Signe Flottorp

Abstract

A computerised clinical decision support system (CCDSS) is a technology that uses patient-specific data to provide relevant medical knowledge at the point of care. It is considered to be an important quality improvement intervention, and the implementation of CCDSS is growing substantially. However, the significant investments do not consistently result in value for money due to content, context, system and implementation issues. The Guideline Implementation with Decision Support (GUIDES) project aims to improve the impact of CCDSS through optimised implementation based on high-quality evidence-based recommendations. To achieve this, we will develop tools that address the factors that determine successful CCDSS implementation. We will develop the GUIDES tools in four steps, using the methods and results of the Tailored Implementation for Chronic Diseases (TICD) project as a starting point: (1) a review of research evidence and frameworks on the determinants of implementing recommendations using CCDSS; (2) a synthesis of a comprehensive framework for the identified determinants; (3) the development of tools for use of the framework and (4) pilot testing the utility of the tools through the development of a tailored CCDSS intervention in Norway, Belgium and Finland. We selected the conservative management of knee osteoarthritis as a prototype condition for the pilot. During the process, the authors will collaborate with an international expert group to provide input and feedback on the tools. This project will provide guidance and tools on methods of identifying implementation determinants and selecting strategies to implement evidence-based recommendations through CCDSS. We will make the GUIDES tools available to CCDSS developers, implementers, researchers, funders, clinicians, managers, educators, and policymakers internationally. The tools and recommendations will be generic, which makes them scalable to a large spectrum of conditions. Ultimately, the better implementation of CCDSS may lead to better-informed decisions and improved care and patient outcomes for a wide range of conditions. PROSPERO, CRD42016033738.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Peru 1 <1%
Unknown 125 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 24 19%
Researcher 17 13%
Student > Doctoral Student 13 10%
Other 10 8%
Student > Ph. D. Student 10 8%
Other 29 23%
Unknown 24 19%
Readers by discipline Count As %
Medicine and Dentistry 44 35%
Nursing and Health Professions 15 12%
Business, Management and Accounting 8 6%
Computer Science 8 6%
Agricultural and Biological Sciences 3 2%
Other 19 15%
Unknown 30 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 16 February 2017.
All research outputs
#5,489,040
of 25,765,370 outputs
Outputs from Implementation Science
#966
of 1,821 outputs
Outputs of similar age
#77,837
of 314,391 outputs
Outputs of similar age from Implementation Science
#25
of 45 outputs
Altmetric has tracked 25,765,370 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,821 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one is in the 46th percentile – i.e., 46% 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 314,391 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.