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A multifaceted quality improvement intervention for CVD risk management in Australian primary healthcare: a protocol for a process evaluation

Overview of attention for article published in Implementation Science, December 2014
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Title
A multifaceted quality improvement intervention for CVD risk management in Australian primary healthcare: a protocol for a process evaluation
Published in
Implementation Science, December 2014
DOI 10.1186/s13012-014-0187-8
Pubmed ID
Authors

Bindu Patel, Anushka Patel, Stephen Jan, Tim Usherwood, Mark Harris, Katie Panaretto, Nicholas Zwar, Julie Redfern, Jesse Jansen, Jenny Doust, David Peiris

Abstract

BackgroundCardiovascular disease (CVD) is the leading cause of death and disability worldwide. Despite the widespread availability of evidence-based clinical guidelines and validated risk predication equations for prevention and management of CVD, their translation into routine practice is limited. We developed a multifaceted quality improvement intervention for CVD risk management which incorporates electronic decision support, patient risk communication tools, computerised audit and feedback tools, and monthly, peer-ranked performance feedback via a web portal. The intervention was implemented in a cluster randomised controlled trial in 60 primary healthcare services in Australia. Overall, there were improvements in risk factor recording and in prescribing of recommended treatments among under-treated individuals, but it is unclear how this intervention was used in practice and what factors promoted or hindered its use. This information is necessary to optimise intervention impact and maximally implement it in a post-trial context. In this study protocol, we outline our methods to conduct a theory-based, process evaluation of the intervention. Our aims are to understand how, why, and for whom the intervention produced the observed outcomes and to develop effective strategies for translation and dissemination.Methods/designWe will conduct four discrete but inter-related studies taking a mixed methods approach. Our quantitative studies will examine (1) the longer term effectiveness of the intervention post-trial, (2) patient and health service level correlates with trial outcomes, and (3) the health economic impact of implementing the intervention at scale. The qualitative studies will (1) identify healthcare provider perspectives on implementation barriers and enablers and (2) use video ethnography and patient semi-structured interviews to understand how cardiovascular risk is communicated in the doctor/patient interaction both with and without the use of intervention. We will also assess the costs of implementing the intervention in Australian primary healthcare settings which will inform scale-up considerations.DiscussionThis mixed methods evaluation will provide a detailed understanding of the process of implementing a quality improvement intervention and identify the factors that might influence scalability and sustainability.Trials registration 12611000478910.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 147 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 18%
Researcher 20 14%
Student > Ph. D. Student 20 14%
Student > Bachelor 13 9%
Student > Postgraduate 10 7%
Other 25 17%
Unknown 33 22%
Readers by discipline Count As %
Medicine and Dentistry 44 30%
Nursing and Health Professions 20 14%
Social Sciences 11 7%
Psychology 7 5%
Business, Management and Accounting 5 3%
Other 24 16%
Unknown 36 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 02 January 2015.
All research outputs
#13,925,649
of 22,774,233 outputs
Outputs from Implementation Science
#1,461
of 1,721 outputs
Outputs of similar age
#170,326
of 331,266 outputs
Outputs of similar age from Implementation Science
#47
of 60 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,721 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one is in the 14th percentile – i.e., 14% 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 331,266 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.