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Testing a systematic approach to identify and prioritise barriers to successful implementation of a complex healthcare intervention

Overview of attention for article published in BMC Medical Research Methodology, February 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
8 tweeters

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
100 Mendeley
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Title
Testing a systematic approach to identify and prioritise barriers to successful implementation of a complex healthcare intervention
Published in
BMC Medical Research Methodology, February 2017
DOI 10.1186/s12874-017-0298-4
Pubmed ID
Authors

Louise E. Craig, Leonid Churilov, Liudmyla Olenko, Dominique A. Cadilhac, Rohan Grimley, Simeon Dale, Cintia Martinez-Garduno, Elizabeth McInnes, Julie Considine, Jeremy M. Grimshaw, Sandy Middleton

Abstract

Multiple barriers may inhibit the adoption of clinical interventions and impede successful implementation. Use of standardised methods to prioritise barriers to target when selecting implementation interventions is an understudied area of implementation research. The aim of this study was to describe a method to identify and prioritise barriers to the implementation of clinical practice elements which were used to inform the development of the T(3) trial implementation intervention (Triage, Treatment [thrombolysis administration; monitoring and management of temperature, blood glucose levels, and swallowing difficulties] and Transfer of stroke patients from Emergency Departments [ED]). A survey was developed based on a literature review and data from a complementary trial to identify the commonly reported barriers for the nine T(3) clinical care elements. This was administered via a web-based questionnaire to a purposive sample of Australian multidisciplinary clinicians and managers in acute stroke care. The questionnaire addressed barriers to each of the nine T(3) trial clinical care elements. Participants produced two ranked lists: on their perception of: firstly, how influential each barrier was in preventing clinicians from performing the clinical care element (influence attribute); and secondly how difficult the barrier was to overcome (difficulty attribute). The rankings for both influence and difficulty were combined to classify the barriers according to three categories ('least desirable', desirable' or 'most desirable' to target) to assist interpretation. All invited participants completed the survey; (n = 17; 35% medical, 35% nursing, 18% speech pathology, 12% bed managers). The barriers classified as most desirable to target and overcome were a 'lack of protocols for the management of fever' and 'not enough blood glucose monitoring machines'. A structured decision-support procedure has been illustrated and successfully applied to identify and prioritise barriers to target within an implementation intervention. This approach may prove to be a useful in other studies and as an adjunct to undertaking barrier assessments within individual sites when planning implementation interventions.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 100 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 15%
Student > Master 13 13%
Researcher 12 12%
Student > Bachelor 7 7%
Student > Doctoral Student 7 7%
Other 18 18%
Unknown 28 28%
Readers by discipline Count As %
Medicine and Dentistry 22 22%
Nursing and Health Professions 18 18%
Psychology 7 7%
Social Sciences 5 5%
Biochemistry, Genetics and Molecular Biology 3 3%
Other 11 11%
Unknown 34 34%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 20 February 2017.
All research outputs
#5,723,249
of 22,953,506 outputs
Outputs from BMC Medical Research Methodology
#808
of 2,026 outputs
Outputs of similar age
#108,119
of 420,233 outputs
Outputs of similar age from BMC Medical Research Methodology
#15
of 34 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 2,026 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 59% of its peers.
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 420,233 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 74% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.