↓ Skip to main content

Explaining outcomes in major system change: a qualitative study of implementing centralised acute stroke services in two large metropolitan regions in England

Overview of attention for article published in Implementation Science, June 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
27 X users

Citations

dimensions_citation
50 Dimensions

Readers on

mendeley
116 Mendeley
Title
Explaining outcomes in major system change: a qualitative study of implementing centralised acute stroke services in two large metropolitan regions in England
Published in
Implementation Science, June 2016
DOI 10.1186/s13012-016-0445-z
Pubmed ID
Authors

Naomi J. Fulop, Angus I. G. Ramsay, Catherine Perry, Ruth J. Boaden, Christopher McKevitt, Anthony G. Rudd, Simon J. Turner, Pippa J. Tyrrell, Charles D. A. Wolfe, Stephen Morris

Abstract

Implementing major system change in healthcare is not well understood. This gap may be addressed by analysing change in terms of interrelated components identified in the implementation literature, including decision to change, intervention selection, implementation approaches, implementation outcomes, and intervention outcomes. We conducted a qualitative study of two cases of major system change: the centralisation of acute stroke services in Manchester and London, which were associated with significantly different implementation outcomes (fidelity to referral pathway) and intervention outcomes (provision of evidence-based care, patient mortality). We interviewed stakeholders at national, pan-regional, and service-levels (n = 125) and analysed 653 documents. Using a framework developed for this study from the implementation science literature, we examined factors influencing implementation approaches; how these approaches interacted with the models selected to influence implementation outcomes; and their relationship to intervention outcomes. London and Manchester's differing implementation outcomes were influenced by the different service models selected and implementation approaches used. Fidelity to the referral pathway was higher in London, where a 'simpler', more inclusive model was used, implemented with a 'big bang' launch and 'hands-on' facilitation by stroke clinical networks. In contrast, a phased approach of a more complex pathway was used in Manchester, and the network acted more as a platform to share learning. Service development occurred more uniformly in London, where service specifications were linked to financial incentives, and achieving standards was a condition of service launch, in contrast to Manchester. 'Hands-on' network facilitation, in the form of dedicated project management support, contributed to achievement of these standards in London; such facilitation processes were less evident in Manchester. Using acute stroke service centralisation in London and Manchester as an example, interaction between model selected and implementation approaches significantly influenced fidelity to the model. The contrasting implementation outcomes may have affected differences in provision of evidence-based care and patient mortality. The framework used in this analysis may support planning and evaluating major system changes, but would benefit from application in different healthcare contexts.

X Demographics

X Demographics

The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 116 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 17%
Student > Ph. D. Student 15 13%
Researcher 13 11%
Student > Bachelor 8 7%
Other 7 6%
Other 21 18%
Unknown 32 28%
Readers by discipline Count As %
Medicine and Dentistry 24 21%
Nursing and Health Professions 15 13%
Social Sciences 14 12%
Business, Management and Accounting 6 5%
Psychology 3 3%
Other 11 9%
Unknown 43 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 06 November 2017.
All research outputs
#2,028,467
of 24,397,600 outputs
Outputs from Implementation Science
#412
of 1,760 outputs
Outputs of similar age
#36,340
of 345,420 outputs
Outputs of similar age from Implementation Science
#11
of 40 outputs
Altmetric has tracked 24,397,600 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,760 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one has done well, scoring higher than 76% 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 345,420 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 89% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.