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Taking the heat or taking the temperature? A qualitative study of a large-scale exercise in seeking to measure for improvement, not blame

Overview of attention for article published in Social Science & Medicine, February 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

twitter
150 tweeters
facebook
3 Facebook pages

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
88 Mendeley
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Title
Taking the heat or taking the temperature? A qualitative study of a large-scale exercise in seeking to measure for improvement, not blame
Published in
Social Science & Medicine, February 2018
DOI 10.1016/j.socscimed.2017.12.033
Pubmed ID
Authors

Natalie Armstrong, Liz Brewster, Carolyn Tarrant, Ruth Dixon, Janet Willars, Maxine Power, Mary Dixon-Woods

Abstract

Measurement of quality and safety has an important role in improving healthcare, but is susceptible to unintended consequences. One frequently made argument is that optimising the benefits from measurement requires controlling the risks of blame, but whether it is possible to do this remains unclear. We examined responses to a programme known as the NHS Safety Thermometer (NHS-ST). Measuring four common patient harms in diverse care settings with the goal of supporting local improvement, the programme explicitly eschews a role for blame. The study design was ethnographic. We conducted 115 hours of observation across 19 care organisations and conducted 126 interviews with frontline staff, senior national leaders, experts in the four harms, and the NHS-ST programme leadership and development team. We also collected and analysed relevant documents. The programme theory of the NHS-ST was based in a logic of measurement for improvement: the designers of the programme sought to avoid the appropriation of the data for any purpose other than supporting improvement. However, organisational participants - both at frontline and senior levels - were concerned that the NHS-ST functioned latently as a blame allocation device. These perceptions were influenced, first, by field-level logics of accountability and managerialism and, second, by specific features of the programme, including public reporting, financial incentives, and ambiguities about definitions that amplified the concerns. In consequence, organisational participants, while they identified some merits of the programme, tended to identify and categorise it as another example of performance management, rich in potential for blame. These findings indicate that the search to optimise the benefits of measurement by controlling the risks of blame remains challenging. They further suggest that a well-intentioned programme theory, while necessary, may not be sufficient for achieving goals for improvement in healthcare systems dominated by institutional logics that run counter to the programme theory.

Twitter Demographics

The data shown below were collected from the profiles of 150 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 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 88 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 17%
Researcher 11 13%
Student > Postgraduate 8 9%
Student > Ph. D. Student 7 8%
Student > Bachelor 6 7%
Other 24 27%
Unknown 17 19%
Readers by discipline Count As %
Medicine and Dentistry 21 24%
Nursing and Health Professions 15 17%
Social Sciences 6 7%
Psychology 5 6%
Business, Management and Accounting 4 5%
Other 17 19%
Unknown 20 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 89. 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 June 2018.
All research outputs
#251,404
of 16,084,376 outputs
Outputs from Social Science & Medicine
#202
of 9,232 outputs
Outputs of similar age
#10,218
of 410,199 outputs
Outputs of similar age from Social Science & Medicine
#14
of 150 outputs
Altmetric has tracked 16,084,376 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,232 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has done particularly well, scoring higher than 97% 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 410,199 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.