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Moving low value care lists into action: prioritizing candidate health technologies for reassessment using administrative data

Overview of attention for article published in BMC Health Services Research, August 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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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1 news outlet
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34 X users

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Title
Moving low value care lists into action: prioritizing candidate health technologies for reassessment using administrative data
Published in
BMC Health Services Research, August 2018
DOI 10.1186/s12913-018-3459-1
Pubmed ID
Authors

Lesley J. J. Soril, Brayan V. Seixas, Craig Mitton, Stirling Bryan, Fiona M. Clement

Abstract

Active management of existing health technologies (e.g., devices, diagnostic, and/or medical procedures) to ensure the delivery of high value care is increasingly recognized around the world. A number of initiatives have raised awareness of technologies that may be overused, mis-used, or potentially harmful by compiling them into lists of low value care. However, despite the growing number of lists, changes to local healthcare practices remain challenging for many systems. The objective of this study was to develop and implement a process, leveraging existing initiatives and data assets, to produce a list of prioritized low value technologies for health technology reassessment (HTR). An expert advisory committee comprised of clinical experts and health system decision-makers was convened to determine key process requirements. Once developed, the process was piloted to assess feasibility in the Canadian province of British Columbia (BC). The expert advisory committee identified five required attributes for the process: data-driven, routine and replicable, actionable, stakeholder collaboration, and high return on investment. Guided by these attributes, a 5-step process was developed. First, over 1300 published low value technologies (i.e., from the National Institute for Health and Care Excellence [NICE] "do not do" recommendations, low value technologies in the Australian Medical Benefits Schedule, and Choosing Wisely "Top 5" lists) were identified. Using appropriate coding systems for BC's administrative health data (e.g., International Classification of Diseases [ICD]), the low value technologies were queried to examine frequencies and costs of technology use. This information was used to rank potential candidates for reassessment based on high annual budgetary impact. Lastly, clinical experts reviewed the ranked technologies prior to broad dissemination and stakeholder action. Pilot testing of the process in BC resulted in the prioritization of 9 initial candidate technologies for reassessment. This is the first account of a systematic approach to move a collective body of low value technology recommendations into action in a healthcare setting. This work demonstrates the feasibility and strength of using administrative data to identify and prioritize low value technologies for HTR at a population-level.

X Demographics

X Demographics

The data shown below were collected from the profiles of 34 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 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 13%
Student > Doctoral Student 7 11%
Other 6 9%
Researcher 5 8%
Student > Master 5 8%
Other 8 13%
Unknown 25 39%
Readers by discipline Count As %
Medicine and Dentistry 9 14%
Business, Management and Accounting 6 9%
Nursing and Health Professions 6 9%
Economics, Econometrics and Finance 3 5%
Agricultural and Biological Sciences 2 3%
Other 8 13%
Unknown 30 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 18 January 2023.
All research outputs
#1,253,783
of 25,784,004 outputs
Outputs from BMC Health Services Research
#349
of 8,765 outputs
Outputs of similar age
#25,653
of 341,661 outputs
Outputs of similar age from BMC Health Services Research
#13
of 193 outputs
Altmetric has tracked 25,784,004 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,765 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one has done particularly well, scoring higher than 96% 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 341,661 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 92% of its contemporaries.
We're also able to compare this research output to 193 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 93% of its contemporaries.