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Assessing Use Errors Related to the Interface Design of Electrosurgical Units

Overview of attention for article published in AORN Journal, January 2018
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2 X users
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1 Facebook page

Citations

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Title
Assessing Use Errors Related to the Interface Design of Electrosurgical Units
Published in
AORN Journal, January 2018
DOI 10.1002/aorn.12006
Pubmed ID
Authors

Jamie L Estock, Airan Li, Maureen C Casey, Matthew A Taylor, Monique Y Boudreaux-Kelly, Martin D Choma, Katrina Jacobs, David E Eibling

Abstract

Medical device use errors, such as instrument connection errors made with electrosurgical units (ESUs), can lead to adverse events. Current device acquisition processes at health care facilities do not typically include a proactive evaluation of use-error risk before device purchase. We conducted an evaluation to identify ESU user interface design features that can help prevent or mitigate instrument connection errors during clinical care. Thirty-six current ESU users participated in the evaluation. We used a randomized crossover design in which each participant used two ESU models in a simulated OR scenario. We compared participants' instrument connection accuracy, efficiency, and subjective feedback regarding the user interface design across the two ESU models. Overall, we found that the ESU model that incorporated more user interface design principles resulted in better performance and increased acceptance from users. Based on the results, we designed a decision-support tool to assess the risk of instrument connection errors before ESU purchase.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 17%
Student > Ph. D. Student 4 17%
Other 2 9%
Student > Bachelor 1 4%
Librarian 1 4%
Other 2 9%
Unknown 9 39%
Readers by discipline Count As %
Unspecified 4 17%
Medicine and Dentistry 4 17%
Nursing and Health Professions 2 9%
Engineering 2 9%
Social Sciences 1 4%
Other 1 4%
Unknown 9 39%
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 11 January 2018.
All research outputs
#15,466,445
of 24,520,935 outputs
Outputs from AORN Journal
#969
of 2,061 outputs
Outputs of similar age
#250,947
of 452,086 outputs
Outputs of similar age from AORN Journal
#31
of 45 outputs
Altmetric has tracked 24,520,935 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,061 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 49th percentile – i.e., 49% 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 452,086 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.