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Evidence-based usability design principles for medication alerting systems

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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1 news outlet
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2 X users

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28 Dimensions

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68 Mendeley
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Title
Evidence-based usability design principles for medication alerting systems
Published in
BMC Medical Informatics and Decision Making, July 2018
DOI 10.1186/s12911-018-0615-9
Pubmed ID
Authors

Romaric Marcilly, Elske Ammenwerth, Erin Roehrer, Julie Niès, Marie-Catherine Beuscart-Zéphir

Abstract

Usability flaws in medication alerting systems may have a negative impact on clinical use and patient safety. In order to prevent the release of alerting systems that contain such flaws, it is necessary to provide designers and evaluators with evidence-based usability design principles. The objective of the present study was to develop a comprehensive, structured list of evidence-based usability design principles for medication alerting systems. Nine sets of design principles for medication alerting systems were analyzed, summarized, and structured. We then matched the summarized principles with a list of usability flaws in order to determine the level of underlying evidence. Fifty-eight principles were summarized from the literature and two additional principles were defined, so that each flaw was matched with a principle. We organized the 60 summarized usability design principles into 6 meta-principles, 38 principles, and 16 sub-principles. Only 15 principles were not matched with a usability flaw. The 6 meta-principles respectively covered the improvement of the signal-to-noise ratio, the support for collaborative working, the fit with a clinician's workflow, the data display, the transparency of the alerting system, and the actionable tools to be provided within an alert. It is possible to develop an evidence-based, structured, comprehensive list of usability design principles that are specific to medication alerting systems and are illustrated by the corresponding usability flaws. This list represents an improvement over the current literature. Each principle is now associated with the best available evidence of its violation. This knowledge may help to improve the usability of medication alerting systems and, ultimately, decrease the harmful consequences of the systems' usability flaws.

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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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 18%
Other 7 10%
Student > Master 7 10%
Student > Bachelor 6 9%
Student > Doctoral Student 5 7%
Other 18 26%
Unknown 13 19%
Readers by discipline Count As %
Medicine and Dentistry 13 19%
Computer Science 10 15%
Nursing and Health Professions 7 10%
Business, Management and Accounting 5 7%
Engineering 5 7%
Other 10 15%
Unknown 18 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 2019.
All research outputs
#2,747,265
of 23,096,849 outputs
Outputs from BMC Medical Informatics and Decision Making
#205
of 2,013 outputs
Outputs of similar age
#57,466
of 329,806 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 27 outputs
Altmetric has tracked 23,096,849 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,013 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 89% 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 329,806 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 82% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.