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Categorical Risk Perception Drives Variability in Antibiotic Prescribing in the Emergency Department: A Mixed Methods Observational Study

Overview of attention for article published in Journal of General Internal Medicine, June 2017
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

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1 news outlet
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33 X users
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2 Facebook pages

Citations

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50 Dimensions

Readers on

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100 Mendeley
Title
Categorical Risk Perception Drives Variability in Antibiotic Prescribing in the Emergency Department: A Mixed Methods Observational Study
Published in
Journal of General Internal Medicine, June 2017
DOI 10.1007/s11606-017-4099-6
Pubmed ID
Authors

Eili Y. Klein, Elena M. Martinez, Larissa May, Mustapha Saheed, Valerie Reyna, David A. Broniatowski

Abstract

Adherence to evidence-based antibiotic therapy guidelines for treatment of upper respiratory tract infections (URIs) varies widely among clinicians. Understanding this variability is key for reducing inappropriate prescribing. To measure how emergency department (ED) clinicians' perceptions of antibiotic prescribing risks affect their decision-making. Clinician survey based on fuzzy-trace theory, a theory of medical decision-making, combined with retrospective data on prescribing outcomes for URI/pneumonia visits in two EDs. The survey predicts the categorical meanings, or gists, that individuals derive from given information. ED physicians, residents, and physician assistants (PAs) who completed surveys and treated patients with URI/pneumonia diagnoses between August 2014 and December 2015. Gists derived from survey responses and their association with rates of antibiotic prescribing per visit. Of 4474 URI/pneumonia visits, 2874 (64.2%) had an antibiotic prescription. However, prescribing rates varied from 7% to 91% for the 69 clinicians surveyed (65.2% response rate). Clinicians who framed therapy-prescribing decisions as a categorical choice between continued illness and possibly beneficial treatment ("why not take a risk?" gist, which assumes antibiotic therapy is essentially harmless) had higher rates of prescribing (OR 1.28 [95% CI, 1.06-1.54]). Greater agreement with the "antibiotics may be harmful" gist was associated with lower prescribing rates (OR 0.81 [95% CI, 0.67-0.98]). Our results indicate that clinicians who perceive prescribing as a categorical choice between patients remaining ill or possibly improving from therapy are more likely to prescribe antibiotics. However, this strategy assumes that antibiotics are essentially harmless. Clinicians who framed decision-making as a choice between potential harms from therapy and continued patient illness (e.g., increased appreciation of potential harms) had lower prescribing rates. These results suggest that interventions to reduce inappropriate prescribing should emphasize the non-negligible possibility of serious side effects.

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X Demographics

The data shown below were collected from the profiles of 33 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 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 100 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 17%
Researcher 14 14%
Student > Master 11 11%
Student > Bachelor 8 8%
Student > Postgraduate 5 5%
Other 21 21%
Unknown 24 24%
Readers by discipline Count As %
Medicine and Dentistry 24 24%
Pharmacology, Toxicology and Pharmaceutical Science 9 9%
Social Sciences 6 6%
Nursing and Health Professions 5 5%
Psychology 5 5%
Other 21 21%
Unknown 30 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 01 August 2017.
All research outputs
#1,235,442
of 23,911,072 outputs
Outputs from Journal of General Internal Medicine
#1,014
of 7,806 outputs
Outputs of similar age
#25,917
of 319,831 outputs
Outputs of similar age from Journal of General Internal Medicine
#10
of 73 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,806 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.8. This one has done well, scoring higher than 86% 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 319,831 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 91% of its contemporaries.
We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.